Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta

Directory of Open Access Journals (Sweden)

Barbara Gasse

2017-06-01

Full Text Available Amelogenesis imperfecta (AI designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene (MMP20 produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues, pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.

Evolutionary Analysis Predicts Sensitive Positions of MMP20 and Validates Newly- and Previously-Identified MMP20 Mutations Causing Amelogenesis Imperfecta.

Science.gov (United States)

Gasse, Barbara; Prasad, Megana; Delgado, Sidney; Huckert, Mathilde; Kawczynski, Marzena; Garret-Bernardin, Annelyse; Lopez-Cazaux, Serena; Bailleul-Forestier, Isabelle; Manière, Marie-Cécile; Stoetzel, Corinne; Bloch-Zupan, Agnès; Sire, Jean-Yves

2017-01-01

Amelogenesis imperfecta (AI) designates a group of genetic diseases characterized by a large range of enamel disorders causing important social and health problems. These defects can result from mutations in enamel matrix proteins or protease encoding genes. A range of mutations in the enamel cleavage enzyme matrix metalloproteinase-20 gene ( MMP20 ) produce enamel defects of varying severity. To address how various alterations produce a range of AI phenotypes, we performed a targeted analysis to find MMP20 mutations in French patients diagnosed with non-syndromic AI. Genomic DNA was isolated from saliva and MMP20 exons and exon-intron boundaries sequenced. We identified several homozygous or heterozygous mutations, putatively involved in the AI phenotypes. To validate missense mutations and predict sensitive positions in the MMP20 sequence, we evolutionarily compared 75 sequences extracted from the public databases using the Datamonkey webserver. These sequences were representative of mammalian lineages, covering more than 150 million years of evolution. This analysis allowed us to find 324 sensitive positions (out of the 483 MMP20 residues), pinpoint functionally important domains, and build an evolutionary chart of important conserved MMP20 regions. This is an efficient tool to identify new- and previously-identified mutations. We thus identified six functional MMP20 mutations in unrelated families, finding two novel mutated sites. The genotypes and phenotypes of these six mutations are described and compared. To date, 13 MMP20 mutations causing AI have been reported, making these genotypes and associated hypomature enamel phenotypes the most frequent in AI.

Analysing News for Stock Market Prediction

Science.gov (United States)

Ramalingam, V. V.; Pandian, A.; Dwivedi, shivam; Bhatt, Jigar P.

2018-04-01

Stock market means the aggregation of all sellers and buyers of stocks representing their ownership claims on the business. To be completely absolute about the investment on these stocks, proper knowledge about them as well as their pricing, for both present and future is very essential. Large amount of data is collected and parsed to obtain this essential information regarding the fluctuations in the stock market. This data can be any news or public opinions in general. Recently, many methods have been used, especially big unstructured data methods to predict the stock market values. We introduce another method of focusing on deriving the best statistical learning model for predicting the future values. The data set used is very large unstructured data collected from an online social platform, commonly known as Quindl. The data from this platform is then linked to a csv fie and cleaned to obtain the essential information for stock market prediction. The method consists of carrying out the NLP (Natural Language Processing) of the data and then making it easier for the system to understand, finds and identifies the correlation in between this data and the stock market fluctuations. The model is implemented using Python Programming Language throughout the entire project to obtain flexibility and convenience of the system.

Structural Dynamic Analyses And Test Predictions For Spacecraft Structures With Non-Linearities

Science.gov (United States)

Vergniaud, Jean-Baptiste; Soula, Laurent; Newerla, Alfred

2012-07-01

The overall objective of the mechanical development and verification process is to ensure that the spacecraft structure is able to sustain the mechanical environments encountered during launch. In general the spacecraft structures are a-priori assumed to behave linear, i.e. the responses to a static load or dynamic excitation, respectively, will increase or decrease proportionally to the amplitude of the load or excitation induced. However, past experiences have shown that various non-linearities might exist in spacecraft structures and the consequences of their dynamic effects can significantly affect the development and verification process. Current processes are mainly adapted to linear spacecraft structure behaviour. No clear rules exist for dealing with major structure non-linearities. They are handled outside the process by individual analysis and margin policy, and analyses after tests to justify the CLA coverage. Non-linearities can primarily affect the current spacecraft development and verification process on two aspects. Prediction of flights loads by launcher/satellite coupled loads analyses (CLA): only linear satellite models are delivered for performing CLA and no well-established rules exist how to properly linearize a model when non- linearities are present. The potential impact of the linearization on the results of the CLA has not yet been properly analyzed. There are thus difficulties to assess that CLA results will cover actual flight levels. Management of satellite verification tests: the CLA results generated with a linear satellite FEM are assumed flight representative. If the internal non- linearities are present in the tested satellite then there might be difficulties to determine which input level must be passed to cover satellite internal loads. The non-linear behaviour can also disturb the shaker control, putting the satellite at risk by potentially imposing too high levels. This paper presents the results of a test campaign performed in

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

Combined analyses of 20 common obesity susceptibility variants

DEFF Research Database (Denmark)

Sandholt, Camilla Helene; Sparsø, Thomas; Grarup, Niels

2010-01-01

Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes.......Genome-wide association studies and linkage studies have identified 20 validated genetic variants associated with obesity and/or related phenotypes. The variants are common, and they individually exhibit small-to-modest effect sizes....

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

Measurement of the analysing power T20 in the backward elastic scattering d-vector.p in the region of Δ-excitation and theoretical analysis of this reaction

International Nuclear Information System (INIS)

Boudard, A.

1984-03-01

We have measured the analysing power T 20 in the backward elastic scattering d.p for 16 energies of the deuteron from 300 MeV to 2300 MeV. This is the region of the observed bump in the backward excitation function of the cross section. This bump is usually thought to be a signature of a Δ(3/2,3/2 + ) dynamically excited in the intermediate state. We have also measured Ay and Ayy from 70 0 to 180 0 for Tsub(d) = 1200 MeV. We have compared both T 20 and the backward cross section with a coherent sum between direct neutron exchange (ONT) and Δ excitation by intermediate exchange of π and rho mesons (TME). The overall shape of the cross section is reproduced. Unlike the earlier measurement from Argonne, there is a deep minimum in T 20 at Tsub(d) = 600 MeV, in agreement with the predictions of direct exchange models. However, an additional structure producing a second minimum at Tsub(d) = 1400 MeV (√S = 3240 MeV) is never reproduced by our calculations. This suggests either that refinements in the Δ treatment are needed or that a new reaction mechanism (resonance) takes place in that region [fr

A Wear Rule and Cutter Life Prediction Model of a 20-in. TBM Cutter for Granite: A Case Study of a Water Conveyance Tunnel in China

Science.gov (United States)

Liu, Quansheng; Liu, Jianping; Pan, Yucong; Zhang, Xiaoping; Peng, Xingxin; Gong, Qiuming; Du, Lijie

2017-05-01

Disc cutter wear is one of the comprehensive results of the rock-machine interaction in tunnel boring machine (TBM) tunneling. The replacement of the disc cutter is a time-consuming and costly activity that can significantly reduce the TBM utilization ( U) and advance rate (AR), and has a major effect on the total time and cost of TBM tunneling projects. Therefore, the importance of predicting the cutter life accurately can never be overemphasized. Most cutter wear prediction models are only suitable for 17-in. or smaller disc cutters. However, use of large-diameter disc cutters has been an irresistible trend for large-section hard rock TBMs. This study attempts to reveal the genuine wear rule of a 20-in. disc cutter and develop a new empirical model for predicting the cutter life in granite based on field data collected from a water conveyance tunnel constructed by the TBM tunneling method in China. The field data including the actual cutter wear and the geological parameters along the studied tunnel were compiled in a special database that was subjected to statistical analysis to reveal the genuine wear rule of a 20-in. disc cutter and develop the reasonable correlations between some common intact rock parameters and the disc cutter life. These equations were developed based on data from massive to very massive granite with a UCS range of 40-100 MPa, which can be applied for the assessment of the cutter life of a 20-in. disc cutter in similar hard rock projects with similar rock strengths and rock abrasivities.

Application of ASTEC V2.0 to severe accident analyses for German KONVOI type reactors

International Nuclear Information System (INIS)

Nowack, H.; Erdmann, W.; Reinke, N.

2011-01-01

The integral code ASTEC is jointly developed by IRSN (Institut de Radioprotection et de Surete Nucleaire, France) and GRS (Germany). Its main objective is to simulate severe accident scenarios in PWRs from the initiating event up to the release of radioactive material into the environment. This paper describes the ASTEC modeling approach and the nodalisation of a KONVOI type PWR as an application example. Results from an integral severe accident study are presented and shortcomings as well as advantages are outlined. As a conclusion, the applicability of ASTEC V2.0 for deterministic severe accident analyses used for PSA level 2 and Severe Accident Management studies will be assessed. (author)

AUTO-MUTE 2.0: A Portable Framework with Enhanced Capabilities for Predicting Protein Functional Consequences upon Mutation.

Science.gov (United States)

Masso, Majid; Vaisman, Iosif I

2014-01-01

The AUTO-MUTE 2.0 stand-alone software package includes a collection of programs for predicting functional changes to proteins upon single residue substitutions, developed by combining structure-based features with trained statistical learning models. Three of the predictors evaluate changes to protein stability upon mutation, each complementing a distinct experimental approach. Two additional classifiers are available, one for predicting activity changes due to residue replacements and the other for determining the disease potential of mutations associated with nonsynonymous single nucleotide polymorphisms (nsSNPs) in human proteins. These five command-line driven tools, as well as all the supporting programs, complement those that run our AUTO-MUTE web-based server. Nevertheless, all the codes have been rewritten and substantially altered for the new portable software, and they incorporate several new features based on user feedback. Included among these upgrades is the ability to perform three highly requested tasks: to run "big data" batch jobs; to generate predictions using modified protein data bank (PDB) structures, and unpublished personal models prepared using standard PDB file formatting; and to utilize NMR structure files that contain multiple models.

AUTO-MUTE 2.0: A Portable Framework with Enhanced Capabilities for Predicting Protein Functional Consequences upon Mutation

Directory of Open Access Journals (Sweden)

Majid Masso

2014-01-01

Full Text Available The AUTO-MUTE 2.0 stand-alone software package includes a collection of programs for predicting functional changes to proteins upon single residue substitutions, developed by combining structure-based features with trained statistical learning models. Three of the predictors evaluate changes to protein stability upon mutation, each complementing a distinct experimental approach. Two additional classifiers are available, one for predicting activity changes due to residue replacements and the other for determining the disease potential of mutations associated with nonsynonymous single nucleotide polymorphisms (nsSNPs in human proteins. These five command-line driven tools, as well as all the supporting programs, complement those that run our AUTO-MUTE web-based server. Nevertheless, all the codes have been rewritten and substantially altered for the new portable software, and they incorporate several new features based on user feedback. Included among these upgrades is the ability to perform three highly requested tasks: to run “big data” batch jobs; to generate predictions using modified protein data bank (PDB structures, and unpublished personal models prepared using standard PDB file formatting; and to utilize NMR structure files that contain multiple models.

Factors predicting labor induction success: a critical analysis.

Science.gov (United States)

Crane, Joan M G

2006-09-01

Because of the risk of failed induction of labor, a variety of maternal and fetal factors as well as screening tests have been suggested to predict labor induction success. Certain characteristics of the woman (including parity, age, weight, height and body mass index), and of the fetus (including birth weight and gestational age) are associated with the success of labor induction; with parous, young women who are taller and lower weight having a higher rate of induction success. Fetuses with a lower birth weight or increased gestational age are also associated with increased induction success. The condition of the cervix at the start of induction is an important predictor, with the modified Bishop score being a widely used scoring system. The most important element of the Bishop score is dilatation. Other predictors, including transvaginal ultrasound (TVUS) and biochemical markers [including fetal fibronectin (fFN)] have been suggested. Meta-analyses of studies identified from MEDLINE, PubMed, and EMBASE and published from 1990 to October 2005 were performed evaluating the use of TVUS and fFN in predicting labor induction success in women at term with singleton gestations. Both TVUS and Bishop score predicted successful induction [likelihood ratio (LR)=1.82, 95% confidence interval (CI)=1.51-2.20 and LR=2.10, 95%CI=1.67-2.64, respectively]. As well, fFN and Bishop score predicted successful induction (LR=1.49, 95%CI=1.20-1.85, and LR=2.62, 95%CI=1.88-3.64, respectively). Although TVUS and fFN predicted successful labor induction, neither has been shown to be superior to Bishop score. Further research is needed to evaluate these potential predictors and insulin-like growth factor binding protein-1 (IGFBP-1), another potential biochemical marker.

Condition based maintenance of a 20 kV-PE/XLPE-insulated cable network using the IRC-Analysis; Zustandsorientierte Instandhaltung eines polymerisolierten 20-kV-Kabelnetzes mit der IRC-Analyse. Moderne Diagnostik reduziert Stoerungsrate

Energy Technology Data Exchange (ETDEWEB)

Hoff, G.; Kranz, H.G. [BUGH Wuppertal (Germany). Labs. fuer Hochspannungstechnik; Beigert, M.; Petzold, F. [Seba Dynatronic Mess- und Ortungstechnik GmbH, Baunach (Germany); Kneissl, C. [Bereich Konzeption und Messtechnik, Lech Elektrizitaetswerke AG, Augsburg (Germany)

2001-10-22

For a preventive maintenance of a polymer insulated cable network a destruction free estimation of the status of the buried PE/XLPE-cables is needed. This contribution presents a condition based maintenance concept which is based on the IRC-Analysis. With this concept a major German utility was able to reduce the amount of failures in a part of the 20kV-cable network. The general tendency of increasing faults was broken. (orig.) [German] Die praeventive Instandhaltung in polymerisolierten Kabelnetzen setzt eine zerstoerungsfreie Zustandbestimmung von gelegten PE/VPE-isolierten Kabeln voraus. Die-Verfasser beschreiben ein zustandsorientiertes Wartungskonzept auf Basis der IRC-Analyse, mit dem es gelungen ist, in einem Teil des 20-kV-Kabelnetzes eines Energieversorgers die in der Vergangenheit stetig steigende Stoerungsrate drastisch zu reduzieren. (orig.)

Visual Versus Fully Automated Analyses of 18F-FDG and Amyloid PET for Prediction of Dementia Due to Alzheimer Disease in Mild Cognitive Impairment.

Science.gov (United States)

Grimmer, Timo; Wutz, Carolin; Alexopoulos, Panagiotis; Drzezga, Alexander; Förster, Stefan; Förstl, Hans; Goldhardt, Oliver; Ortner, Marion; Sorg, Christian; Kurz, Alexander

2016-02-01

Biomarkers of Alzheimer disease (AD) can be imaged in vivo and can be used for diagnostic and prognostic purposes in people with cognitive decline and dementia. Indicators of amyloid deposition such as (11)C-Pittsburgh compound B ((11)C-PiB) PET are primarily used to identify or rule out brain diseases that are associated with amyloid pathology but have also been deployed to forecast the clinical course. Indicators of neuronal metabolism including (18)F-FDG PET demonstrate the localization and severity of neuronal dysfunction and are valuable for differential diagnosis and for predicting the progression from mild cognitive impairment (MCI) to dementia. It is a matter of debate whether to analyze these images visually or using automated techniques. Therefore, we compared the usefulness of both imaging methods and both analyzing strategies to predict dementia due to AD. In MCI participants, a baseline examination, including clinical and imaging assessments, and a clinical follow-up examination after a planned interval of 24 mo were performed. Of 28 MCI patients, 9 developed dementia due to AD, 2 developed frontotemporal dementia, and 1 developed moderate dementia of unknown etiology. The positive and negative predictive values and the accuracy of visual and fully automated analyses of (11)C-PiB for the prediction of progression to dementia due to AD were 0.50, 1.00, and 0.68, respectively, for the visual and 0.53, 1.00, and 0.71, respectively, for the automated analyses. Positive predictive value, negative predictive value, and accuracy of fully automated analyses of (18)F-FDG PET were 0.37, 0.78, and 0.50, respectively. Results of visual analyses were highly variable between raters but were superior to automated analyses. Both (18)F-FDG and (11)C-PiB imaging appear to be of limited use for predicting the progression from MCI to dementia due to AD in short-term follow-up, irrespective of the strategy of analysis. On the other hand, amyloid PET is extremely useful to

Predictive analyses of flow-induced vibration and fretting wear in steam generator tubes

International Nuclear Information System (INIS)

Axisa, F.

1989-01-01

Maintaining the service life of PWR steam generators under highly reliable conditions requires a complex design to prevent various damaging processes, including those related to flow induced vibration. Predictive analyses have to rely on numerical tools to compute the vibratory response of multi-supported tubes in association with experimental data and semi-empirical relationships for quantifying flow-induced excitation mechanisms and tube damaging processes. In the presence of loose supports tube dynamics becomes highly nonlinear in nature. To deal with such problems CEA and FRAMATOME developed a computer program called GERBOISE. This paper provides a short description of an experimental program currently in progress at CEN Saclay to validate the numerical methods implemented in GERBOISE. According to the results obtained so far reasonable agreement is obtained between experiment and numerical simulation, especially as averaged quantities are concerned

Comparison of the prognostic and predictive utilities of the 21-gene Recurrence Score assay and Adjuvant! for women with node-negative, ER-positive breast cancer: results from NSABP B-14 and NSABP B-20.

Science.gov (United States)

Tang, Gong; Shak, Steven; Paik, Soonmyung; Anderson, Stewart J; Costantino, Joseph P; Geyer, Charles E; Mamounas, Eleftherios P; Wickerham, D Lawrence; Wolmark, Norman

2011-05-01

The Oncotype DX Recurrence Score (RS) is a validated genomic predictor of outcome and response to adjuvant chemotherapy in ER-positive breast cancer. Adjuvant! was developed using SEER registry data and results from the Early Breast Cancer Clinical Trialists' overview analyses to estimate outcome and benefit from adjuvant hormonal therapy and chemotherapy. In this report we compare the prognostic and predictive utility of these two tools in node-negative, ER-positive breast cancer. RS and Adjuvant! results were available from 668 tamoxifen-treated NSABP B-14 patients, 227 tamoxifen-treated NSABP B-20 patients, and 424 chemotherapy plus tamoxifen-treated B-20 patients. Adjuvant! results were also available from 1952 B-20 patients. The primary endpoint was distant recurrence-free interval (DRFI). Cox proportional hazards models were used to compare the prognostic and predictive utility of RS and Adjuvant!. Both RS (P < 0.001) and Adjuvant! (P = 0.002) provided strong independent prognostic information in tamoxifen-treated patients. Combining RS and individual clinicopathologic characteristics provided greater prognostic discrimination than combining RS and the composite Adjuvant!. In the B-20 cohort with RS results (n = 651), RS was significantly predictive of chemotherapy benefit (interaction P = 0.031 for DRFI, P = 0.011 for overall survival [OS], P = 0.082 for disease-free survival [DFS]), but Adjuvant! was not (interaction P = 0.99, P = 0.311, and P = 0.357, respectively). However, in the larger B-20 sub-cohort (n = 1952), Adjuvant! was significantly predictive of chemotherapy benefit for OS (interaction P = 0.009) but not for DRFI (P = 0.219) or DFS (P = 0.099). Prognostic estimates can be optimized by combining RS and clinicopathologic information instead of simply combining RS and Adjuvant!. RS should be used for estimating relative chemotherapy benefit.

A cycle simulation model for predicting the performance of a diesel engine fuelled by diesel and biodiesel blends

International Nuclear Information System (INIS)

Gogoi, T.K.; Baruah, D.C.

2010-01-01

Among the alternative fuels, biodiesel and its blends are considered suitable and the most promising fuel for diesel engine. The properties of biodiesel are found similar to that of diesel. Many researchers have experimentally evaluated the performance characteristics of conventional diesel engines fuelled by biodiesel and its blends. However, experiments require enormous effort, money and time. Hence, a cycle simulation model incorporating a thermodynamic based single zone combustion model is developed to predict the performance of diesel engine. The effect of engine speed and compression ratio on brake power and brake thermal efficiency is analysed through the model. The fuel considered for the analysis are diesel, 20%, 40%, 60% blending of diesel and biodiesel derived from Karanja oil (Pongamia Glabra). The model predicts similar performance with diesel, 20% and 40% blending. However, with 60% blending, it reveals better performance in terms of brake power and brake thermal efficiency.

On the requirement for remodelling the spent nuclear fuel transportation casks for research reactors. A review of the drop impact analyses of JRC-80Y-20T

International Nuclear Information System (INIS)

2005-07-01

The Japan Atomic Energy Research Institute (JAERI) constructed two stainless steel transportation casks, JRC-80Y-20T, for spent nuclear fuels of research reactors and had utilized them for transportation since 1981. A modification of the design was applied to the United States of America (USA) for transportation of silicide fuels. Additional analyses employing the impact analysis code LS-DYNA that was often used for safety analysis were submitted by the JAERI to the USA in 2003 to show integrity of the packages; the casks were still not approved, because inelastic deformation was occurred on the surface of the lid touching to the body. To resolve this problem on design approval of transportation casks, a review group was formed in June 2004. The group examined the impact analyses by reviewing the input data and performing the sensitivity analyses. As the drop impact analyses were found to be practically reasonable, it was concluded that the approval of the USA for the transportation casks could not be obtained just by revising the analyses; therefore, remodelling the casks is required. (author)

Analyses of hypothetical nuclear criticality excursions in 10- and 20-MW freezer/sublimer vessels

International Nuclear Information System (INIS)

Haught, C.F.; Jordan, W.C.; Basoglu, B.; Dodds, H.L.; Wilkinson, A.D.

1995-01-01

A theoretical model is used to predict the consequences of a postulated hypothetical nuclear criticality excursion in a freezer/sublimer (F/S). Previous work has shown that an intrusion of water into a F/S may result in a critical configuration. A first attempt is made to model the neutronic and thermal-hydraulic phenomena occurring during a criticality excursion involving both uranium hexafluoride (UF 6 ) and uranyl fluoride (UO 2 F 2 ) solution, which is present in the F/S during upset conditions. The model employs point neutronics coupled with simple thermal hydraulics. Reactivity feedback from changes in the properties of the system are included in the model. The excursion is studied in a 10-MW F/S with an initial load of 3,500 kg of 5% weight enriched UF 6 and in a 20-MW F/S with an initial load of 6,800 kg of 2% weight enriched UF 6 . The magnitude of the fission release determined in this work is 5.93 x 10 18 fissions in the 10-MW F/S and 4.21 x 10 18 fissions in the 20-MW F/S. In order to demonstrate the reliability of the techniques used in this work, a limited validation study was conducted by comparing the fission release and peak fission rate determined by this work with experimental results for a limited number of experiments. The agreement between calculations and experiments in the validation study is considered to be satisfactory. The calculational results for the hypothetical accidents in the two F/S vessels appear reasonable

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

Directory of Open Access Journals (Sweden)

Kihara Daisuke

2010-05-01

Full Text Available Abstract Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria. The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP

Prediction of the systemic exposure to oral 9-amino-20(S)-camptothecin using single-sample analysis

NARCIS (Netherlands)

Sparreboom, A.; de Jonge, M. J.; Punt, C. J.; Loos, W. J.; Nooter, K.; Stoter, G.; Porro, M. G.; Verweij, J.

1999-01-01

The purpose of this study was to develop and validate limited-sampling strategies for prediction of the area under the plasma-concentration time curves (AUCs) of the lactone and total (i. e., lactone plus carboxylate) forms of the novel topoisomerase-I inhibitor 9-amino-20(S)-camptothecin (9-AC).

Predictive value of ocular trauma score in open globe combat eye injuries

International Nuclear Information System (INIS)

Islam, Q.

2016-01-01

Prediction of final visual outcome in ocular injuries is of paramount importance and various prognostic models have been proposed to predict final visual outcome. The objective of this study was to validate the predictive value of ocular trauma score (OTS) in patients with combat related open globe injuries and to evaluate the factors affecting the final visual outcome. Methods: Data of 93 patients admitted in AFIO Rawalpindi between Jan 2010 to June 2014 with combat related open globe ocular injuries was analysed. Initial and final best corrected visual acuity (BCVA) was categorized as No Light Perception (NLP), Light Perception (LP) to Hand Movement (HM), 1/200-19/200, 20/200-20/50, and =20/40. OTS was calculated for each eye by assigning numerical raw points to six variables and then scores were stratified into five OTS categories. Results: Mean age of study population was 28.77 ± 8.37 years. Presenting visual acuity was <20/200 (6/60) in 103 (96.23%) eyes. However, final BCVA of =20/40 (6/12) was achieved in 18 (16.82%) eyes, while 72 (67.28%) eyes had final BCVA of <20/200 (6/60). Final visual outcome in our study were similar to those in OTS study, except for NLP in category 1 (81% vs. 74%) and =20/40 in category 3 (30% vs. 41%). The OTS model predicted visual survival (LP or better) with a sensitivity of 94.80% and predicted no vision (NLP) with a specificity of 100%. Conclusion: OTS is a reliable tool for assessment of ocular injuries and predicting final visual outcome at the outset. (author)

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

Cloning and molecular analyses of a gibberellin 20-oxidase gene expressed specifically in developing seeds of watermelon.

Science.gov (United States)

Kang, H G; Jun, S H; Kim, J; Kawaide, H; Kamiya, Y; An, G

1999-10-01

To understand the biosynthesis and functional role of gibberellins (GAs) in developing seeds, we isolated Cv20ox, a cDNA clone from watermelon (Citrullus lanatus) that shows significant amino acid homology with GA 20-oxidases. The complementary DNA clone was expressed in Escherichia coli as a fusion protein, which oxidized GA(12) at C-20 to the C(19) compound GA(9), a precursor of bioactive GAs. RNA-blot analysis showed that the Cv20ox gene was expressed specifically in developing seeds. The gene was strongly expressed in the integument tissues, and it was also expressed weakly in inner seed tissues. In parthenocarpic fruits induced by 1-(2-chloro-4-pyridyl)-3-phenylurea treatment, the expression pattern of Cv20ox did not change, indicating that the GA 20-oxidase gene is expressed primarily in the maternal cells of developing seeds. The promoter of Cv20ox was isolated and fused to the beta-glucuronidase (GUS) gene. In a transient expression system, beta-glucuronidase staining was detectable only in the integument tissues of developing watermelon seeds.

A PREDICTABLE MULTI-THREADED MAIN-MEMORY STORAGE MANAGER

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

This paper introduces the design and implementation of a predictable multi-threaded main-memo- ry storage manager (CS20), and emphasizes the database service mediator(DSM), an operation prediction model using exponential averaging. The memory manager, indexing, as well as lock manager in CS20 are also presented briefly. CS20 has been embedded in a mobile telecommunication service system. Practice showed, DSM effectively controls system load and hence improves the real-time characteristics of data accessing.

When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation.

Directory of Open Access Journals (Sweden)

Young Bin Kim

Full Text Available Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016.

When Bitcoin encounters information in an online forum: Using text mining to analyse user opinions and predict value fluctuation.

Science.gov (United States)

Kim, Young Bin; Lee, Jurim; Park, Nuri; Choo, Jaegul; Kim, Jong-Hyun; Kim, Chang Hun

2017-01-01

Bitcoin is an online currency that is used worldwide to make online payments. It has consequently become an investment vehicle in itself and is traded in a way similar to other open currencies. The ability to predict the price fluctuation of Bitcoin would therefore facilitate future investment and payment decisions. In order to predict the price fluctuation of Bitcoin, we analyse the comments posted in the Bitcoin online forum. Unlike most research on Bitcoin-related online forums, which is limited to simple sentiment analysis and does not pay sufficient attention to note-worthy user comments, our approach involved extracting keywords from Bitcoin-related user comments posted on the online forum with the aim of analytically predicting the price and extent of transaction fluctuation of the currency. The effectiveness of the proposed method is validated based on Bitcoin online forum data ranging over a period of 2.8 years from December 2013 to September 2016.

Predictive Engineering Tools for Injection-Molded Long-Carbon-Thermoplastic Composites: Weight and Cost Analyses

Energy Technology Data Exchange (ETDEWEB)

Nguyen, Ba Nghiep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fifield, Leonard S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gandhi, Umesh N. [Toyota Research Inst. North America, Ann Arbor, MI (United States); Mori, Steven [MAGNA Exteriors and Interiors Corporation, Aurora, ON (Canada); Wollan, Eric J. [PlastiComp, Inc., Winona, MN (United States)

2016-08-01

This project proposed to integrate, optimize and validate the fiber orientation and length distribution models previously developed and implemented in the Autodesk Simulation Moldflow Insight (ASMI) package for injection-molded long-carbon-fiber thermoplastic composites into a cohesive prediction capability. The current effort focused on rendering the developed models more robust and efficient for automotive industry part design to enable weight savings and cost reduction. The project goal has been achieved by optimizing the developed models, improving and integrating their implementations in ASMI, and validating them for a complex 3D LCF thermoplastic automotive part (Figure 1). Both PP and PA66 were used as resin matrices. After validating ASMI predictions for fiber orientation and fiber length for this complex part against the corresponding measured data, in collaborations with Toyota and Magna PNNL developed a method using the predictive engineering tool to assess LCF/PA66 complex part design in terms of stiffness performance. Structural three-point bending analyses of the complex part and similar parts in steel were then performed for this purpose, and the team has then demonstrated the use of stiffness-based complex part design assessment to evaluate weight savings relative to the body system target (≥ 35%) set in Table 2 of DE-FOA-0000648 (AOI #1). In addition, starting from the part-to-part analysis, the PE tools enabled an estimated weight reduction for the vehicle body system using 50 wt% LCF/PA66 parts relative to the current steel system. Also, from this analysis an estimate of the manufacturing cost including the material cost for making the equivalent part in steel has been determined and compared to the costs for making the LCF/PA66 part to determine the cost per “saved” pound.

Cumulative risk, cumulative outcome: a 20-year longitudinal study.

Directory of Open Access Journals (Sweden)

Leslie Atkinson

Full Text Available Cumulative risk (CR models provide some of the most robust findings in the developmental literature, predicting numerous and varied outcomes. Typically, however, these outcomes are predicted one at a time, across different samples, using concurrent designs, longitudinal designs of short duration, or retrospective designs. We predicted that a single CR index, applied within a single sample, would prospectively predict diverse outcomes, i.e., depression, intelligence, school dropout, arrest, smoking, and physical disease from childhood to adulthood. Further, we predicted that number of risk factors would predict number of adverse outcomes (cumulative outcome; CO. We also predicted that early CR (assessed at age 5/6 explains variance in CO above and beyond that explained by subsequent risk (assessed at ages 12/13 and 19/20. The sample consisted of 284 individuals, 48% of whom were diagnosed with a speech/language disorder. Cumulative risk, assessed at 5/6-, 12/13-, and 19/20-years-old, predicted aforementioned outcomes at age 25/26 in every instance. Furthermore, number of risk factors was positively associated with number of negative outcomes. Finally, early risk accounted for variance beyond that explained by later risk in the prediction of CO. We discuss these findings in terms of five criteria posed by these data, positing a "mediated net of adversity" model, suggesting that CR may increase some central integrative factor, simultaneously augmenting risk across cognitive, quality of life, psychiatric and physical health outcomes.

Climate Prediction Center (CPC) US daily temperature analyses

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. daily temperature analyses are maps depicting various temperature quantities utilizing daily maximum and minimum temperature data across the US. Maps are...

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

Interactions between risk factors in the prediction of onset of eating disorders: Exploratory hypothesis generating analyses.

Science.gov (United States)

Stice, Eric; Desjardins, Christopher D

2018-06-01

Because no study has tested for interactions between risk factors in the prediction of future onset of each eating disorder, this exploratory study addressed this lacuna to generate hypotheses to be tested in future confirmatory studies. Data from three prevention trials that targeted young women at high risk for eating disorders due to body dissatisfaction (N = 1271; M age 18.5, SD 4.2) and collected diagnostic interview data over 3-year follow-up were combined to permit sufficient power to predict onset of anorexia nervosa (AN), bulimia nervosa (BN), binge eating disorder (BED), and purging disorder (PD) using classification tree analyses, an analytic technique uniquely suited to detecting interactions. Low BMI was the most potent predictor of AN onset, and body dissatisfaction amplified this relation. Overeating was the most potent predictor of BN onset, and positive expectancies for thinness and body dissatisfaction amplified this relation. Body dissatisfaction was the most potent predictor of BED onset, and overeating, low dieting, and thin-ideal internalization amplified this relation. Dieting was the most potent predictor of PD onset, and negative affect and positive expectancies for thinness amplified this relation. Results provided evidence of amplifying interactions between risk factors suggestive of cumulative risk processes that were distinct for each disorder; future confirmatory studies should test the interactive hypotheses generated by these analyses. If hypotheses are confirmed, results may allow interventionists to target ultra high-risk subpopulations with more intensive prevention programs that are uniquely tailored for each eating disorder, potentially improving the yield of prevention efforts. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

Validation of the Web-Based IBTR! 2.0 Nomogram to Predict for Ipsilateral Breast Tumor Recurrence After Breast-Conserving Therapy.

Science.gov (United States)

Kindts, Isabelle; Laenen, Annouschka; Peeters, Stephanie; Janssen, Hilde; Depuydt, Tom; Nevelsteen, Ines; Van Limbergen, Erik; Weltens, Caroline

2016-08-01

To evaluate the IBTR! 2.0 nomogram, which predicts 10-year ipsilateral breast tumor recurrence (IBTR) after breast-conserving therapy with and without radiation therapy for breast cancer, by using a large, external, and independent cancer center database. We retrospectively identified 1898 breast cancer cases, treated with breast-conserving therapy and radiation therapy at the University Hospital Leuven from 2000 to 2007, with requisite data for the nomogram variables. Clinicopathologic factors were assessed. Two definitions of IBTR were considered where simultaneous regional or distant recurrence were either censored (conform IBTR! 2.0) or included as event. Validity of the prediction algorithm was tested in terms of discrimination and calibration. Discrimination was assessed by the concordance probability estimate and Harrell's concordance index. The mean predicted and observed 10-year estimates were compared for the entire cohort and for 4 risk groups predefined by nomogram-predicted IBTR risks, and a calibration plot was drawn. Median follow-up was 10.9 years. The 10-year IBTR rates were 1.3% and 2.1%, according to the 2 definitions of IBTR. The validation cohort differed from the development cohort with respect to the administration of hormonal therapy, surgical section margins, lymphovascular invasion, and tumor size. In univariable analysis, younger age (P=.002) and a positive nodal status (P=.048) were significantly associated with IBTR, with a trend for the omission of hormonal therapy (P=.061). The concordance probability estimate and concordance index varied between 0.57 and 0.67 for the 2 definitions of IBTR. In all 4 risk groups the model overestimated the IBTR risk. In particular, between the lowest-risk groups a limited differentiation was suggested by the calibration plot. The IBTR! 2.0 predictive model for IBTR in breast cancer patients shows substandard discriminative ability, with an overestimation of the risk in all subgroups. Copyright �

Validation of the Web-Based IBTR! 2.0 Nomogram to Predict for Ipsilateral Breast Tumor Recurrence After Breast-Conserving Therapy

International Nuclear Information System (INIS)

Kindts, Isabelle; Laenen, Annouschka; Peeters, Stephanie; Janssen, Hilde; Depuydt, Tom; Nevelsteen, Ines; Van Limbergen, Erik; Weltens, Caroline

2016-01-01

Purpose: To evaluate the IBTR! 2.0 nomogram, which predicts 10-year ipsilateral breast tumor recurrence (IBTR) after breast-conserving therapy with and without radiation therapy for breast cancer, by using a large, external, and independent cancer center database. Methods and Materials: We retrospectively identified 1898 breast cancer cases, treated with breast-conserving therapy and radiation therapy at the University Hospital Leuven from 2000 to 2007, with requisite data for the nomogram variables. Clinicopathologic factors were assessed. Two definitions of IBTR were considered where simultaneous regional or distant recurrence were either censored (conform IBTR! 2.0) or included as event. Validity of the prediction algorithm was tested in terms of discrimination and calibration. Discrimination was assessed by the concordance probability estimate and Harrell's concordance index. The mean predicted and observed 10-year estimates were compared for the entire cohort and for 4 risk groups predefined by nomogram-predicted IBTR risks, and a calibration plot was drawn. Results: Median follow-up was 10.9 years. The 10-year IBTR rates were 1.3% and 2.1%, according to the 2 definitions of IBTR. The validation cohort differed from the development cohort with respect to the administration of hormonal therapy, surgical section margins, lymphovascular invasion, and tumor size. In univariable analysis, younger age (P=.002) and a positive nodal status (P=.048) were significantly associated with IBTR, with a trend for the omission of hormonal therapy (P=.061). The concordance probability estimate and concordance index varied between 0.57 and 0.67 for the 2 definitions of IBTR. In all 4 risk groups the model overestimated the IBTR risk. In particular, between the lowest-risk groups a limited differentiation was suggested by the calibration plot. Conclusions: The IBTR! 2.0 predictive model for IBTR in breast cancer patients shows substandard discriminative ability, with an

Validation of the Web-Based IBTR! 2.0 Nomogram to Predict for Ipsilateral Breast Tumor Recurrence After Breast-Conserving Therapy

Energy Technology Data Exchange (ETDEWEB)

Kindts, Isabelle, E-mail: Isabelle.kindts@uzleuven.be [Department of Oncology, KU Leuven - University of Leuven, Leuven (Belgium); Department of Radiation Oncology, University Hospitals Leuven, Leuven (Belgium); Laenen, Annouschka [Leuven Biostatistics and Statistical Bioinformatics Center (L-Biostat), KU Leuven - University of Leuven, Leuven (Belgium); Peeters, Stephanie; Janssen, Hilde; Depuydt, Tom [Department of Oncology, KU Leuven - University of Leuven, Leuven (Belgium); Department of Radiation Oncology, University Hospitals Leuven, Leuven (Belgium); Nevelsteen, Ines [Department of Oncology, KU Leuven - University of Leuven, Leuven (Belgium); Department of Surgical Oncology, University Hospitals Leuven, Leuven (Belgium); Van Limbergen, Erik; Weltens, Caroline [Department of Oncology, KU Leuven - University of Leuven, Leuven (Belgium); Department of Radiation Oncology, University Hospitals Leuven, Leuven (Belgium)

2016-08-01

Purpose: To evaluate the IBTR! 2.0 nomogram, which predicts 10-year ipsilateral breast tumor recurrence (IBTR) after breast-conserving therapy with and without radiation therapy for breast cancer, by using a large, external, and independent cancer center database. Methods and Materials: We retrospectively identified 1898 breast cancer cases, treated with breast-conserving therapy and radiation therapy at the University Hospital Leuven from 2000 to 2007, with requisite data for the nomogram variables. Clinicopathologic factors were assessed. Two definitions of IBTR were considered where simultaneous regional or distant recurrence were either censored (conform IBTR! 2.0) or included as event. Validity of the prediction algorithm was tested in terms of discrimination and calibration. Discrimination was assessed by the concordance probability estimate and Harrell's concordance index. The mean predicted and observed 10-year estimates were compared for the entire cohort and for 4 risk groups predefined by nomogram-predicted IBTR risks, and a calibration plot was drawn. Results: Median follow-up was 10.9 years. The 10-year IBTR rates were 1.3% and 2.1%, according to the 2 definitions of IBTR. The validation cohort differed from the development cohort with respect to the administration of hormonal therapy, surgical section margins, lymphovascular invasion, and tumor size. In univariable analysis, younger age (P=.002) and a positive nodal status (P=.048) were significantly associated with IBTR, with a trend for the omission of hormonal therapy (P=.061). The concordance probability estimate and concordance index varied between 0.57 and 0.67 for the 2 definitions of IBTR. In all 4 risk groups the model overestimated the IBTR risk. In particular, between the lowest-risk groups a limited differentiation was suggested by the calibration plot. Conclusions: The IBTR! 2.0 predictive model for IBTR in breast cancer patients shows substandard discriminative ability, with an

Tickled to death: analysing public perceptions of 'cute' videos of threatened species (slow lorises - Nycticebus spp.) on Web 2.0 sites.

Science.gov (United States)

Anne-Isola Nekaris, K; Nekaris, By K Anne-Isola; Campbell, Nicola; Coggins, Tim G; Rode, E Johanna; Nijman, Vincent

2013-01-01

The internet is gaining importance in global wildlife trade and changing perceptions of threatened species. There is little data available to examine the impact that popular Web 2.0 sites play on public perceptions of threatened species. YouTube videos portraying wildlife allow us to quantify these perceptions. Focussing on a group of threatened and globally protected primates, slow lorises, we quantify public attitudes towards wildlife conservation by analysing 12,411 comments and associated data posted on a viral YouTube video 'tickling slow loris' over a 33-months period. In the initial months a quarter of commentators indicated wanting a loris as a pet, but as facts about their conservation and ecology became more prevalent this dropped significantly. Endorsements, where people were directed to the site by celebrities, resulted mostly in numerous neutral responses with few links to conservation or awareness. Two conservation-related events, linked to Wikipedia and the airing of a television documentary, led to an increase in awareness, and ultimately to the removal of the analysed video. Slow loris videos that have gone viral have introduced these primates to a large cross-section of society that would not normally come into contact with them. Analyses of webometric data posted on the internet allow us quickly to gauge societal sentiments. We showed a clear temporal change in some views expressed but without an apparent increase in knowledge about the conservation plight of the species, or the illegal nature of slow loris trade. Celebrity endorsement of videos showing protected wildlife increases visits to such sites, but does not educate about conservation issues. The strong desire of commentators to express their want for one as a pet demonstrates the need for Web 2.0 sites to provide a mechanism via which illegal animal material can be identified and policed.

Tickled to death: analysing public perceptions of 'cute' videos of threatened species (slow lorises - Nycticebus spp. on Web 2.0 sites.

Directory of Open Access Journals (Sweden)

K Anne-Isola Nekaris

Full Text Available BACKGROUND: The internet is gaining importance in global wildlife trade and changing perceptions of threatened species. There is little data available to examine the impact that popular Web 2.0 sites play on public perceptions of threatened species. YouTube videos portraying wildlife allow us to quantify these perceptions. METHODOLOGY/PRINCIPAL FINDINGS: Focussing on a group of threatened and globally protected primates, slow lorises, we quantify public attitudes towards wildlife conservation by analysing 12,411 comments and associated data posted on a viral YouTube video 'tickling slow loris' over a 33-months period. In the initial months a quarter of commentators indicated wanting a loris as a pet, but as facts about their conservation and ecology became more prevalent this dropped significantly. Endorsements, where people were directed to the site by celebrities, resulted mostly in numerous neutral responses with few links to conservation or awareness. Two conservation-related events, linked to Wikipedia and the airing of a television documentary, led to an increase in awareness, and ultimately to the removal of the analysed video. CONCLUSIONS/SIGNIFICANCE: Slow loris videos that have gone viral have introduced these primates to a large cross-section of society that would not normally come into contact with them. Analyses of webometric data posted on the internet allow us quickly to gauge societal sentiments. We showed a clear temporal change in some views expressed but without an apparent increase in knowledge about the conservation plight of the species, or the illegal nature of slow loris trade. Celebrity endorsement of videos showing protected wildlife increases visits to such sites, but does not educate about conservation issues. The strong desire of commentators to express their want for one as a pet demonstrates the need for Web 2.0 sites to provide a mechanism via which illegal animal material can be identified and policed.

Potential Predictability of the Sea-Surface Temperature Forced Equatorial East Africa Short Rains Interannual Variability in the 20th Century

Science.gov (United States)

Bahaga, T. K.; Gizaw, G.; Kucharski, F.; Diro, G. T.

2014-12-01

In this article, the predictability of the 20th century sea-surface temperature (SST) forced East African short rains variability is analyzed using observational data and ensembles of long atmospheric general circulation model (AGCM) simulations. To our knowledge, such an analysis for the whole 20th century using a series of AGCM ensemble simulations is carried out here for the first time. The physical mechanisms that govern the influence of SST on East African short rains in the model are also investigated. It is found that there is substantial skill in reproducing the East African short rains variability, given that the SSTs are known. Consistent with previous recent studies, it is found that the Indian Ocean and in particular the western pole of the Indian Ocean dipole (IOD) play a dominant role for the prediction skill, whereas SSTs outside the Indian Ocean play a minor role. The physical mechanism for the influence of the western Indian Ocean on East African rainfall in the model is consistent with previous findings and consists of a gill-type response to a warm (cold) anomaly that induces a westerly(easterly) low-level flow anomaly over equatorial Africa and leads to moisture flux convergence (divergence) over East Africa. On the other hand, a positive El Nino-Southern Oscillation (ENSO) anomaly leads to a spatially non-coherent reducing effect over parts of East Africa, but the relationship is not strong enough to provide any predictive skill in our model. The East African short rains prediction skill is also analyzed within a model-derived potential predictability framework and it is shown that the actual prediction skill is broadly consistent with the model potential prediction skill. Low-frequency variations of the prediction skill are mostly related to SSTs outside the Indian Ocean region and are likely due to an increased interference of ENSO with the Indian Ocean influence on East African short rains after the mid-1970s climate shift.

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

Cloning and Molecular Analyses of a Gibberellin 20-Oxidase Gene Expressed Specifically in Developing Seeds of Watermelon1

Science.gov (United States)

Kang, Hong-Gyu; Jun, Sung-Hoon; Kim, Junyul; Kawaide, Hiroshi; Kamiya, Yuji; An, Gynheung

1999-01-01

To understand the biosynthesis and functional role of gibberellins (GAs) in developing seeds, we isolated Cv20ox, a cDNA clone from watermelon (Citrullus lanatus) that shows significant amino acid homology with GA 20-oxidases. The complementary DNA clone was expressed in Escherichia coli as a fusion protein, which oxidized GA12 at C-20 to the C19 compound GA9, a precursor of bioactive GAs. RNA-blot analysis showed that the Cv20ox gene was expressed specifically in developing seeds. The gene was strongly expressed in the integument tissues, and it was also expressed weakly in inner seed tissues. In parthenocarpic fruits induced by 1-(2-chloro-4-pyridyl)-3-phenylurea treatment, the expression pattern of Cv20ox did not change, indicating that the GA 20-oxidase gene is expressed primarily in the maternal cells of developing seeds. The promoter of Cv20ox was isolated and fused to the β-glucuronidase (GUS) gene. In a transient expression system, β-glucuronidase staining was detectable only in the integument tissues of developing watermelon seeds. PMID:10517828

Weight Suppression Predicts Bulimic Symptoms at 20-year Follow-up: The Mediating Role of Drive for Thinness

Science.gov (United States)

Bodell, Lindsay P.; Brown, Tiffany A.; Keel, Pamela K.

2016-01-01

Weight suppression predicts the onset and maintenance of bulimic syndromes. Despite this finding, no study has examined psychological mechanisms contributing to these associations using a longitudinal design. Given societal pressures to be thin and an actual history of higher weight, it is possible that greater weight suppression contributes to increased fear of gaining weight and preoccupation with being thin, which increase vulnerability to eating disorders. The present study investigated whether greater drive for thinness mediates associations between weight suppression and bulimic symptoms over long-term follow-up. Participants were women (n = 1190) and men (n = 509) who completed self-report surveys in college and 10- and 20- years later. Higher weight suppression at baseline predicted higher bulimic symptoms at 20-year follow-up (p symptoms, body mass index, and drive for thinness. Increased drive for thinness at 10-year follow-up mediated this effect. Findings highlight the long-lasting effect of weight suppression on bulimic symptoms and suggest that preoccupation with thinness may help maintain this association. Future studies would benefit from incorporating other hypothesized consequences of weight suppression, including biological factors, into risk models. PMID:27808544

Adolescent oligomenorrhea (age 14-19) tracks into the third decade of life (age 20-28) and predicts increased cardiovascular risk factors and metabolic syndrome.

Science.gov (United States)

Glueck, Charles J; Woo, Jessica G; Khoury, Philip R; Morrison, John A; Daniels, Stephen R; Wang, Ping

2015-04-01

Assess whether adolescent oligomenorrhea (age 14-19) tracks into young adulthood (age 20-28) and predicts increased cardiometabolic risk factors, metabolic syndrome (MetS), and impaired fasting glucose-type II diabetes mellitus (IFG+T2DM). Prospective study of menstrual cyclicity and its metabolic effects in 865 black and white schoolgirls from age 9 to 19, and 605 of these 865 girls from age 20 to 28. Patterns of menstrual delays (oligomenorrhea) during ages 14-19 and ages 20-28 were closely related (ppolycystic ovary syndrome (PCOS, p=.049) predicted ages 20-28 menses delay. Menses delays during ages 14-19 and 20-28, and, their interaction product were correlated with IFG+T2DM and MetS at ages 20-28. Waist circumference (ages 20-28, prisk factor for future development of young adult IFG+T2DM, MetS, oligomenorrhea, and polycystic ovary syndrome. Copyright © 2015 Elsevier Inc. All rights reserved.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses.

Science.gov (United States)

Brown, Jason L; Bennett, Joseph R; French, Connor M

2017-01-01

SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.

A case study of GWE satellite data impact on GLA assimilation analyses of two ocean cyclones

Science.gov (United States)

Gallimore, R. G.; Johnson, D. R.

1986-01-01

The effects of the Global Weather Experiment (GWE) data obtained on January 18-20, 1979 on Goddard Laboratory for Atmospheres assimilation analyses of simultaneous cyclones in the western Pacific and Atlantic oceans are examined. The ability of satellite data within assimilation models to determine the baroclinic structures of developing extratropical cyclones is evaluated. The impact of the satellite data on the amplitude and phase of the temperature structure within the storm domain, potential energy, and baroclinic growth rate is studied. The GWE data are compared with Data Systems Test results. It is noted that it is necessary to characterize satellite effects on the baroclinic structure of cyclone waves which degrade numerical weather predictions of cyclogenesis.

Exploring Factors that Predict Preservice Teachers' Intentions to Use Web 2.0 Technologies Using Decomposed Theory of Planned Behavior

Science.gov (United States)

Sadaf, Ayesha; Newby, Timothy J.; Ertmer, Peggy A.

2013-01-01

This study investigated factors that predict preservice teachers' intentions to use Web 2.0 technologies in their future classrooms. The researchers used a mixed-methods research design and collected qualitative interview data (n = 7) to triangulate quantitative survey data (n = 286). Results indicate that positive attitudes and perceptions of…

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.

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.

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.

High neuroticism at age 20 predicts history of mental disorders and low self-esteem at age 35.

Science.gov (United States)

Lönnqvist, Jan-Erik; Verkasalo, Markku; Mäkinen, Seppo; Henriksson, Markus

2009-07-01

The authors assessed whether neuroticism in emerging adulthood predicts mental disorders and self-esteem in early adulthood after controlling for possible confounding variables. A sample of 69 male military conscripts was initially assessed at age 20 and again as civilians at age 35. The initial assessment included a psychiatric interview, objective indicators of conscript competence, an intellectual performance test, and neuroticism questionnaires. The follow-up assessment included a Structured Clinical Interview for DSM-IV (SCID; First, Spitzer, Gibbon, & Williams, 1996) and the Rosenberg Self-Esteem Scale (Rosenberg, 1965). Neuroticism predicted future mental disorders and low self-esteem beyond more objective indicators of adjustment. The results support the use of neuroticism as a predictor of future mental disorders, even over periods of time when personality is subject to change.

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

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.

SDMtoolbox 2.0: the next generation Python-based GIS toolkit for landscape genetic, biogeographic and species distribution model analyses

Directory of Open Access Journals (Sweden)

Jason L. Brown

2017-12-01

Full Text Available SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism, generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.

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

A model for predicting lung cancer response to therapy

International Nuclear Information System (INIS)

Seibert, Rebecca M.; Ramsey, Chester R.; Hines, J. Wesley; Kupelian, Patrick A.; Langen, Katja M.; Meeks, Sanford L.; Scaperoth, Daniel D.

2007-01-01

Purpose: Volumetric computed tomography (CT) images acquired by image-guided radiation therapy (IGRT) systems can be used to measure tumor response over the course of treatment. Predictive adaptive therapy is a novel treatment technique that uses volumetric IGRT data to actively predict the future tumor response to therapy during the first few weeks of IGRT treatment. The goal of this study was to develop and test a model for predicting lung tumor response during IGRT treatment using serial megavoltage CT (MVCT). Methods and Materials: Tumor responses were measured for 20 lung cancer lesions in 17 patients that were imaged and treated with helical tomotherapy with doses ranging from 2.0 to 2.5 Gy per fraction. Five patients were treated with concurrent chemotherapy, and 1 patient was treated with neoadjuvant chemotherapy. Tumor response to treatment was retrospectively measured by contouring 480 serial MVCT images acquired before treatment. A nonparametric, memory-based locally weight regression (LWR) model was developed for predicting tumor response using the retrospective tumor response data. This model predicts future tumor volumes and the associated confidence intervals based on limited observations during the first 2 weeks of treatment. The predictive accuracy of the model was tested using a leave-one-out cross-validation technique with the measured tumor responses. Results: The predictive algorithm was used to compare predicted verse-measured tumor volume response for all 20 lesions. The average error for the predictions of the final tumor volume was 12%, with the true volumes always bounded by the 95% confidence interval. The greatest model uncertainty occurred near the middle of the course of treatment, in which the tumor response relationships were more complex, the model has less information, and the predictors were more varied. The optimal days for measuring the tumor response on the MVCT images were on elapsed Days 1, 2, 5, 9, 11, 12, 17, and 18 during

Changes in environmental tobacco smoke (ETS) exposure over a 20-year period: cross-sectional and longitudinal analyses

Science.gov (United States)

Jefferis, Barbara J; Thomson, Andrew G; Lennon, Lucy T; Feyerabend, Colin; Doig, Mira; McMeekin, Laura; Wannamethee, S Goya; Cook, Derek G; Whincup, Peter H

2009-01-01

Aims To examine long-term changes in environmental tobacco smoke (ETS) exposure in British men between 1978 and 2000, using serum cotinine. Design Prospective cohort: British Regional Heart Study. Setting General practices in 24 towns in England, Wales and Scotland. Participants Non-smoking men: 2125 studied at baseline [questionnaire (Q1): 1978–80, aged 40–59 years], 3046 studied 20 years later (Q20: 1998–2000, aged 60–79 years) and 1208 studied at both times. Non-smokers were men reporting no current smoking with cotinine < 15 ng/ml at Q1 and/or Q20. Measurements Serum cotinine to assess ETS exposure. Findings In cross-sectional analysis, geometric mean cotinine level declined from 1.36 ng/ml [95% confidence interval (CI): 1.31, 1.42] at Q1 to 0.19 ng/ml (95% CI: 0.18, 0.19) at Q20. The prevalence of cotinine levels ≤ 0.7 ng/ml [associated with low coronary heart disease (CHD) risk] rose from 27.1% at Q1 to 83.3% at Q20. Manual social class and northern region of residence were associated with higher mean cotinine levels both at Q1 and Q20; older age was associated with lower cotinine level at Q20 only. Among 1208 persistent non-smokers, cotinine fell by 1.47 ng/ml (95% CI: 1.37, 1.57), 86% decline. Absolute falls in cotinine were greater in manual occupational groups, in the Midlands and Scotland compared to southern England, although percentage decline was very similar across groups. Conclusions A marked decline in ETS exposure occurred in Britain between 1978 and 2000, which is likely to have reduced ETS-related disease risks appreciably before the introduction of legislation banning smoking in public places. PMID:19207361

Analyses of MMP20 Missense Mutations in Two Families with Hypomaturation Amelogenesis Imperfecta.

Science.gov (United States)

Kim, Youn Jung; Kang, Jenny; Seymen, Figen; Koruyucu, Mine; Gencay, Koray; Shin, Teo Jeon; Hyun, Hong-Keun; Lee, Zang Hee; Hu, Jan C-C; Simmer, James P; Kim, Jung-Wook

2017-01-01

Amelogenesis imperfecta is a group of rare inherited disorders that affect tooth enamel formation, quantitatively and/or qualitatively. The aim of this study was to identify the genetic etiologies of two families presenting with hypomaturation amelogenesis imperfecta. DNA was isolated from peripheral blood samples obtained from participating family members. Whole exome sequencing was performed using DNA samples from the two probands. Sequencing data was aligned to the NCBI human reference genome (NCBI build 37.2, hg19) and sequence variations were annotated with the dbSNP build 138. Mutations in MMP20 were identified in both probands. A homozygous missense mutation (c.678T>A; p.His226Gln) was identified in the consanguineous Family 1. Compound heterozygous MMP20 mutations (c.540T>A, p.Tyr180 * and c.389C>T, p.Thr130Ile) were identified in the non-consanguineous Family 2. Affected persons in Family 1 showed hypomaturation AI with dark brown discoloration, which is similar to the clinical phenotype in a previous report with the same mutation. However, the dentition of the Family 2 proband exhibited slight yellowish discoloration with reduced transparency. Functional analysis showed that the p.Thr130Ile mutant protein had reduced activity of MMP20, while there was no functional MMP20 in the Family 1 proband. These results expand the mutational spectrum of the MMP20 and broaden our understanding of genotype-phenotype correlations in amelogenesis imperfecta.

Analyses of MMP20 Missense Mutations in Two Families with Hypomaturation Amelogenesis Imperfecta

Directory of Open Access Journals (Sweden)

Jung-Wook Kim

2017-04-01

Full Text Available Amelogenesis imperfecta is a group of rare inherited disorders that affect tooth enamel formation, quantitatively and/or qualitatively. The aim of this study was to identify the genetic etiologies of two families presenting with hypomaturation amelogenesis imperfecta. DNA was isolated from peripheral blood samples obtained from participating family members. Whole exome sequencing was performed using DNA samples from the two probands. Sequencing data was aligned to the NCBI human reference genome (NCBI build 37.2, hg19 and sequence variations were annotated with the dbSNP build 138. Mutations in MMP20 were identified in both probands. A homozygous missense mutation (c.678T>A; p.His226Gln was identified in the consanguineous Family 1. Compound heterozygous MMP20 mutations (c.540T>A, p.Tyr180* and c.389C>T, p.Thr130Ile were identified in the non-consanguineous Family 2. Affected persons in Family 1 showed hypomaturation AI with dark brown discoloration, which is similar to the clinical phenotype in a previous report with the same mutation. However, the dentition of the Family 2 proband exhibited slight yellowish discoloration with reduced transparency. Functional analysis showed that the p.Thr130Ile mutant protein had reduced activity of MMP20, while there was no functional MMP20 in the Family 1 proband. These results expand the mutational spectrum of the MMP20 and broaden our understanding of genotype-phenotype correlations in amelogenesis imperfecta.

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.

Tickled to Death: Analysing Public Perceptions of ‘Cute’ Videos of Threatened Species (Slow Lorises – Nycticebus spp.) on Web 2.0 Sites

Science.gov (United States)

Nekaris, By K. Anne-Isola; Campbell, Nicola; Coggins, Tim G.; Rode, E. Johanna; Nijman, Vincent

2013-01-01

Background The internet is gaining importance in global wildlife trade and changing perceptions of threatened species. There is little data available to examine the impact that popular Web 2.0 sites play on public perceptions of threatened species. YouTube videos portraying wildlife allow us to quantify these perceptions. Methodology/Principal Findings Focussing on a group of threatened and globally protected primates, slow lorises, we quantify public attitudes towards wildlife conservation by analysing 12,411 comments and associated data posted on a viral YouTube video ‘tickling slow loris’ over a 33-months period. In the initial months a quarter of commentators indicated wanting a loris as a pet, but as facts about their conservation and ecology became more prevalent this dropped significantly. Endorsements, where people were directed to the site by celebrities, resulted mostly in numerous neutral responses with few links to conservation or awareness. Two conservation-related events, linked to Wikipedia and the airing of a television documentary, led to an increase in awareness, and ultimately to the removal of the analysed video. Conclusions/Significance Slow loris videos that have gone viral have introduced these primates to a large cross-section of society that would not normally come into contact with them. Analyses of webometric data posted on the internet allow us quickly to gauge societal sentiments. We showed a clear temporal change in some views expressed but without an apparent increase in knowledge about the conservation plight of the species, or the illegal nature of slow loris trade. Celebrity endorsement of videos showing protected wildlife increases visits to such sites, but does not educate about conservation issues. The strong desire of commentators to express their want for one as a pet demonstrates the need for Web 2.0 sites to provide a mechanism via which illegal animal material can be identified and policed. PMID:23894432

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.

What does a worm want with 20,000 genes?

OpenAIRE

Hodgkin, Jonathan

2001-01-01

The number of genes predicted for the Caenorhabditis elegans genome is remarkably high: approximately 20,000, if both protein-coding and RNA-coding genes are counted. This article discusses possible explanations for such a high value.

Long-term fertilization alters chemically-separated soil organic carbon pools: Based on stable C isotope analyses

Science.gov (United States)

Dou, Xiaolin; He, Ping; Cheng, Xiaoli; Zhou, Wei

2016-01-01

Quantification of dynamics of soil organic carbon (SOC) pools under the influence of long-term fertilization is essential for predicting carbon (C) sequestration. We combined soil chemical fractionation with stable C isotope analyses to investigate the C dynamics of the various SOC pools after 25 years of fertilization. Five types of soil samples (0-20, 20-40 cm) including the initial level (CK) and four fertilization treatments (inorganic nitrogen fertilizer, IN; balanced inorganic fertilizer, NPK; inorganic fertilizer plus farmyard manure, MNPK; inorganic fertilizer plus corn straw residue, SNPK) were separated into recalcitrant and labile fractions, and the fractions were analysed for C content, C:N ratios, δ13C values, soil C and N recalcitrance indexes (RIC and RIN). Chemical fractionation showed long-term MNPK fertilization strongly increased the SOC storage in both soil layers (0-20 cm = 1492.4 gC m2 and 20-40 cm = 1770.6 gC m2) because of enhanced recalcitrant C (RC) and labile C (LC). The 25 years of inorganic fertilizer treatment did not increase the SOC storage mainly because of the offsetting effects of enhanced RC and decreased LC, whereas no clear SOC increases under the SNPK fertilization resulted from the fast decay rates of soil C.

Designing Geometry 2.0 learning environments: a preliminary study with primary school students

Science.gov (United States)

Joglar Prieto, Nuria; María Sordo Juanena, José; Star, Jon R.

2014-04-01

The information and communication technologies of Web 2.0 are arriving in our schools, allowing the design and implementation of new learning environments with great educational potential. This article proposes a pedagogical model based on a new geometry technology-integrated learning environment, called Geometry 2.0, which was tested with 39 sixth grade students from a public school in Madrid (Spain). The main goals of the study presented here were to describe an optimal role for the mathematics teacher within Geometry 2.0, and to analyse how dynamic mathematics and communication might affect young students' learning of basic figural concepts in a real setting. The analyses offered in this article illustrate how our Geometry 2.0 model facilitates deeply mathematical tasks which encourage students' exploration, cooperation and communication, improving their learning while fostering geometrical meanings.

PC-PVT 2.0: An updated platform for psychomotor vigilance task testing, analysis, prediction, and visualization.

Science.gov (United States)

Reifman, Jaques; Kumar, Kamal; Khitrov, Maxim Y; Liu, Jianbo; Ramakrishnan, Sridhar

2018-07-01

The psychomotor vigilance task (PVT) has been widely used to assess the effects of sleep deprivation on human neurobehavioral performance. To facilitate research in this field, we previously developed the PC-PVT, a freely available software system analogous to the "gold-standard" PVT-192 that, in addition to allowing for simple visual reaction time (RT) tests, also allows for near real-time PVT analysis, prediction, and visualization in a personal computer (PC). Here we present the PC-PVT 2.0 for Windows 10 operating system, which has the capability to couple PVT tests of a study protocol with the study's sleep/wake and caffeine schedules, and make real-time individualized predictions of PVT performance for such schedules. We characterized the accuracy and precision of the software in measuring RT, using 44 distinct combinations of PC hardware system configurations. We found that 15 system configurations measured RTs with an average delay of less than 10 ms, an error comparable to that of the PVT-192. To achieve such small delays, the system configuration should always use a gaming mouse as the means to respond to visual stimuli. We recommend using a discrete graphical processing unit for desktop PCs and an external monitor for laptop PCs. This update integrates a study's sleep/wake and caffeine schedules with the testing software, facilitating testing and outcome visualization, and provides near-real-time individualized PVT predictions for any sleep-loss condition considering caffeine effects. The software, with its enhanced PVT analysis, visualization, and prediction capabilities, can be freely downloaded from https://pcpvt.bhsai.org. Published by Elsevier B.V.

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.

Deflection type energy analyser for energetic electron beams in a beam-plasma system

International Nuclear Information System (INIS)

Michel, J.A.; Hogge, J.P.

1988-11-01

An energy analyser for the study of electron beam distribution functions in unmagnetized plasmas is described. This analyser is designed to avoid large electric fields which are created in multi-grid analysers and to measure directly the beam distribution function without differentiation. As an example of an application we present results on the propagation of an energetic beam (E b : 2.0 keV) in a plasma (n o : 1.10 10 cm -3 , T e : 1.4 eV) (author) 7 figs., 10 refs

RELAP5 thermal-hydraulic analyses of overcooling sequences in a pressurized water reactor

International Nuclear Information System (INIS)

Bolander, M.A.; Fletcher, C.D.; Davis, C.B.; Kullberg, C.M.; Stitt, B.D.; Waterman, M.E.; Burtt, J.D.

1984-01-01

In support of the Pressurized Thermal Shock Integration Study, sponsored by the United States Nuclear Regulatory Commission, the Idaho National Engineering Laboratory has performed analyses of overcooling transients using the RELAP5/MOD1.6 and MOD2.0 computer codes. These analyses were performed for the H.B. Robinson Unit 2 pressurized water reactor, which is a Westinghouse 3-loop design plant. Results of the RELAP5 analyses are presented. The capabilities of the RELAP5 computer code as a tool for analyzing integral plant transients requiring a detailed plant model, including complex trip logic and major control systems, are examined

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.

NetMHCpan, a method for MHC class I binding prediction beyond humans

DEFF Research Database (Denmark)

Hoof, Ilka; Peters, B; Sidney, J

2009-01-01

molecules. We show that the NetMHCpan-2.0 method can accurately predict binding to uncharacterized HLA molecules, including HLA-C and HLA-G. Moreover, NetMHCpan-2.0 is demonstrated to accurately predict peptide binding to chimpanzee and macaque MHC class I molecules. The power of NetMHCpan-2.0 to guide...

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

Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

DEFF Research Database (Denmark)

Vicca, S.; Bahn, M.; Estiarte, M.

2014-01-01

to fluctuations in soil temperature and soil water content can be used to predict SCE under altered rainfall patterns. Of the 58 experiments for which we gathered SCE data, 20 were discarded because either too few data were available or inconsistencies precluded their incorporation in the analyses. The 38...... remaining experiments were used to test the hypothesis that a model parameterized with data from the control plots (using soil temperature and water content as predictor variables) could adequately predict SCE measured in the manipulated treatment. Only for 7 of these 38 experiments was this hypothesis...... strongly on establishing response functions across a broader range of precipitation regimes and soil moisture conditions. Such experiments should make accurate measurements of water availability, should conduct high-frequency SCE measurements, and should consider both instantaneous responses...

A positive relationship between spring temperature and productivity in 20 songbird species in the boreal zone.

Science.gov (United States)

Meller, Kalle; Piha, Markus; Vähätalo, Anssi V; Lehikoinen, Aleksi

2018-03-01

Anthropogenic climate warming has already affected the population dynamics of numerous species and is predicted to do so also in the future. To predict the effects of climate change, it is important to know whether productivity is linked to temperature, and whether species' traits affect responses to climate change. To address these objectives, we analysed monitoring data from the Finnish constant effort site ringing scheme collected in 1987-2013 for 20 common songbird species together with climatic data. Warm spring temperature had a positive linear relationship with productivity across the community of 20 species independent of species' traits (realized thermal niche or migration behaviour), suggesting that even the warmest spring temperatures remained below the thermal optimum for reproduction, possibly due to our boreal study area being closer to the cold edge of all study species' distributions. The result also suggests a lack of mismatch between the timing of breeding and peak availability of invertebrate food of the study species. Productivity was positively related to annual growth rates in long-distance migrants, but not in short-distance migrants. Across the 27-year study period, temporal trends in productivity were mostly absent. The population sizes of species with colder thermal niches had decreasing trends, which were not related to temperature responses or temporal trends in productivity. The positive connection between spring temperature and productivity suggests that climate warming has potential to increase the productivity in bird species in the boreal zone, at least in the short term.

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

Numerical prediction of augmented turbulent heat transfer in an annular fuel channel with repeated two-dimensional square ribs

International Nuclear Information System (INIS)

Takase, K.

1996-01-01

The square-ribbed fuel rod for high temperature gas-cooled reactors was designed and developed so as to enhance the turbulent heat transfer in comparison with the previous standard fuel rod. The turbulent heat transfer characteristics in an annular fuel channel with repeated two-dimensional square ribs were analysed numerically on a fully developed incompressible flow using the k-ε turbulence model and the two-dimensional axisymmetrical coordinate system. Numerical analyses were carried out under the conditions of Reynolds numbers from 3000 to 20000 and ratios of square-rib pitch to height of 10, 20 and 40 respectively. The predictions of the heat transfer coefficients agreed well within an error of 10% for the square-rib pitch to height ratio of 10, 20% for 20 and 25% for 40 respectively, with the heat transfer empirical correlations obtained from the experimental data due to the simulated square-ribbed fuel rods. Therefore it was found that the effect of heat transfer augmentation due to the square ribs could be predicted by the present numerical simulations and the mechanism could be explained by the change in the turbulence kinematic energy distribution along the flow direction. (orig.)

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.

Distinct coping strategies differentially predict urge levels and lapses in a smoking cessation attempt.

Science.gov (United States)

Brodbeck, Jeannette; Bachmann, Monica S; Znoj, Hansjörg

2013-06-01

This study analysed mechanisms through which stress-coping and temptation-coping strategies were associated with lapses. Furthermore, we explored whether distinct coping strategies differentially predicted reduced lapse risk, lower urge levels, or a weaker association between urge levels and lapses during the first week of an unassisted smoking cessation attempt. Participants were recruited via the internet and mass media in Switzerland. Ecological momentary assessment (EMA) with mobile devices was used to assess urge levels and lapses. Online questionnaires were used to measure smoking behaviours and coping variables at baseline, as well as smoking behaviour at the three-month follow-up. The sample consisted of 243 individuals, aged 20 to 40, who reported 4199 observations. Findings of multilevel regression analyses show that coping was mainly associated with a reduced lapse risk and not with lower urge levels or a weaker association between urge levels and lapses. 'Calming down' and 'commitment to change' predicted a lower lapse risk and also a weaker relation between urge levels and lapses. 'Stimulus control' predicted a lower lapse risk and lower urge levels. Conversely, 'task-orientation' and 'risk assessment' were related to higher lapse risk and 'risk assessment' also to higher urge levels. Disengagement coping i.e. 'eating or shopping', 'distraction', and 'mobilising social support' did not affect lapse risk. Promising coping strategies during the initial stage of smoking cessation attempt are targeted directly at reducing the lapse risk and are characterised by engagement with the stressor or one's reactions towards the stressor and a focus on positive consequences instead of health risks. Copyright © 2013 Elsevier Ltd. All rights reserved.

ERANOS 2.0, Modular code and data system for fast reactor neutronics analyses

International Nuclear Information System (INIS)

2008-01-01

1 - Description of program or function: The European Reactor Analysis Optimized calculation System, ERANOS, has been developed and validated with the aim of providing a suitable basis for reliable neutronic calculations of current as well as advanced fast reactor cores. It consists of data libraries, deterministic codes and calculation procedures which have been developed within the European Collaboration on Fast Reactors over the past 20 years or so, in order to answer the needs of both industrial and R and D organisations. The whole system counts roughly 250 functions and 3000 subroutines totalling 450000 lines of FORTRAN-77 and ESOPE instructions. ERANOS is written using the ALOS software which requires only standard FORTRAN compilers and includes advanced programming features. A modular structure was adopted for easier evolution and incorporation of new functionalities. Blocks of data (SETs) can be created or used by the modules themselves or by the user via the LU control language. Programming, and dynamic memory allocation, are performed by means of the ESOPE language. External temporary storage and permanent storage capabilities are provided by the GEMAT and ARCHIVE functions, respectively. ESOPE, LU, GEMAT and ARCHIVE are all part of the ALOS software. This modular structure allows different modules to be linked together in procedures corresponding to recommended calculation routes ranging from fast-running and moderately-accurate 'routine' procedures to slow-running but highly-accurate 'reference' procedures. The main contents of the ERANOS-2.0 package are: nuclear data libraries (multigroup cross-sections from the JEF-2.2 evaluated nuclear data file, and other specific data files), a cell and lattice code (ECCO), reactor flux solvers (diffusion, Sn transport, nodal variational transport), a burn-up module, various processing modules (material and neutron balance, breeding gains,...), tools related to perturbation theory and sensitivity analysis, core

The structure of late-life depressive symptoms across a 20-year span: a taxometric investigation.

Science.gov (United States)

Holland, Jason M; Schutte, Kathleen K; Brennan, Penny L; Moos, Rudolf H

2010-03-01

Past studies of the underlying structure of depressive symptoms have yielded mixed results, with some studies supporting a continuous conceptualization and others supporting a categorical one. However, no study has examined this research question with an exclusively older adult sample, despite the potential uniqueness of late-life depressive symptoms. In the present study, the underlying structure of late-life depressive symptoms was examined among a sample of 1,289 individuals across 3 waves of data collection spanning 20 years. The authors employed a taxometric methodology using indicators of depression derived from the Research Diagnostic Criteria (R. L. Spitzer, J. Endicott, & E. Robins, 1978). Maximum eigenvalue analyses and inchworm consistency tests generally supported a categorical conceptualization and identified a group that was primarily characterized by thoughts about death and suicide. However, compared to a categorical depression variable, depressive symptoms treated continuously were generally better predictors of relevant criterion variables. These findings suggest that thoughts of death and suicide may characterize a specific type of late-life depression, yet a continuous conceptualization still typically maximizes the predictive utility of late-life depressive symptoms.

Inelastic hadron-nucleus interactions at 20 and 37 GeV/c

International Nuclear Information System (INIS)

Faessler, M.A.; Lynen, U.; Niewisch, J.; Pietrzyk, B.; Povh, B.; Schroeder, H.; Gugelot, P.C.

1979-01-01

The experiment studies charged particle production for π - , K - , and anti p interactions on nuclei at 20 and 37 GeV/c at the CERN SPS. A non-magnetic detector, consisting of CsI(Tl) scintillation and lucite Cerenkov counters, distinguishes between fast particles, mainly pions, and slow particles, mainly nucleons, with a cut at velocity β approximately 0.7. Angular distributions, multiplicity distributions and correlations of slow and fast particles were analysed. It is shown that the measurement of the correlations can provide a critical test for different theoretical models of the hadron-nucleus interaction. At the energies studied so far a systematic deviation from KNO scaling is observed. This gives further support to the 'standard picture' of the hadron-nucleus interaction and it contrasts with predictions of the coherent-tube model. The regularity observed for the angular distribution of fast secondaries as a function of the number of slow particles can only be explained by combining features predicted by different models. (Auth.)

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

Predicting Psychotherapy Dropouts: A Multilevel Approach.

Science.gov (United States)

Kegel, Alexander F; Flückiger, Christoph

2015-01-01

The role of therapeutic processes in predicting premature termination of psychotherapy has been a particular focus of recent research. The purpose of this study was to contrast outpatients who completed therapy and those who dropped out with respect to their self-reported in-session experiences of self-esteem, mastery, clarification and the therapeutic alliance. The 296 patients with mixed disorders were treated with an integrative form of cognitive-behavioural therapy without pre-determined time limit (M = 20.2 sessions). Multilevel analyses indicated that patients who did not completetreatment reported, on average, lower levels of self-esteem, mastery and clarification and lower ratings of their therapeutic alliance in treatment in contrast to patients who completed therapy. Patient-reported change in self-esteem experiences over the course of treatment turned out to be the strongest predictor of dropout from psychotherapy or successful completion. When dropout occurred before the average treatment length was reached, patients reported fewer clarifying experiences as early as the first session and their ratings of the therapeutic alliance were characterized by an absence of positive development. Both of these aspects seem to be involved in patients' decisions to leave treatment early. The findings underscore the importance of the therapeutic process in understanding the mechanisms behind treatment dropout. Analyses data from 296 patients at a private outpatient clinic in a routine practice setting (CBT). Completer/dropout definition: presence or absence of measurement battery at post-assessment. Focuses on change in therapy processes by investigating post-session reports. Finds that positive changes in self-esteem experiences is the most robust predictor of dropout, followed by ratings of clarification experiences and the global alliance. In line with recent dropout research, these process indicators might help to detect therapeutic situations that are

Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.

Science.gov (United States)

Sánchez, Rubén; Serra, François; Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Pulido, Luis; de María, Alejandro; Capella-Gutíerrez, Salvador; Huerta-Cepas, Jaime; Gabaldón, Toni; Dopazo, Joaquín; Dopazo, Hernán

2011-07-01

Phylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing.

Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing

Science.gov (United States)

Sánchez, Rubén; Serra, François; Tárraga, Joaquín; Medina, Ignacio; Carbonell, José; Pulido, Luis; de María, Alejandro; Capella-Gutíerrez, Salvador; Huerta-Cepas, Jaime; Gabaldón, Toni; Dopazo, Joaquín; Dopazo, Hernán

2011-01-01

Phylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing. PMID:21646336

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

Validation of the sperm class analyser CASA system for sperm counting in a busy diagnostic semen analysis laboratory.

Science.gov (United States)

Dearing, Chey G; Kilburn, Sally; Lindsay, Kevin S

2014-03-01

Sperm counts have been linked to several fertility outcomes making them an essential parameter of semen analysis. It has become increasingly recognised that Computer-Assisted Semen Analysis (CASA) provides improved precision over manual methods but that systems are seldom validated robustly for use. The objective of this study was to gather the evidence to validate or reject the Sperm Class Analyser (SCA) as a tool for routine sperm counting in a busy laboratory setting. The criteria examined were comparison with the Improved Neubauer and Leja 20-μm chambers, within and between field precision, sperm concentration linearity from a stock diluted in semen and media, accuracy against internal and external quality material, assessment of uneven flow effects and a receiver operating characteristic (ROC) analysis to predict fertility in comparison with the Neubauer method. This work demonstrates that SCA CASA technology is not a standalone 'black box', but rather a tool for well-trained staff that allows rapid, high-number sperm counting providing errors are identified and corrected. The system will produce accurate, linear, precise results, with less analytical variance than manual methods that correlate well against the Improved Neubauer chamber. The system provides superior predictive potential for diagnosing fertility problems.

Antiferromagnetism in a 20% Ho-80% Tb alloy single crystal

DEFF Research Database (Denmark)

Lebech, Bente

1968-01-01

20% Ho-80% Tb exhibits two magnetic phases, similar to those of Tb. The spiral turn angle varies from 31.1° to 21.4°. A minimum effective spin for the occurrence of stable simple ferromagnetic structure at low temperatures is predicted....

Vision 20/20: Automation and advanced computing in clinical radiation oncology

International Nuclear Information System (INIS)

Moore, Kevin L.; Moiseenko, Vitali; Kagadis, George C.; McNutt, Todd R.; Mutic, Sasa

2014-01-01

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy

Vision 20/20: Automation and advanced computing in clinical radiation oncology

Energy Technology Data Exchange (ETDEWEB)

Moore, Kevin L., E-mail: kevinmoore@ucsd.edu; Moiseenko, Vitali [Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, California 92093 (United States); Kagadis, George C. [Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 26504 (Greece); McNutt, Todd R. [Department of Radiation Oncology and Molecular Radiation Science, School of Medicine, Johns Hopkins University, Baltimore, Maryland 21231 (United States); Mutic, Sasa [Department of Radiation Oncology, Washington University in St. Louis, St. Louis, Missouri 63110 (United States)

2014-01-15

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

Vision 20/20: Automation and advanced computing in clinical radiation oncology.

Science.gov (United States)

Moore, Kevin L; Kagadis, George C; McNutt, Todd R; Moiseenko, Vitali; Mutic, Sasa

2014-01-01

This Vision 20/20 paper considers what computational advances are likely to be implemented in clinical radiation oncology in the coming years and how the adoption of these changes might alter the practice of radiotherapy. Four main areas of likely advancement are explored: cloud computing, aggregate data analyses, parallel computation, and automation. As these developments promise both new opportunities and new risks to clinicians and patients alike, the potential benefits are weighed against the hazards associated with each advance, with special considerations regarding patient safety under new computational platforms and methodologies. While the concerns of patient safety are legitimate, the authors contend that progress toward next-generation clinical informatics systems will bring about extremely valuable developments in quality improvement initiatives, clinical efficiency, outcomes analyses, data sharing, and adaptive radiotherapy.

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

Directory of Open Access Journals (Sweden)

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.

Pensions at a glance 2015 OECD and G20 indicators

CERN Document Server

2016-01-01

The 10-year anniversary edition of Pensions at a Glance highlights the pension reforms undertaken by OECD and G20 countries over the last two years. Two special chapters provide deeper analysis of first-tier pension schemes and of the impact of short or interrupted careers, due to late entry into employment, childcare or unemployment, on pension entitlements. Another chapter analyses the sensitivity of long-term pension replacement rates on various parameters. A range of indicators for comparing pension policies and their outcomes between OECD and G20 countries is also provided.

Analysing Culture and Interculture in Saudi EFL Textbooks: A Corpus Linguistic Approach

Science.gov (United States)

Almujaiwel, Sultan

2018-01-01

This paper combines corpus processing tools to investigate the cultural elements of Saudi education of English as a foreign language (EFL). The latest Saudi EFL textbooks (2016 onwards) are available in researchable PDF formats. This helps process them through corpus search software tools. The method adopted is based on analysing 20 cultural…

The Sources of Life Chances: Does Education, Class Category, Occupation, or Short-Term Earnings Predict 20-Year Long-Term Earnings?

Directory of Open Access Journals (Sweden)

ChangHwan Kim

2018-03-01

Full Text Available In sociological studies of economic stratification and intergenerational mobility, occupation has long been presumed to reflect lifetime earnings better than do short-term earnings. However, few studies have actually tested this critical assumption. In this study, we investigate the cross-sectional determinants of 20-year accumulated earnings using data that match respondents in the Survey of Income and Program Participation to their longitudinal earnings records based on administrative tax information from 1990 to 2009. Fit statistics of regression models are estimated to assess the predictive power of various proxy variables, including occupation, education, and short-term earnings, on cumulative earnings over the 20-year time period. Contrary to the popular assumption in sociology, our results find that cross-sectional earnings have greater predictive power on long-term earnings than occupation-based class classifications, including three-digit detailed occupations for both men and women. The model based on educational attainment, including field of study, has slightly better fit than models based on one-digit occupation or the Erikson, Goldthorpe, and Portocarero class scheme. We discuss the theoretical implications of these findings for the sociology of stratification and intergenerational mobility.

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.)

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

probability, there are more important effects contributing to variations of MEm that are not explained or are independent from these functions. Furthermore, autocorrelations exist between indicator traits and predicted MEm. Nevertheless, this integrative approach, combining information from dairy cattle nutrition with dairy cattle genetics, generated novel traits which are difficult to record on a large scale. The simulated data basis for MEm was used to determine the size of a cow calibration group for genomic selection. A calibration group including 2,581 cows with MEm phenotypes was competitive with conventional breeding strategies. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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.

Loss of epithelial FAM20A in mice causes amelogenesis imperfecta, tooth eruption delay and gingival overgrowth.

Science.gov (United States)

Li, Li-Li; Liu, Pei-Hong; Xie, Xiao-Hua; Ma, Su; Liu, Chao; Chen, Li; Qin, Chun-Lin

2016-06-30

FAM20A has been studied to a very limited extent. Mutations in human FAM20A cause amelogenesis imperfecta, gingival fibromatosis and kidney problems. It would be desirable to systemically analyse the expression of FAM20A in dental tissues and to assess the pathological changes when this molecule is specifically nullified in individual tissues. Recently, we generated mice with a Fam20A-floxed allele containing the beta-galactosidase reporter gene. We analysed FAM20A expression in dental tissues using X-Gal staining, immunohistochemistry and in situ hybridization, which showed that the ameloblasts in the mouse mandibular first molar began to express FAM20A at 1 day after birth, and the reduced enamel epithelium in erupting molars expressed a significant level of FAM20A. By breeding K14-Cre mice with Fam20A(flox/flox) mice, we created K14-Cre;Fam20A(flox/flox) (conditional knock out, cKO) mice, in which Fam20A was inactivated in the epithelium. We analysed the dental tissues of cKO mice using X-ray radiography, histology and immunohistochemistry. The molar enamel matrix in cKO mice was much thinner than normal and was often separated from the dentinoenamel junction. The Fam20A-deficient ameloblasts were non-polarized and disorganized and were detached from the enamel matrix. The enamel abnormality in cKO mice was consistent with the diagnosis of amelogenesis imperfecta. The levels of enamelin and matrix metalloproteinase 20 were lower in the ameloblasts and enamel of cKO mice than the normal mice. The cKO mice had remarkable delays in the eruption of molars and hyperplasia of the gingival epithelium. The findings emphasize the essential roles of FAM20A in the development of dental and oral tissues.

Response to a combination of oxygen and a hypnotic as treatment for obstructive sleep apnoea is predicted by a patient's therapeutic CPAP requirement.

Science.gov (United States)

Landry, Shane A; Joosten, Simon A; Sands, Scott A; White, David P; Malhotra, Atul; Wellman, Andrew; Hamilton, Garun S; Edwards, Bradley A

2017-08-01

Upper airway collapsibility predicts the response to several non-continuous positive airway pressure (CPAP) interventions for obstructive sleep apnoea (OSA). Measures of upper airway collapsibility cannot be easily performed in a clinical context; however, a patient's therapeutic CPAP requirement may serve as a surrogate measure of collapsibility. The present work aimed to compare the predictive use of CPAP level with detailed physiological measures of collapsibility. Therapeutic CPAP levels and gold-standard pharyngeal collapsibility measures (passive pharyngeal critical closing pressure (P crit ) and ventilation at CPAP level of 0 cmH 2 O (V passive )) were retrospectively analysed from a randomized controlled trial (n = 20) comparing the combination of oxygen and eszopiclone (treatment) versus placebo/air control. Responders (9/20) to treatment were defined as those who exhibited a 50% reduction in apnoea/hypopnoea index (AHI) plus an AHICPAP requirement compared with non-responders (6.6 (5.4-8.1)  cmH 2 O vs 8.9 (8.4-10.4) cmH 2 O, P = 0.007), consistent with their reduced collapsibility (lower P crit , P = 0.017, higher V passive P = 0.025). Therapeutic CPAP level provided the highest predictive accuracy for differentiating responders from non-responders (area under the curve (AUC) = 0.86 ± 0.9, 95% CI: 0.68-1.00, P = 0.007). However, both P crit (AUC = 0.83 ± 0.11, 95% CI: 0.62-1.00, P = 0.017) and V passive (AUC = 0.77 ± 0.12, 95% CI: 0.53-1.00, P = 0.44) performed well, and the difference in AUC for these three metrics was not statistically different. A therapeutic CPAP level ≤8 cmH 2 O provided 78% sensitivity and 82% specificity (positive predictive value = 78%, negative predictive value = 82%) for predicting a response to these therapies. Therapeutic CPAP requirement, as a surrogate measure of pharyngeal collapsibility, predicts the response to non-anatomical therapy (oxygen and

Pahute Mesa Well Development and Testing Analyses for Wells ER-20-8 and ER-20-4, Nevada National Security Site, Nye County, Nevada, Revision 0

Energy Technology Data Exchange (ETDEWEB)

Greg Ruskauff and Sam Marutzky

2012-09-01

Wells ER-20-4 and ER-20-8 were drilled during fiscal year (FY) 2009 and FY 2010 (NNSA/NSO, 2011a and b). The closest underground nuclear test detonations to the area of investigation are TYBO (U-20y), BELMONT (U-20as), MOLBO (U-20ag), BENHAM (U-20c), and HOYA (U-20 be) (Figure 1-1). The TYBO, MOLBO, and BENHAM detonations had working points located below the regional water table. The BELMONT and HOYA detonation working points were located just above the water table, and the cavity for these detonations are calculated to extend below the water table (Pawloski et al., 2002). The broad purpose of Wells ER-20-4 and ER-20-8 is to determine the extent of radionuclide-contaminated groundwater, the geologic formations, groundwater geochemistry as an indicator of age and origin, and the water-bearing properties and hydraulic conditions that influence radionuclide migration. Well development and testing is performed to determine the hydraulic properties at the well and between other wells, and to obtain groundwater samples at the well that are representative of the formation at the well. The area location, wells, underground nuclear detonations, and other features are shown in Figure 1-1. Hydrostratigraphic cross sections A-A’, B-B’, C-C’, and D-D’ are shown in Figures 1-2 through 1-5, respectively.

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.

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].

Predicting well-being longitudinally for mothers rearing offspring with intellectual and developmental disabilities.

Science.gov (United States)

Grein, K A; Glidden, L M

2015-07-01

Well-being outcomes for parents of children with intellectual and developmental disabilities (IDD) may vary from positive to negative at different times and for different measures of well-being. Predicting and explaining this variability has been a major focus of family research for reasons that have both theoretical and applied implications. The current study used data from a 23-year longitudinal investigation of adoptive and birth parents of children with IDD to determine which early child, mother and family characteristics would predict the variance in maternal outcomes 20 years after their original measurement. Using hierarchical regression analyses, we tested the predictive power of variables measured when children were 7 years old on outcomes of maternal well-being when children were 26 years old. Outcome variables included maternal self-report measures of depression and well-being. Final models of well-being accounted for 20% to 34% of variance. For most outcomes, Family Accord and/or the personality variable of Neuroticism (emotional stability/instability) were significant predictors, but some variables demonstrated a different pattern. These findings confirm that (1) characteristics of the child, mother and family during childhood can predict outcomes of maternal well-being 20 years later; and (2) different predictor-outcome relationships can vary substantially, highlighting the importance of using multiple measures to gain a more comprehensive understanding of maternal well-being. These results have implications for refining prognoses for parents and for tailoring service delivery to individual child, parent and family characteristics. © 2014 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data

Directory of Open Access Journals (Sweden)

Sarah J. Graves

2016-02-01

Full Text Available Mapping species through classification of imaging spectroscopy data is facilitating research to understand tree species distributions at increasingly greater spatial scales. Classification requires a dataset of field observations matched to the image, which will often reflect natural species distributions, resulting in an imbalanced dataset with many samples for common species and few samples for less common species. Despite the high prevalence of imbalanced datasets in multiclass species predictions, the effect on species prediction accuracy and landscape species abundance has not yet been quantified. First, we trained and assessed the accuracy of a support vector machine (SVM model with a highly imbalanced dataset of 20 tropical species and one mixed-species class of 24 species identified in a hyperspectral image mosaic (350–2500 nm of Panamanian farmland and secondary forest fragments. The model, with an overall accuracy of 62% ± 2.3% and F-score of 59% ± 2.7%, was applied to the full image mosaic (23,000 ha at a 2-m resolution to produce a species prediction map, which suggested that this tropical agricultural landscape is more diverse than what has been presented in field-based studies. Second, we quantified the effect of class imbalance on model accuracy. Model assessment showed a trend where species with more samples were consistently over predicted while species with fewer samples were under predicted. Standardizing sample size reduced model accuracy, but also reduced the level of species over- and under-prediction. This study advances operational species mapping of diverse tropical landscapes by detailing the effect of imbalanced data on classification accuracy and providing estimates of tree species abundance in an agricultural landscape. Species maps using data and methods presented here can be used in landscape analyses of species distributions to understand human or environmental effects, in addition to focusing conservation

Investigation of the tensor analysing power T{sub 20} in the vector d+p→{sup 3}He+η reaction with the COSY-ANKE experiment

Energy Technology Data Exchange (ETDEWEB)

Papenbrock, Michael Paul

2016-07-01

The work presented here is a contribution to the ongoing search for quasi-bound states between mesons and nuclei. Early theoretical predictions estimated that an η-meson may form a quasi-bound state with nuclei with a mass number of A≥12. Many measurements in this field have revealed evidence that such a state may indeed exist. More interestingly, it may already form at much lower mass numbers, e.g. between an η-meson and {sup 3}He nucleus. Of special note is an unpolarised measurement of the d+p→{sup 3}He+η reaction, which has been studied in unprecedented detail in the excess energy range -5 MeVa quasi-bound η{sup 3}He state was found by parametrising total and differential cross sections and extracting the final state interaction between the two ejectiles, which was found to be surprisingly strong. However, with both beam and target being unpolarised, possible contributions of the initial state to the cross section could not be investigated. In the d+p→{sup 3}He+η reaction the final state can be produced from two different initial spin states with S=1/2 and S=3/2. If the production amplitudes of these respective states inhibit a different energy dependence, it could manifest in the shape of the total cross section in an unpolarised measurement, thereby affecting the determination of the final state interaction. A new measurement with a vector and tensor polarised deuteron beam on the vector d+p→{sup 3}He+η reaction was performed with COSY-ANKE in the same excess energy range, i.e. -5 MeVanalysing power T{sub 20}. The extracted values of T{sub 20} are compatible with a constant across this energy range. A linear fit revealed only a rather small possible energy dependence. Hence, the possible impact of the initial spin states on the extraction of the final state interaction was found to be of very little significance. Combining

HIV-1 DNA predicts disease progression and post-treatment virological control

Science.gov (United States)

Williams, James P; Hurst, Jacob; Stöhr, Wolfgang; Robinson, Nicola; Brown, Helen; Fisher, Martin; Kinloch, Sabine; Cooper, David; Schechter, Mauro; Tambussi, Giuseppe; Fidler, Sarah; Carrington, Mary; Babiker, Abdel; Weber, Jonathan

2014-01-01

In HIV-1 infection, a population of latently infected cells facilitates viral persistence despite antiretroviral therapy (ART). With the aim of identifying individuals in whom ART might induce a period of viraemic control on stopping therapy, we hypothesised that quantification of the pool of latently infected cells in primary HIV-1 infection (PHI) would predict clinical progression and viral replication following ART. We measured HIV-1 DNA in a highly characterised randomised population of individuals with PHI. We explored associations between HIV-1 DNA and immunological and virological markers of clinical progression, including viral rebound in those interrupting therapy. In multivariable analyses, HIV-1 DNA was more predictive of disease progression than plasma viral load and, at treatment interruption, predicted time to plasma virus rebound. HIV-1 DNA may help identify individuals who could safely interrupt ART in future HIV-1 eradication trials. Clinical trial registration: ISRCTN76742797 and EudraCT2004-000446-20 DOI: http://dx.doi.org/10.7554/eLife.03821.001 PMID:25217531

Human Factors Risk Analyses of a Doffing Protocol for Ebola-Level Personal Protective Equipment: Mapping Errors to Contamination.

Science.gov (United States)

Mumma, Joel M; Durso, Francis T; Ferguson, Ashley N; Gipson, Christina L; Casanova, Lisa; Erukunuakpor, Kimberly; Kraft, Colleen S; Walsh, Victoria L; Zimring, Craig; DuBose, Jennifer; Jacob, Jesse T

2018-03-05

Doffing protocols for personal protective equipment (PPE) are critical for keeping healthcare workers (HCWs) safe during care of patients with Ebola virus disease. We assessed the relationship between errors and self-contamination during doffing. Eleven HCWs experienced with doffing Ebola-level PPE participated in simulations in which HCWs donned PPE marked with surrogate viruses (ɸ6 and MS2), completed a clinical task, and were assessed for contamination after doffing. Simulations were video recorded, and a failure modes and effects analysis and fault tree analyses were performed to identify errors during doffing, quantify their risk (risk index), and predict contamination data. Fifty-one types of errors were identified, many having the potential to spread contamination. Hand hygiene and removing the powered air purifying respirator (PAPR) hood had the highest total risk indexes (111 and 70, respectively) and number of types of errors (9 and 13, respectively). ɸ6 was detected on 10% of scrubs and the fault tree predicted a 10.4% contamination rate, likely occurring when the PAPR hood inadvertently contacted scrubs during removal. MS2 was detected on 10% of hands, 20% of scrubs, and 70% of inner gloves and the predicted rates were 7.3%, 19.4%, 73.4%, respectively. Fault trees for MS2 and ɸ6 contamination suggested similar pathways. Ebola-level PPE can both protect and put HCWs at risk for self-contamination throughout the doffing process, even among experienced HCWs doffing with a trained observer. Human factors methodologies can identify error-prone steps, delineate the relationship between errors and self-contamination, and suggest remediation strategies.

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

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.

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…

BEAN 2.0: an integrated web resource for the identification and functional analysis of type III secreted effectors.

Science.gov (United States)

Dong, Xiaobao; Lu, Xiaotian; Zhang, Ziding

2015-01-01

Gram-negative pathogenic bacteria inject type III secreted effectors (T3SEs) into host cells to sabotage their immune signaling networks. Because T3SEs constitute a meeting-point of pathogen virulence and host defense, they are of keen interest to host-pathogen interaction research community. To accelerate the identification and functional understanding of T3SEs, we present BEAN 2.0 as an integrated web resource to predict, analyse and store T3SEs. BEAN 2.0 includes three major components. First, it provides an accurate T3SE predictor based on a hybrid approach. Using independent testing data, we show that BEAN 2.0 achieves a sensitivity of 86.05% and a specificity of 100%. Second, it integrates a set of online sequence analysis tools. Users can further perform functional analysis of putative T3SEs in a seamless way, such as subcellular location prediction, functional domain scan and disorder region annotation. Third, it compiles a database covering 1215 experimentally verified T3SEs and constructs two T3SE-related networks that can be used to explore the relationships among T3SEs. Taken together, by presenting a one-stop T3SE bioinformatics resource, we hope BEAN 2.0 can promote comprehensive understanding of the function and evolution of T3SEs. © The Author(s) 2015. Published by Oxford University Press.

Applying a radiomics approach to predict prognosis of lung cancer patients

Science.gov (United States)

Emaminejad, Nastaran; Yan, Shiju; Wang, Yunzhi; Qian, Wei; Guan, Yubao; Zheng, Bin

2016-03-01

Radiomics is an emerging technology to decode tumor phenotype based on quantitative analysis of image features computed from radiographic images. In this study, we applied Radiomics concept to investigate the association among the CT image features of lung tumors, which are either quantitatively computed or subjectively rated by radiologists, and two genomic biomarkers namely, protein expression of the excision repair cross-complementing 1 (ERCC1) genes and a regulatory subunit of ribonucleotide reductase (RRM1), in predicting disease-free survival (DFS) of lung cancer patients after surgery. An image dataset involving 94 patients was used. Among them, 20 had cancer recurrence within 3 years, while 74 patients remained DFS. After tumor segmentation, 35 image features were computed from CT images. Using the Weka data mining software package, we selected 10 non-redundant image features. Applying a SMOTE algorithm to generate synthetic data to balance case numbers in two DFS ("yes" and "no") groups and a leave-one-case-out training/testing method, we optimized and compared a number of machine learning classifiers using (1) quantitative image (QI) features, (2) subjective rated (SR) features, and (3) genomic biomarkers (GB). Data analyses showed relatively lower correlation among the QI, SR and GB prediction results (with Pearson correlation coefficients 0.5). Among them, using QI yielded the highest performance.

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

Sydlangeland Fjernvarme A.m.b.a. Feasibility study on 10-20.000 m{sup 3} pond heat storage[Denmark]; Sydlangeland Fjernvarme A.m.b.a. Forundersoegelse for 10-20.000 m{sup 3} damvarmelager

Energy Technology Data Exchange (ETDEWEB)

Visbjerg, L. [Sydlangeland Fjernvarme A.m.b.a. (Denmark); Wesenberg, C.; Bliksted, T. [NIRAS Raadgivende Ingenioerer og Planlaeggere A/S (Denmark); Porsvig, M. [Geoteknisk Institut (Denmark); Duer, K. [DTU, Solenergi Center Danmark (Denmark)

2000-11-01

The project includes siting analyses, geotechnical feasibility studies and evaluations of operating economy for establishing a seasonal heat storage carried out as a 10-20,000 m{sup 3} pilot pond heat storage at Sydlangeland straw-fired district heating plant. (EHS)

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.

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

Recent plant studies using Victoria 2.0

International Nuclear Information System (INIS)

Bixler, Nathan E.; Gasser, Ronald D.

2000-01-01

VICTORIA 2.0 is a mechanistic computer code designed to analyze fission product behavior within the reactor coolant system (RCS) during a severe nuclear reactor accident. It provides detailed predictions of the release of radioactive and nonradioactive materials from the reactor core and transport and deposition of these materials within the RCS and secondary circuits. These predictions account for the chemical and aerosol processes that affect radionuclide behavior. VICTORIA 2.0 was released in early 1999; a new version VICTORIA 2.1, is now under development. The largest improvements in VICTORIA 2.1 are connected with the thermochemical database, which is being revised and expanded following the recommendations of a peer review. Three risk-significant severe accident sequences have recently been investigated using the VICTORIA 2.0 code. The focus here is on how various chemistry options affect the predictions. Additionally, the VICTORIA predictions are compared with ones made using the MELCOR code. The three sequences are a station blackout in a GE BWR and steam generator tube rupture (SGTR) and pump-seal LOCA sequences in a 3-loop Westinghouse PWR. These sequences cover a range of system pressures, from fully depressurized to full system pressure. The chief results of this study are the fission product fractions that are retained in the core, RCS, secondary, and containment and the fractions that are released into the environment

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.

Neutron radiative capture by the 241Am nucleus in the energy range 1 keV-20 MeV

International Nuclear Information System (INIS)

Zolotarev, K.I.; Ignatyuk, A.V.; Tolstikov, V.A.; Tertychnyj, G.Ya.

1998-01-01

Production of high actinides leads to many technological problems in the nuclear power. The 241 Am(n,γ) 242 Am reaction is one of the sources of high actinide buildup. So a knowledge of the radiative capture cross-section of 241 Am for neutron energies up to 20 MeV is of considerable important for present day fission reactors and future advanced reactors. The main goal of this paper is the evaluation of the excitation function for the reaction 241 Am(n,γ) 242 Am in the energy range 1 keV-20 MeV. The evaluation was done on the basis of analysed experimental data, data from theoretical model calculations and systematic predictions for 14.5 MeV and 20 MeV. Data from the present evaluation are compared with the cross-section values given in the evaluations carried out earlier. (author)

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.

MED: a new non-supervised gene prediction algorithm for bacterial and archaeal genomes

Directory of Open Access Journals (Sweden)

Yang Yi-Fan

2007-03-01

Full Text Available Abstract Background Despite a remarkable success in the computational prediction of genes in Bacteria and Archaea, a lack of comprehensive understanding of prokaryotic gene structures prevents from further elucidation of differences among genomes. It continues to be interesting to develop new ab initio algorithms which not only accurately predict genes, but also facilitate comparative studies of prokaryotic genomes. Results This paper describes a new prokaryotic genefinding algorithm based on a comprehensive statistical model of protein coding Open Reading Frames (ORFs and Translation Initiation Sites (TISs. The former is based on a linguistic "Entropy Density Profile" (EDP model of coding DNA sequence and the latter comprises several relevant features related to the translation initiation. They are combined to form a so-called Multivariate Entropy Distance (MED algorithm, MED 2.0, that incorporates several strategies in the iterative program. The iterations enable us to develop a non-supervised learning process and to obtain a set of genome-specific parameters for the gene structure, before making the prediction of genes. Conclusion Results of extensive tests show that MED 2.0 achieves a competitive high performance in the gene prediction for both 5' and 3' end matches, compared to the current best prokaryotic gene finders. The advantage of the MED 2.0 is particularly evident for GC-rich genomes and archaeal genomes. Furthermore, the genome-specific parameters given by MED 2.0 match with the current understanding of prokaryotic genomes and may serve as tools for comparative genomic studies. In particular, MED 2.0 is shown to reveal divergent translation initiation mechanisms in archaeal genomes while making a more accurate prediction of TISs compared to the existing gene finders and the current GenBank annotation.

Analysing harmonic motions with an iPhone’s magnetometer

Science.gov (United States)

Yavuz, Ahmet; Kağan Temiz, Burak

2016-05-01

In this paper, we propose an experiment for analysing harmonic motion using an iPhone’s (or iPad’s) magnetometer. This experiment consists of the detection of magnetic field variations obtained from an iPhone’s magnetometer sensor. A graph of harmonic motion is directly displayed on the iPhone’s screen using the Sensor Kinetics application. Data from this application was analysed with Eureqa software to establish the equation of the harmonic motion. Analyses show that the use of an iPhone’s magnetometer to analyse harmonic motion is a practical and effective method for small oscillations and frequencies less than 15-20 Hz.

Maladaptive social information processing in childhood predicts young men's atypical amygdala reactivity to threat.

Science.gov (United States)

Choe, Daniel Ewon; Shaw, Daniel S; Forbes, Erika E

2015-05-01

Maladaptive social information processing, such as hostile attributional bias and aggressive response generation, is associated with childhood maladjustment. Although social information processing problems are correlated with heightened physiological responses to social threat, few studies have examined their associations with neural threat circuitry, specifically amygdala activation to social threat. A cohort of 310 boys participated in an ongoing longitudinal study and completed questionnaires and laboratory tasks assessing their social and cognitive characteristics the boys were between 10 and 12 years of age. At age 20, 178 of these young men underwent functional magnetic resonance imaging and a social threat task. At age 22, adult criminal arrest records and self-reports of impulsiveness were obtained. Path models indicated that maladaptive social information-processing at ages 10 and 11 predicted increased left amygdala reactivity to fear faces, an ambiguous threat, at age 20 while accounting for childhood antisocial behavior, empathy, IQ, and socioeconomic status. Exploratory analyses indicated that aggressive response generation - the tendency to respond to threat with reactive aggression - predicted left amygdala reactivity to fear faces and was concurrently associated with empathy, antisocial behavior, and hostile attributional bias, whereas hostile attributional bias correlated with IQ. Although unrelated to social information-processing problems, bilateral amygdala reactivity to anger faces at age 20 was unexpectedly predicted by low IQ at age 11. Amygdala activation did not mediate associations between social information processing and number of criminal arrests, but both impulsiveness at age 22 and arrests were correlated with right amygdala reactivity to anger facial expressions at age 20. Childhood social information processing and IQ predicted young men's amygdala response to threat a decade later, which suggests that childhood social

Cell division cycle 20 overexpression predicts poor prognosis for patients with lung adenocarcinoma.

Science.gov (United States)

Shi, Run; Sun, Qi; Sun, Jing; Wang, Xin; Xia, Wenjie; Dong, Gaochao; Wang, Anpeng; Jiang, Feng; Xu, Lin

2017-03-01

The cell division cycle 20, a key component of spindle assembly checkpoint, is an essential activator of the anaphase-promoting complex. Aberrant expression of cell division cycle 20 has been detected in various human cancers. However, its clinical significance has never been deeply investigated in non-small-cell lung cancer. By analyzing The Cancer Genome Atlas database and using some certain online databases, we validated overexpression of cell division cycle 20 in both messenger RNA and protein levels, explored its clinical significance, and evaluated the prognostic role of cell division cycle 20 in non-small-cell lung cancer. Cell division cycle 20 expression was significantly correlated with sex (p = 0.003), histological classification (p overexpression of cell division cycle 20 was significantly associated with bigger primary tumor size (p = 0.0023), higher MKI67 level (r = 0.7618, p Overexpression of cell division cycle 20 is associated with poor prognosis in lung adenocarcinoma patients, and its overexpression can also be used to identify high-risk groups. In conclusion, cell division cycle 20 might serve as a potential biomarker for lung adenocarcinoma patients.

Usage Analysis of Web 2.0 and Library 2.0 Tools by Librarians in Kwara State Academic Libraries

Science.gov (United States)

Tella, Adeyinka; Soluoku, Taofeeqat

2016-01-01

This study analysed the usage of Web 2.0 and Library 2.0 tools by librarians in Kwara State academic libraries. A sample of 40 librarians was surveyed through total enumeration sampling technique from four different tertiary education institutions libraries in Kwara State, Nigeria. Questionnaire was used for the collection of data. The collected…

Predicting the multi-domain progression of Parkinson's disease: a Bayesian multivariate generalized linear mixed-effect model.

Science.gov (United States)

Wang, Ming; Li, Zheng; Lee, Eun Young; Lewis, Mechelle M; Zhang, Lijun; Sterling, Nicholas W; Wagner, Daymond; Eslinger, Paul; Du, Guangwei; Huang, Xuemei

2017-09-25

It is challenging for current statistical models to predict clinical progression of Parkinson's disease (PD) because of the involvement of multi-domains and longitudinal data. Past univariate longitudinal or multivariate analyses from cross-sectional trials have limited power to predict individual outcomes or a single moment. The multivariate generalized linear mixed-effect model (GLMM) under the Bayesian framework was proposed to study multi-domain longitudinal outcomes obtained at baseline, 18-, and 36-month. The outcomes included motor, non-motor, and postural instability scores from the MDS-UPDRS, and demographic and standardized clinical data were utilized as covariates. The dynamic prediction was performed for both internal and external subjects using the samples from the posterior distributions of the parameter estimates and random effects, and also the predictive accuracy was evaluated based on the root of mean square error (RMSE), absolute bias (AB) and the area under the receiver operating characteristic (ROC) curve. First, our prediction model identified clinical data that were differentially associated with motor, non-motor, and postural stability scores. Second, the predictive accuracy of our model for the training data was assessed, and improved prediction was gained in particularly for non-motor (RMSE and AB: 2.89 and 2.20) compared to univariate analysis (RMSE and AB: 3.04 and 2.35). Third, the individual-level predictions of longitudinal trajectories for the testing data were performed, with ~80% observed values falling within the 95% credible intervals. Multivariate general mixed models hold promise to predict clinical progression of individual outcomes in PD. The data was obtained from Dr. Xuemei Huang's NIH grant R01 NS060722 , part of NINDS PD Biomarker Program (PDBP). All data was entered within 24 h of collection to the Data Management Repository (DMR), which is publically available ( https://pdbp.ninds.nih.gov/data-management ).

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.

Older but not wiser—Predicting a partner's preferences gets worse with age

OpenAIRE

Scheibehenne, Benjamin; Todd, Peter M.; Mata, Jutta

2011-01-01

To test the influence of relationship length on ability to predict a partner's preferences, 58 younger (M = 24.1 years) and 20 older (M = 68.7 years) couples made predictions in three domains that varied in daily importance. While prediction accuracy was generally better than chance, longer relationship length correlated with lower prediction accuracy and greater overconfidence. The difference in accuracy between older and younger couples increased for strong preferences and when controlling ...

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.

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.

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.

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.

Microstructure Evolution and Flow Stress Model of a 20Mn5 Hollow Steel Ingot during Hot Compression.

Science.gov (United States)

Liu, Min; Ma, Qing-Xian; Luo, Jian-Bin

2018-03-21

20Mn5 steel is widely used in the manufacture of heavy hydro-generator shaft due to its good performance of strength, toughness and wear resistance. However, the hot deformation and recrystallization behaviors of 20Mn5 steel compressed under high temperature were not studied. In this study, the hot compression experiments under temperatures of 850-1200 °C and strain rates of 0.01/s-1/s are conducted using Gleeble thermal and mechanical simulation machine. And the flow stress curves and microstructure after hot compression are obtained. Effects of temperature and strain rate on microstructure are analyzed. Based on the classical stress-dislocation relation and the kinetics of dynamic recrystallization, a two-stage constitutive model is developed to predict the flow stress of 20Mn5 steel. Comparisons between experimental flow stress and predicted flow stress show that the predicted flow stress values are in good agreement with the experimental flow stress values, which indicates that the proposed constitutive model is reliable and can be used for numerical simulation of hot forging of 20Mn5 hollow steel ingot.

Mutations in SLC20A2 are a major cause of familial idiopathic basal ganglia calcification

Science.gov (United States)

Hsu, Sandy Chan; Sears, Renee L.; Lemos, Roberta R.; Quintáns, Beatriz; Huang, Alden; Spiteri, Elizabeth; Nevarez, Lisette; Mamah, Catherine; Zatz, Mayana; Pierce, Kerrie D.; Fullerton, Janice M.; Adair, John C.; Berner, Jon E.; Bower, Matthew; Brodaty, Henry; Carmona, Olga; Dobricić, Valerija; Fogel, Brent L.; García-Estevez, Daniel; Goldman, Jill; Goudreau, John L.; Hopfer, Suellen; Janković, Milena; Jaumà, Serge; Jen, Joanna C.; Kirdlarp, Suppachok; Klepper, Joerg; Kostić, Vladimir; Lang, Anthony E.; Linglart, Agnès; Maisenbacher, Melissa K.; Manyam, Bala V.; Mazzoni, Pietro; Miedzybrodzka, Zofia; Mitarnun, Witoon; Mitchell, Philip B.; Mueller, Jennifer; Novaković, Ivana; Paucar, Martin; Paulson, Henry; Simpson, Sheila A.; Svenningsson, Per; Tuite, Paul; Vitek, Jerrold; Wetchaphanphesat, Suppachok; Williams, Charles; Yang, Michele; Schofield, Peter R.; de Oliveira, João R. M.; Sobrido, María-Jesús

2014-01-01

Familial idiopathic basal ganglia calcification (IBGC) or Fahr’s disease is a rare neurodegenerative disorder characterized by calcium deposits in the basal ganglia and other brain regions, which is associated with neuropsychiatric and motor symptoms. Familial IBGC is genetically heterogeneous and typically transmitted in an autosomal dominant fashion. We performed a mutational analysis of SLC20A2, the first gene found to cause IBGC, to assess its genetic contribution to familial IBGC. We recruited 218 subjects from 29 IBGC-affected families of varied ancestry and collected medical history, neurological exam, and head CT scans to characterize each patient’s disease status. We screened our patient cohort for mutations in SLC20A2. Twelve novel (nonsense, deletions, missense, and splice site) potentially pathogenic variants, one synonymous variant, and one previously reported mutation were identified in 13 families. Variants predicted to be deleterious cosegregated with disease in five families. Three families showed nonsegregation with clinical disease of such variants, but retrospective review of clinical and neuroimaging data strongly suggested previous misclassification. Overall, mutations in SLC20A2 account for as many as 41 % of our familial IBGC cases. Our screen in a large series expands the catalog of SLC20A2 mutations identified to date and demonstrates that mutations in SLC20A2 are a major cause of familial IBGC. Non-perfect segregation patterns of predicted deleterious variants highlight the challenges of phenotypic assessment in this condition with highly variable clinical presentation. PMID:23334463

Availability simulation software adaptation to the IFMIF accelerator facility RAMI analyses

Energy Technology Data Exchange (ETDEWEB)

Bargalló, Enric, E-mail: enric.bargallo-font@upc.edu [Fusion Energy Engineering Laboratory (FEEL), Technical University of Catalonia (UPC) Barcelona-Tech, Barcelona (Spain); Sureda, Pere Joan [Fusion Energy Engineering Laboratory (FEEL), Technical University of Catalonia (UPC) Barcelona-Tech, Barcelona (Spain); Arroyo, Jose Manuel [Laboratorio Nacional de Fusión por Confinamiento Magnético – CIEMAT, Madrid (Spain); Abal, Javier; De Blas, Alfredo; Dies, Javier; Tapia, Carlos [Fusion Energy Engineering Laboratory (FEEL), Technical University of Catalonia (UPC) Barcelona-Tech, Barcelona (Spain); Mollá, Joaquín; Ibarra, Ángel [Laboratorio Nacional de Fusión por Confinamiento Magnético – CIEMAT, Madrid (Spain)

2014-10-15

Highlights: • The reason why IFMIF RAMI analyses needs a simulation is explained. • Changes, modifications and software validations done to AvailSim are described. • First IFMIF RAMI results obtained with AvailSim 2.0 are shown. • Implications of AvailSim 2.0 in IFMIF RAMI analyses are evaluated. - Abstract: Several problems were found when using generic reliability tools to perform RAMI (Reliability Availability Maintainability Inspectability) studies for the IFMIF (International Fusion Materials Irradiation Facility) accelerator. A dedicated simulation tool was necessary to model properly the complexity of the accelerator facility. AvailSim, the availability simulation software used for the International Linear Collider (ILC) became an excellent option to fulfill RAMI analyses needs. Nevertheless, this software needed to be adapted and modified to simulate the IFMIF accelerator facility in a useful way for the RAMI analyses in the current design phase. Furthermore, some improvements and new features have been added to the software. This software has become a great tool to simulate the peculiarities of the IFMIF accelerator facility allowing obtaining a realistic availability simulation. Degraded operation simulation and maintenance strategies are the main relevant features. In this paper, the necessity of this software, main modifications to improve it and its adaptation to IFMIF RAMI analysis are described. Moreover, first results obtained with AvailSim 2.0 and a comparison with previous results is shown.

Availability simulation software adaptation to the IFMIF accelerator facility RAMI analyses

International Nuclear Information System (INIS)

Bargalló, Enric; Sureda, Pere Joan; Arroyo, Jose Manuel; Abal, Javier; De Blas, Alfredo; Dies, Javier; Tapia, Carlos; Mollá, Joaquín; Ibarra, Ángel

2014-01-01

Highlights: • The reason why IFMIF RAMI analyses needs a simulation is explained. • Changes, modifications and software validations done to AvailSim are described. • First IFMIF RAMI results obtained with AvailSim 2.0 are shown. • Implications of AvailSim 2.0 in IFMIF RAMI analyses are evaluated. - Abstract: Several problems were found when using generic reliability tools to perform RAMI (Reliability Availability Maintainability Inspectability) studies for the IFMIF (International Fusion Materials Irradiation Facility) accelerator. A dedicated simulation tool was necessary to model properly the complexity of the accelerator facility. AvailSim, the availability simulation software used for the International Linear Collider (ILC) became an excellent option to fulfill RAMI analyses needs. Nevertheless, this software needed to be adapted and modified to simulate the IFMIF accelerator facility in a useful way for the RAMI analyses in the current design phase. Furthermore, some improvements and new features have been added to the software. This software has become a great tool to simulate the peculiarities of the IFMIF accelerator facility allowing obtaining a realistic availability simulation. Degraded operation simulation and maintenance strategies are the main relevant features. In this paper, the necessity of this software, main modifications to improve it and its adaptation to IFMIF RAMI analysis are described. Moreover, first results obtained with AvailSim 2.0 and a comparison with previous results is shown

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)

A mixed-method research to investigate the adoption of mobile devices and Web2.0 technologies among medical students and educators.

Science.gov (United States)

Fan, Si; Radford, Jan; Fabian, Debbie

2016-04-19

The past decade has witnessed the increasing adoption of Web 2.0 technologies in medical education. Recently, the notion of digital habitats, Web 2.0 supported learning environments, has also come onto the scene. While there has been initial research on the use of digital habitats for educational purposes, very limited research has examined the adoption of digital habitats by medical students and educators on mobile devices. This paper reports the Stage 1 findings of a two-staged study. The whole study aimed to develop and implement a personal digital habitat, namely digiMe, for medical students and educators at an Australian university. The first stage, however, examined the types of Web 2.0 tools and mobile devices that are being used by potential digiMe users, and reasons for their adoption. In this first stage of research, data were collected through a questionnaire and semi-structured interviews. Questionnaire data collected from 104 participants were analysed using the Predictive Analytics SoftWare (PASW). Frequencies, median and mean values were pursued. Kruskal Wallis tests were then performed to examine variations between views of different participant groups. Notes from the 6 interviews, together with responses to the open-ended section of the questionnaire, were analysed using the constructivist grounded theory approach, to generate key themes relevant to the adoption of Web 2.0 tools and mobile devices. The findings reflected the wide use of mobile devices, including both smart phones and computing tablets, by medical students and educators for learning, teaching and professional development purposes. Among the 22 types of Web 2.0 tools investigated, less than half of these tools were frequently used by the participants, this reflects the mismatch between users' desires and their actual practice. Age and occupation appeared to be the influential factors for their adoption. Easy access to information and improved communication are main purposes. This

Titanium K-Shell X-Ray Production from High Velocity Wire Arrays Implosions on the 20-MA Z Accelerator

International Nuclear Information System (INIS)

Apruzese, J.P.; Beg, F.N.; Clark, R.C.; Coverdale, C.A.; Davis, J.; Deeney, C.; Douglas, M.R.; Nash, T.J.; Ruiz-Comacho, J.; Spielman, R.B.; Struve, K.W.; Thornhill, J.W.; Whitney, K.G.

1999-01-01

The advent of the 20-MA Z accelerator [R.B. Spielman, C. Deeney, G.A. Chandler, et al., Phys. Plasmas 5, 2105, (1997)] has enabled implosions of large diameter, high-wire-number arrays of titanium to begin testing Z-pinch K-shell scaling theories. The 2-cm long titanium arrays, which were mounted on a 40-mm diameter, produced between 75±15 to 125±20 kJ of K-shell x-rays. Mass scans indicate that, as predicted, higher velocity implosions in the series produced higher x-ray yields. Spectroscopic analyses indicate that these high velocity implosions achieved peak electron temperatures from 2.7±0.1 to 3.2±0.2 keV and obtained a K-shell emission mass participation of up to 12%

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...

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.

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.

Microstructure analyses and thermoelectric properties of Ag1−xPb18Sb1+yTe20

International Nuclear Information System (INIS)

Perlt, S.; Höche, Th.; Dadda, J.; Müller, E.; Bauer Pereira, P.; Hermann, R.; Sarahan, M.; Pippel, E.; Brydson, R.

2012-01-01

This study reports microstructural investigations of long-term annealed Ag 1−x Pb m Sb 1+y Te 2+m (m=18, x=y=0, hereinafter referred to as AgPb 18 SbTe 20 ) (Lead–Antimony–Silver–Tellurium, LAST-18) as well as of Ag 1−x Pb 18 Sb 1+y Te 20 , i.e. Ag-deficient and Sb-excess LAST-18 (x≠0,y≠0), respectively. Two different length scales are explored. The micrometer scale was evaluated by SEM to analyze the volume fraction and the number of secondary phases as well as the impact of processing parameters on the homogeneity of bulk samples. For AgPb 18 SbTe 20 , site-specific FIB liftout of TEM lamellae from thermoelectrically characterized samples was accomplished to investigate the structure on the nanometer scale. High-resolution TEM and energy-filtered TEM were performed to reveal shape and size distribution of nanoprecipitates, respectively. A hypothesis concerning the structure–property relationship is set out within the frame of a gradient annealing experiment. This study is completed by results dealing with inhomogeneities on the micrometer scale of Ag 1−x Pb 18 Sb 1+y Te 20 and its electronic properties. Highlights: ► SEM and TEM microstructure investigation of long-term annealed AgPb 18 SbTe 20 . ► SEM and thermoelectric studies on Ag 1−x Pb 18 Sb 1+y Te 20 . ► Discussion concerning structure–property relationship in long-term annealed AgPb 18 SbTe 20 . ► Correlation between Ag 1−x Pb 18 Sb 1+y Te 20 microscale structure and electronic properties.

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.

Safety, efficacy, predictability and stability of laser in situ keratomileusis (LASIK) with a 1000-Hz scanning spot excimer laser.

Science.gov (United States)

Khoramnia, Ramin; Salgado, Josefina P; Wuellner, Christian; Donitzky, Christof; Lohmann, Chris P; Winkler von Mohrenfels, Christoph

2012-09-01

To evaluate the safety, efficacy, predictability and stability of laser in situ keratomileusis (LASIK) with a 1000-Hz scanning spot excimer laser (Concept System 1000; WaveLight GmbH, Erlangen, Germany). LASIK was performed on twenty eyes with myopia or myopic astigmatism (mean spherical equivalent refraction: -3.97±1.72 dioptres (D); mean cylinder: -0.84±0.77 D) using a microkeratome for flap creation and the Concept System 1000 for photoablation. Patients were examined preoperatively as well as 1, 3 and 6 months after the treatment. Manifest sphere and cylinder, uncorrected (UCDVA) and best corrected (BCDVA) distance visual acuity, corneal topography and pachymetry were analysed. We observed no adverse events that might have been associated with the use of a repetition rate of 1000 Hz. All eyes maintained or had improved BCDVA at 6 months after treatment when compared to preoperative values. Six months after LASIK, UCDVA was 20/20 or better in 85% and 20/25 or better in 100% of the eyes. The spherical equivalent refraction was within ±0.50 D in 95% of the eyes at 6 months after surgery. The refraction stayed stable over time; 95% of the eyes changedLASIK with the prototype 1000-Hz excimer laser was safe, efficient and predictable. The postoperative refraction was stable over time. There were no specific clinical side-effects that might be associated with the use of such a high repetition rate. © 2011 The Authors. Acta Ophthalmologica © 2011 Acta Ophthalmologica Scandinavica Foundation.

IntaRNA 2.0: enhanced and customizable prediction of RNA–RNA interactions

Science.gov (United States)

Mann, Martin; Wright, Patrick R.

2017-01-01

Abstract The IntaRNA algorithm enables fast and accurate prediction of RNA–RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA–RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage. PMID:28472523

LoopIng: a template-based tool for predicting the structure of protein loops.

KAUST Repository

Messih, Mario Abdel; Lepore, Rosalba; Tramontano, Anna

2015-01-01

) and significant enhancements for long loops (11-20 residues). The quality of the predictions is robust to errors that unavoidably affect the stem regions when these are modeled. The method returns a confidence score for the predicted template loops and has

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

Microbase2.0: A Generic Framework for Computationally Intensive Bioinformatics Workflows in the Cloud

OpenAIRE

Flanagan Keith; Nakjang Sirintra; Hallinan Jennifer; Harwood Colin; Hirt Robert P.; Pocock Matthew R.; Wipat Anil

2012-01-01

As bioinformatics datasets grow ever larger, and analyses become increasingly complex, there is a need for data handling infrastructures to keep pace with developing technology. One solution is to apply Grid and Cloud technologies to address the computational requirements of analysing high throughput datasets. We present an approach for writing new, or wrapping existing applications, and a reference implementation of a framework, Microbase2.0, for executing those applications using Grid and C...

Persistence of antibodies 20 y after vaccination with a combined hepatitis A and B vaccine

Science.gov (United States)

Van Damme, Pierre; Leroux-Roels, Geert; Suryakiran, P.; Folschweiller, Nicolas; Van Der Meeren, Olivier

2017-01-01

ABSTRACT Vaccination is the most effective and well-tolerated method of conferring long-term protection against hepatitis A and B viruses (HAV; HBV). Long-term studies are required to characterize the duration of protection and need for boosters. Following primary immunization of 150 and 157 healthy adults with 3-doses of combined hepatitis A/hepatitis B vaccine (HAB; Twinrix™, GSK Vaccines, Belgium) at 0-1-6 months in 2 separate studies, we measured vaccine-induced antibody persistence against HAV and HBV annually for 20 y (Study A: NCT01000324; Study B: NCT01037114). Subjects with circulating anti-HAV antibodies hepatitis B surface antigen hepatitis A and/or B vaccine dose (Havrix™/Engerix™-B, GSK Vaccines, Belgium). Applying the immunogenicity results from these studies, mathematical modeling predicted long-term persistence. After 20 y, 18 and 25 subjects in studies A and B, respectively, comprised the long-term according-to-protocol cohort for immunogenicity; 100% and 96.0% retained anti-HAV antibodies ≥ 15 mIU/mL, respectively; 94.4% and 92.0% had anti-HBs antibodies ≥ 10 mIU/mL, respectively. Between Years 16–20, 4 subjects who received a challenge dose of monovalent hepatitis A vaccine (N = 2) or hepatitis B vaccine (N = 2), all mounted a strong anamnestic response suggestive of immune memory despite low antibody levels. Mathematical modeling predicts that 40 y after vaccination ≥ 97% vaccinees will maintain anti-HAV ≥ 15 mIU/mL and ≥ 50% vaccinees will retain anti-HBs ≥ 10 mIU/mL. Immunogenicity data confirm that primary immunization with 3-doses of HAB induces persisting anti-HAV and anti-HBs specific antibodies in most adults for up to 20 y; mathematical modeling predicts even longer-term protection. PMID:28281907

Persistence of antibodies 20 y after vaccination with a combined hepatitis A and B vaccine.

Science.gov (United States)

Van Damme, Pierre; Leroux-Roels, Geert; Suryakiran, P; Folschweiller, Nicolas; Van Der Meeren, Olivier

2017-05-04

Vaccination is the most effective and well-tolerated method of conferring long-term protection against hepatitis A and B viruses (HAV; HBV). Long-term studies are required to characterize the duration of protection and need for boosters. Following primary immunization of 150 and 157 healthy adults with 3-doses of combined hepatitis A/hepatitis B vaccine (HAB; Twinrix™, GSK Vaccines, Belgium) at 0-1-6 months in 2 separate studies, we measured vaccine-induced antibody persistence against HAV and HBV annually for 20 y (Study A: NCT01000324; Study B: NCT01037114). Subjects with circulating anti-HAV antibodies B surface antigen B vaccine dose (Havrix™/Engerix™-B, GSK Vaccines, Belgium). Applying the immunogenicity results from these studies, mathematical modeling predicted long-term persistence. After 20 y, 18 and 25 subjects in studies A and B, respectively, comprised the long-term according-to-protocol cohort for immunogenicity; 100% and 96.0% retained anti-HAV antibodies ≥ 15 mIU/mL, respectively; 94.4% and 92.0% had anti-HBs antibodies ≥ 10 mIU/mL, respectively. Between Years 16-20, 4 subjects who received a challenge dose of monovalent hepatitis A vaccine (N = 2) or hepatitis B vaccine (N = 2), all mounted a strong anamnestic response suggestive of immune memory despite low antibody levels. Mathematical modeling predicts that 40 y after vaccination ≥ 97% vaccinees will maintain anti-HAV ≥ 15 mIU/mL and ≥ 50% vaccinees will retain anti-HBs ≥ 10 mIU/mL. Immunogenicity data confirm that primary immunization with 3-doses of HAB induces persisting anti-HAV and anti-HBs specific antibodies in most adults for up to 20 y; mathematical modeling predicts even longer-term protection.

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.

Quality of courses evaluated by 'predictions' rather than opinions: Fewer respondents needed for similar results.

Science.gov (United States)

Cohen-Schotanus, Janke; Schönrock-Adema, Johanna; Schmidt, Henk G

2010-01-01

A well-known problem with student surveys is a too low response rate. Experiences with predicting electoral outcomes, which required much smaller sample sizes, inspired us to adopt a similar approach to course evaluation. We expected that having respondents estimate the average opinions of their peers required fewer respondents for comparable outcomes than giving own opinions. Two course evaluation studies were performed among successive first-year medical students (N = 380 and 450, respectively). Study 1: Half the cohort gave opinions on nine questions, while the other half predicted the average outcomes. A prize was offered for the three best predictions (motivational remedy). Study 2: Half the cohort gave opinions, a quarter made predictions without a prize and a quarter made predictions with previous year's results as prior knowledge (cognitive remedy). The numbers of respondents required for stable outcomes were determined following an iterative process. Differences between numbers of respondents required and between average scores were analysed with ANOVA. In both studies, the prediction conditions required significantly fewer respondents (p < 0.001) for comparable outcomes. The informed prediction condition required the fewest respondents (N < 20). Problems with response rates can be reduced by asking respondents to predict evaluation outcomes rather than giving opinions.

The IntFOLD server: an integrated web resource for protein fold recognition, 3D model quality assessment, intrinsic disorder prediction, domain prediction and ligand binding site prediction.

Science.gov (United States)

Roche, Daniel B; Buenavista, Maria T; Tetchner, Stuart J; McGuffin, Liam J

2011-07-01

The IntFOLD server is a novel independent server that integrates several cutting edge methods for the prediction of structure and function from sequence. Our guiding principles behind the server development were as follows: (i) to provide a simple unified resource that makes our prediction software accessible to all and (ii) to produce integrated output for predictions that can be easily interpreted. The output for predictions is presented as a simple table that summarizes all results graphically via plots and annotated 3D models. The raw machine readable data files for each set of predictions are also provided for developers, which comply with the Critical Assessment of Methods for Protein Structure Prediction (CASP) data standards. The server comprises an integrated suite of five novel methods: nFOLD4, for tertiary structure prediction; ModFOLD 3.0, for model quality assessment; DISOclust 2.0, for disorder prediction; DomFOLD 2.0 for domain prediction; and FunFOLD 1.0, for ligand binding site prediction. Predictions from the IntFOLD server were found to be competitive in several categories in the recent CASP9 experiment. The IntFOLD server is available at the following web site: http://www.reading.ac.uk/bioinf/IntFOLD/.

Surface Temperature Prediction of a Bridge for Tactical Decision Aide Modelling

Science.gov (United States)

1988-01-01

Roadway And Piling Surface Temperature Predictions (No Radiosity Incident on Lower Surface) Compared to Temperature Estimates...Heat gained from water = Heat lost by long wave radiosity radiation. Algebraically, with the conduction term expressed in the same manner as for...5 10 15 20 LOCAL TIME (hrs.) Figure 8. Effect of No Radiosity Incident on Lower Surface. 37 U 8a M OT U% 60-- 0- o.. 20- 0- 1 T I I 5 10 15 20 LOCAL

IntaRNA 2.0: enhanced and customizable prediction of RNA-RNA interactions.

Science.gov (United States)

Mann, Martin; Wright, Patrick R; Backofen, Rolf

2017-07-03

The IntaRNA algorithm enables fast and accurate prediction of RNA-RNA hybrids by incorporating seed constraints and interaction site accessibility. Here, we introduce IntaRNAv2, which enables enhanced parameterization as well as fully customizable control over the prediction modes and output formats. Based on up to date benchmark data, the enhanced predictive quality is shown and further improvements due to more restrictive seed constraints are highlighted. The extended web interface provides visualizations of the new minimal energy profiles for RNA-RNA interactions. These allow a detailed investigation of interaction alternatives and can reveal potential interaction site multiplicity. IntaRNAv2 is freely available (source and binary), and distributed via the conda package manager. Furthermore, it has been included into the Galaxy workflow framework and its already established web interface enables ad hoc usage. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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....

Hazard Forecasting by MRI: A Prediction Algorithm of the First Kind

Science.gov (United States)

Lomnitz, C.

2003-12-01

Seismic gaps do not tell us when and where the next earthquake is due. We present new results on limited earthquake hazard prediction at plate boundaries. Our algorithm quantifies earthquake hazard in seismic gaps. The prediction window found for M7 is on the order of 50 km by 20 years (Lomnitz, 1996a). The earth is unstable with respect to small perturbations of the initial conditions. A prediction of the first kind is an estimate of the time evolution of a complex system with fixed boundary conditions in response to changes in the initial state, for example, weather prediction (Edward Lorenz, 1975; Hasselmann, 2002). We use the catalog of large world earthquakes as a proxy for the initial conditions. The MRI algorithm simulates the response of the system to updating the catalog. After a local stress transient dP the entropy decays as (grad dP)2 due to transient flows directed toward the epicenter. Healing is the thermodynamic process which resets the state of stress. It proceeds as a power law from the rupture boundary inwards, as in a wound. The half-life of a rupture is defined as the healing time which shrinks the size of a scar by half. Healed segments of plate boundary can rupture again. From observations in Chile, Mexico and Japan we find that the half-life of a seismic rupture is about 20 years, in agreement with seismic gap observations. The moment ratio MR is defined as the contrast between the cumulative regional moment release and the local moment deficiency at time t along the plate boundary. The procedure is called MRI. The findings: (1) MRI works; (2) major earthquakes match prominent peaks in the MRI graph; (3) important events (Central Chile 1985; Mexico 1985; Kobe 1995) match MRI peaks which began to emerge 10 to 20 years before the earthquake; (4) The emergence of peaks in MRI depends on earlier ruptures that occurred, not adjacent to but at 10 to 20 fault lengths from the epicentral region, in agreement with triggering effects. The hazard

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.

RSIC after 20 years: a look back and a look ahead

International Nuclear Information System (INIS)

Maskewitz, B.F.; Roussin, R.W.; Trubev, D.K.

1983-01-01

On the occasion of RSIC's 20th anniversary year, this review includes highlights and lessons learned. In June 1963, the first RSIC Newsletter was published, and information analyses procedures and practices were initiated. Evidence indicates that RSIC served for 20 years as the focal point for the exchange and transfer of radiation transport technology and contributed to the advancement of the state of the art. The original concept is found to be sound: operate an information analysis center by collecting, organizing, evaluating, and analyzing all relevant information and making the information available in a form readily useful to scientists and engineers. Computing technology, a computer-based literature information system, and an advisory service remain important elements of the center. Continuing interaction between the center, developers, and users of information products and services has been a key to RSIC success. A look to the future reflects optimism

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

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

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…

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

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

Collaborative Learning with Web 2.0 Tools: Analysing Malaysian Students' Perceptions and Peer Interaction

Science.gov (United States)

Leow, Fui Theng; Neo, Mai

2015-01-01

Today, ICT, web resources and multimedia contents have become prevalent in Malaysian university classrooms; hence, the learning approaches need to be redesigned for enabling students to use these technologies in co-constructing new meaning. This study analyses student's perception and their peer interaction in the constructivist-collaborative…

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/

A study on two phase flows of linear compressors for the prediction of refrigerant leakage

International Nuclear Information System (INIS)

Hwang, Il Sun; Lee, Young Lim; Oh, Won Sik; Park, Kyeong Bae

2015-01-01

Usage of linear compressors is on the rise due to their high efficiency. In this paper, leakage of a linear compressor has been studied through numerical analysis and experiments. First, nitrogen leakage for a stagnant piston with fixed cylinder pressure as well as for a moving piston with fixed cylinder pressure was analyzed to verify the validity of the two-phase flow analysis model. Next, refrigerant leakage of a linear compressor in operation was finally predicted through 3-dimensional unsteady, two phase flow CFD (Computational fluid dynamics). According to the research results, the numerical analyses for the fixed cylinder pressure models were in good agreement with the experimental results. The refrigerant leakage of the linear compressor in operation mainly occurred through the oil exit and the leakage became negligible after about 0.4s following operation where the leakage became lower than 2.0x10 -4 kg/s.

The influence of bilirubin, haemolysis and turbidity on 20 analytical tests performed on automatic analysers. Results of an interlaboratory study.

Science.gov (United States)

Grafmeyer, D; Bondon, M; Manchon, M; Levillain, P

1995-01-01

The director of a laboratory has to be sure to give out reliable results for routine tests on automatic analysers regardless of the clinical context. However, he may find hyperbilirubinaemia in some circumstances, parenteral nutrition causing turbidity in others, and haemolysis occurring if sampling is difficult. For this reason, the Commission for Instrumentation of the Société Française de Biologie Clinique (SFBC) (president Alain Feuillu) decided to look into "visible" interferences--bilirubin, haemolysis and turbidity--and their effect on 20 major tests: 13 substrates/chemistries: albumin, calcium, cholesterol, creatinine, glucose, iron, magnesium, phosphorus, total bilirubin, total proteins, triacylglycerols, uric acid, urea, and 7 enzymatic activities: alkaline phosphatase, alanine aminotransferase, alpha-amylase, aspartate aminotransferase, creatine kinase, gamma-glutamyl transferase and lactate dehydrogenase measured on 15 automatic analysers representative of those found on the French market (Astra 8, AU 510, AU 5010, AU 5000, Chem 1, CX 7, Dax 72, Dimension, Ektachem, Hitachi 717, Hitachi 737, Hitachi 747, Monarch, Open 30, Paramax, Wako 30 R) and to see how much they affect the accuracy of results under routine conditions in the laboratory. The study was carried out following the SFBC protocol for the validation of techniques using spiked plasma pools with bilirubin, ditauro-bilirubin, haemoglobin (from haemolysate) and Intralipid (turbidity). Overall, the following results were obtained: haemolysis affects tests the most often (34.5% of cases); total bilirubin interferes in 21.7% of cases; direct bilirubin and turbidity seem to interfere less at around 17%. The different tests are not affected to the same extent; enzyme activity is hardly affected at all; on the other hand certain major tests are extremely sensitive, increasingly so as we go through the following: creatinine (interference of bilirubin), triacylglycerols (interference of bilirubin and

Reliability and validity of a 20-s alternative to the wingate anaerobic test in team sport male athletes.

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Ahmed Attia

Full Text Available The intent of this study was to evaluate relative and absolute reliability of the 20-s anaerobic test (WAnT20 versus the WAnT30 and to verify how far the various indices of the 30-s Wingate anaerobic test (WAnT30 could be predicted from the WAnT20 data in male athletes. The participants were Exercise Science majors (age: 21.5±1.6 yrs, stature: 0.183±0.08 m, body mass: 81.2±10.9 kg who participated regularly in team sports. In Phase I, 41 participants performed duplicate WAnT20 and WAnT30 tests to assess reliability. In Phase II, 31 participants performed one trial each of the WAnT20 and WAnT30 to determine the ability of the WAnT20 to predict components of the WAnT30. In Phase III, 31 participants were used to cross-validate the prediction equations developed in Phase II. Respective intra-class correlation coefficients (ICC for peak power output (PPO (ICC = 0.98 and 0.95 and mean power output (MPO (ICC 0.98 and 0.90 did not differ significantly between WAnT20 and WAnT30. ICCs for minimal power output (POmin and fatigue index (FI were poor for both tests (range 0.53 to 0.76. Standard errors of the means (SEM for PPO and MPO were less than their smallest worthwhile changes (SWC in both tests; however, POmin and FI values were "marginal," with SEM values greater than their respective SWCs for both tests values. Stepwise regression analysis showed that MPO had the highest coefficient of predictability (R = 0.97, with POmin and FI considerable lower (R = 0.71 and 0.41 respectively. Cross-validation showed insignificant bias with limits of agreement of 0.99±1.04, 6.5±92.7 W, and 1.6±9.8% between measured and predicted MPO, POmin, and FI, respectively. WAnT20 offers a reliable and valid test of leg anaerobic power in male athletes and could replace the classic WAnT30.

Angular analyses of $b \\to s \\mu^+ \\mu^-$ transitions at CMS

CERN Document Server

Wang, Dayong

2018-01-01

The flavour changing neutral current decays can be interesting probes for searching for new physics. Angular distributions of $b \\to s \\ell^+ \\ell^-$ transition processes of both $\\mathrm{B}^0 \\to \\mathrm{K}^{*0} \\mu^ +\\mu^-$ and $\\mathrm{B}^{+} \\to \\mathrm{K}^{+} \\mu^+\\mu^-$ are studied using a sample of proton-proton collisions at $\\sqrt{s} = 8~\\mathrm{TeV}$ collected with the CMS detector at the LHC, corresponding to an integrated luminosity of $20.5~\\mathrm{fb}^{-1}$. Angular analyses are performed to determine $P_1$ and $P_5'$ angular parameters for $\\mathrm{B}^0 \\to \\mathrm{K}^{*0} \\mu^ +\\mu^-$ and $A_{FB}$ and $F_{H}$ parameters for $\\mathrm{B}^{+} \\to \\mathrm{K}^{+} \\mu^+\\mu^-$, all as functions of the dimuon invariant mass squared. The $P_5'$ parameter is of particular interest due to recent measurements that indicate a potential discrepancy with the standard model. All the measurements are consistent with the standard model predictions. Efforts with more channels and more coming data will be con...

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,...

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

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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

Change of CD20 Expression in Diffuse Large B-Cell Lymphoma Treated with Rituximab, an Anti-CD20 Monoclonal Antibody: A Study of the Osaka Lymphoma Study Group

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Naoki Wada

2009-10-01

Full Text Available Change of CD20 expression was examined in cases of diffuse large B-cell lymphoma (DLBCL. CD20 expression after treatment with anti-CD20 antibody (rituximab, Rx for DLBCL was examined in 23 cases who received serial biopsy by immunohistochemistry (IHC and flow cytometry (FCM. CD20– by IHC and/or FCM was defined as CD20–. Four cases were CD20– at initial biopsy but became CD20+ after chemotherapy with Rx (CH-R (group A. Recurrent tumors in three group A cases became resistant to CH-R. Initial and recurrent tumors were CD20+ before and after CH-R in 17 cases (group B. Tumors before CH-R were CD20– in two cases (group C and continued to be CD20– in one and turned CD20+ in the other with survival time after the relapse of 8 and 23 months, respectively. Evaluation of CD20 expression with immunohistochemical and flow cytometric methods is used for the prediction of responsiveness of relapsed DLBCL for CH-R.

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…

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.

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

Virtual screening of cocrystal formers for CL-20

Science.gov (United States)

Zhou, Jun-Hong; Chen, Min-Bo; Chen, Wei-Ming; Shi, Liang-Wei; Zhang, Chao-Yang; Li, Hong-Zhen

2014-08-01

According to the structure characteristics of 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20) and the kinetic mechanism of the cocrystal formation, the method of virtual screening CL-20 cocrystal formers by the criterion of the strongest intermolecular site pairing energy (ISPE) was proposed. In this method the strongest ISPE was thought to determine the first step of the cocrystal formation. The prediction results for four sets of common drug molecule cocrystals by this method were compared with those by the total ISPE method from the reference (Musumeci et al., 2011), and the experimental results. This method was then applied to virtually screen the CL-20 cocrystal formers, and the prediction results were compared with the experimental results.

The Bacillus subtilis Conjugative Plasmid pLS20 Encodes Two Ribbon-Helix-Helix Type Auxiliary Relaxosome Proteins That Are Essential for Conjugation

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Andrés Miguel-Arribas

2017-11-01

Full Text Available Bacterial conjugation is the process by which a conjugative element (CE is transferred horizontally from a donor to a recipient cell via a connecting pore. One of the first steps in the conjugation process is the formation of a nucleoprotein complex at the origin of transfer (oriT, where one of the components of the nucleoprotein complex, the relaxase, introduces a site- and strand specific nick to initiate the transfer of a single DNA strand into the recipient cell. In most cases, the nucleoprotein complex involves, besides the relaxase, one or more additional proteins, named auxiliary proteins, which are encoded by the CE and/or the host. The conjugative plasmid pLS20 replicates in the Gram-positive Firmicute bacterium Bacillus subtilis. We have recently identified the relaxase gene and the oriT of pLS20, which are separated by a region of almost 1 kb. Here we show that this region contains two auxiliary genes that we name aux1LS20 and aux2LS20, and which we show are essential for conjugation. Both Aux1LS20 and Aux2LS20 are predicted to contain a Ribbon-Helix-Helix DNA binding motif near their N-terminus. Analyses of the purified proteins show that Aux1LS20 and Aux2LS20 form tetramers and hexamers in solution, respectively, and that they both bind preferentially to oriTLS20, although with different characteristics and specificities. In silico analyses revealed that genes encoding homologs of Aux1LS20 and/or Aux2LS20 are located upstream of almost 400 relaxase genes of the RelLS20 family (MOBL of relaxases. Thus, Aux1LS20 and Aux2LS20 of pLS20 constitute the founding member of the first two families of auxiliary proteins described for CEs of Gram-positive origin.

The Bacillus subtilis Conjugative Plasmid pLS20 Encodes Two Ribbon-Helix-Helix Type Auxiliary Relaxosome Proteins That Are Essential for Conjugation.

Science.gov (United States)

Miguel-Arribas, Andrés; Hao, Jian-An; Luque-Ortega, Juan R; Ramachandran, Gayetri; Val-Calvo, Jorge; Gago-Córdoba, César; González-Álvarez, Daniel; Abia, David; Alfonso, Carlos; Wu, Ling J; Meijer, Wilfried J J

2017-01-01

Bacterial conjugation is the process by which a conjugative element (CE) is transferred horizontally from a donor to a recipient cell via a connecting pore. One of the first steps in the conjugation process is the formation of a nucleoprotein complex at the origin of transfer ( oriT ), where one of the components of the nucleoprotein complex, the relaxase, introduces a site- and strand specific nick to initiate the transfer of a single DNA strand into the recipient cell. In most cases, the nucleoprotein complex involves, besides the relaxase, one or more additional proteins, named auxiliary proteins, which are encoded by the CE and/or the host. The conjugative plasmid pLS20 replicates in the Gram-positive Firmicute bacterium Bacillus subtilis . We have recently identified the relaxase gene and the oriT of pLS20, which are separated by a region of almost 1 kb. Here we show that this region contains two auxiliary genes that we name aux1 LS20 and aux2 LS20 , and which we show are essential for conjugation. Both Aux1 LS20 and Aux2 LS20 are predicted to contain a Ribbon-Helix-Helix DNA binding motif near their N-terminus. Analyses of the purified proteins show that Aux1 LS20 and Aux2 LS20 form tetramers and hexamers in solution, respectively, and that they both bind preferentially to oriT LS20 , although with different characteristics and specificities. In silico analyses revealed that genes encoding homologs of Aux1 LS20 and/or Aux2 LS20 are located upstream of almost 400 relaxase genes of the Rel LS20 family (MOB L ) of relaxases. Thus, Aux1 LS20 and Aux2 LS20 of pLS20 constitute the founding member of the first two families of auxiliary proteins described for CEs of Gram-positive origin.

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

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.

Incidence, Mortality, and Predictive Factors of Hepatocellular Carcinoma in Primary Biliary Cirrhosis

Directory of Open Access Journals (Sweden)

Kenichi Hosonuma

2013-01-01

Full Text Available Background. The study aims to analyze in detail the incidence, mortality using the standardized incidence ratio (SIR, and standardized mortality ratio (SMR of hepatocellular carcinoma (HCC in primary biliary cirrhosis (PBC, because no large case studies have focused on the detailed statistical analysis of them in Asia. Methods. The study cohorts were consecutively diagnosed at Gunma University and its affiliated hospitals. Age- or sex-specific annual cancer incidence and deaths were obtained from Japanese Cancer Registry and Death Registry as a reference for the comparison of SIR or SMR of HCC. Moreover, univariate analyses and multivariate analyses were performed to clarify predictive factors for the incidence of HCC. Results. The overall 179 patients were followed up for a median of 97 months. HCC had developed in 13 cases. SIR for HCC was 11.6 (95% confidence interval (CI, 6.2–19.8 and SMR for HCC was 11.2 (95% CI, 5.4–20.6 in overall patients. The serum albumin levels were a predictive factor for the incidence of HCC in overall patients. Conclusions. The incidence and mortality of HCC in PBC patients were significantly higher than those in Japanese general population. PBC patients with low serum albumin levels were populations at high risk for HCC.

Re-experiencing phenomena following a disaster: The long-term predictive role of intrusion symptoms in the development of post-trauma depression and anxiety.

Science.gov (United States)

Lawrence-Wood, Ellie; Van Hooff, Miranda; Baur, Jenelle; McFarlane, Alexander C

2016-01-15

Contention in the literature regarding the diagnostic utility of intrusion symptoms highlights that they have high sensitivity but low specificity in predicting PTSD. They are highly prevalent following a range of traumatic events, and across a range of disorders. The prevalence of intrusion symptoms in the absence of PTSD suggests their relevance to the development of other psychopathology. Therefore, the predictive role of intrusion symptoms for other post-trauma psychopathology was examined using data from an epidemiological, longitudinal sample of adults recruited in childhood. From 5 phases of data collection for this sample, these analyses focused on the 20 year and 28 year follow-ups (n=583). Lifetime exposure to trauma was assessed using a modified set of 10 Criterion-A events from the Composite International Diagnostic Interview (CIDI), with PTSD assessed in reference to a self-nominated worst lifetime event, and other DSM-IV disorder also assessed using the CIDI. Results showed that the presence of intrusion symptoms without PTSD at the 20 year follow-up was predictive of increased risk at 28 years for depressive but not anxiety disorders. There was limited psychopathology in the sample, reducing the power to examine many individual disorders. Furthermore, trauma history and psychiatric symptoms were retrospectively reported, introducing the possibility of recall bias. Together the findings suggest that intrusion symptoms may play an aetiological role in the development and/or maintenance of disorders other than PTSD. Copyright © 2015 Elsevier B.V. All rights reserved.

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

Connecting clinical and actuarial prediction with rule-based methods.

Science.gov (United States)

Fokkema, Marjolein; Smits, Niels; Kelderman, Henk; Penninx, Brenda W J H

2015-06-01

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 methods for clinical practice. We argue that rule-based methods may be more useful than the linear main effect models usually employed in prediction studies, from a data and decision analytic as well as a practical perspective. In addition, decision rules derived with rule-based methods can be represented as fast and frugal trees, which, unlike main effects models, can be used in a sequential fashion, reducing the number of cues that have to be evaluated before making a prediction. We illustrate the usability of rule-based methods by applying RuleFit, an algorithm for deriving decision rules for classification and regression problems, to a dataset on prediction of the course of depressive and anxiety disorders from Penninx et al. (2011). The RuleFit algorithm provided a model consisting of 2 simple decision rules, requiring evaluation of only 2 to 4 cues. Predictive accuracy of the 2-rule model was very similar to that of a logistic regression model incorporating 20 predictor variables, originally applied to the dataset. In addition, the 2-rule model required, on average, evaluation of only 3 cues. Therefore, the RuleFit algorithm appears to be a promising method for creating decision tools that are less time consuming and easier to apply in psychological practice, and with accuracy comparable to traditional actuarial methods. (c) 2015 APA, all rights reserved).

Amorphous-to-Cu51Zr14 phase transformation in Cu60Ti20Zr20 alloy

International Nuclear Information System (INIS)

Cao, Q P; Zhou, Y H; Horsewell, A; Jiang, J Z

2003-01-01

The kinetics of an amorphous-to-Cu 51 Zr 14 phase transformation in an as-cast Cu 60 Ti 20 Zr 20 rod have been investigated by differential scanning calorimetry. The relative volume fractions of the transferred crystalline phase as a function of annealing time, obtained at 713, 716, 723, 728, and 733 K, have been analysed in detail using 14 nucleation and growth models together with the JMA model. A time-dependent nucleation process is revealed. A steady-state nucleation rate of the order of 10 22 - 10 23 nuclei m -3 s -1 in the temperature range 713-733 K and an activation energy of the order of 550 kJmol -1 for the phase transformation in the as-cast Cu 60 Ti 20 Zr 20 rod were detected, for which some possible reasons are suggested

Prediction of reported consumption of selected fat-containing foods.

Science.gov (United States)

Tuorila, H; Pangborn, R M

1988-10-01

A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

International Nuclear Information System (INIS)

Joseph, A; Herrera, D; Hijal, T; Kildea, J; Hendren, L; Leung, A; Wainberg, J; Sawaf, M; Gorshkov, M; Maglieri, R; Keshavarz, M

2016-01-01

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Energy Technology Data Exchange (ETDEWEB)

Joseph, A; Herrera, D; Hijal, T; Kildea, J [McGill University Health Centre, Montreal, Quebec (Canada); Hendren, L; Leung, A; Wainberg, J; Sawaf, M; Gorshkov, M; Maglieri, R; Keshavarz, M [McGill University, Montreal, Quebec (Canada)

2016-06-15

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes

The Use of Web 2.0 Tools by Students in Learning and Leisure Contexts: A Study in a Portuguese Institution of Higher Education

Science.gov (United States)

Costa, Carolina; Alvelos, Helena; Teixeira, Leonor

2016-01-01

This study analyses and compares the use of Web 2.0 tools by students in both learning and leisure contexts. Data were collected based on a questionnaire applied to 234 students from the University of Aveiro (Portugal) and the results were analysed by using descriptive analysis, paired samples t-tests, cluster analyses and Kruskal-Wallis tests.…

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...

Ultrastructural analyses of blood capillaries of ovary of 20-days albino rats foetus under their irradiation in different periods of embryogenesis

International Nuclear Information System (INIS)

Ablekovskaya, O.N.; Amvros'ev, A.P.

1999-01-01

The character and direction of structural transformations of blood capillaries of micro circulatory channel of 20-days white rat foetus in normal conditions and after single external 0,5 Gy dose irradiation by 10 and 14 days of embryogenesis were examined. Electron-microscopical, stereo logical and statistical analyses were used. The peculiarities of reactions of hemo capillaries and their cell structure to gamma-rays action in embryogenesis were revealed. It was shown the increase of diameters of capillaries, extension of section area of cytoplasm of endotheliocytes, diminution the size of nuclei of these cells. Polyploid endotheliocytes were found in the experimental conditions. Prenatal acute irradiation in low doses leaded to reduction of the number of microvessels and mitochondria in cytoplasm of cells of blood capillaries in ovary of rat foetus. These results revealed that low dose ionizing radiation changed the morphological expression of important synthetic, transport and energy processes in capillary cells of ovary in fetal period of ontogenesis

Multipinhole collimator with 20 apertures for a brain SPECT application

Energy Technology Data Exchange (ETDEWEB)

Lee, Tzu-Cheng; Ellin, Justin R.; Shrestha, Uttam; Seo, Youngho, E-mail: youngho.seo@ucsf.edu [Physics Research Laboratory, Department of Radiology and Biomedical Imaging, University of California, San Francisco, California 94107 (United States); Huang, Qiu [School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030 (China); Gullberg, Grant T. [Department of Radiotracer Development and Imaging Technology, Life Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California 94702 (United States)

2014-11-01

Purpose: Several new technologies for single photon emission computed tomography (SPECT) instrumentation with parallel-hole collimation have been proposed to improve detector sensitivity and signal collection efficiency. Benefits from improved signal efficiency include shorter acquisition times and lower dose requirements. In this paper, the authors show a possibility of over an order of magnitude enhancement in photon detection efficiency (from 7.6 × 10{sup −5} to 1.6 × 10{sup −3}) for dopamine transporter (DaT) imaging of the striatum over the conventional SPECT parallel-hole collimators by use of custom-designed 20 multipinhole (20-MPH) collimators with apertures of 0.75 cm diameter. Methods: Quantifying specific binding ratio (SBR) of {sup 123}I-ioflupane or {sup 123}I-iometopane’s signal at the striatal region is a common brain imaging method to confirm the diagnosis of the Parkinson’s disease. The authors performed imaging of a striatal phantom filled with aqueous solution of I-123 and compared camera recovery ratios of SBR acquired between low-energy high-resolution (LEHR) parallel-hole collimators and 20-MPH collimators. Results: With only two-thirds of total acquisition time (20 min against 30 min), a comparable camera recovery ratio of SBR was achieved using 20-MPH collimators in comparison to that from the LEHR collimator study. Conclusions: Their systematic analyses showed that the 20-MPH collimator could be a promising alternative for the DaT SPECT imaging for brain over the traditional LEHR collimator, which could give both shorter scan time and improved diagnostic accuracy.

A NEW METHOD FOR PREDICTING SURVIVAL AND ESTIMATING UNCERTAINTY IN TRAUMA PATIENTS

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V. G. Schetinin

2017-01-01

Full Text Available The Trauma and Injury Severity Score (TRISS is the current “gold” standard of screening patient’s condition for purposes of predicting survival probability. More than 40 years of TRISS practice revealed a number of problems, particularly, 1 unexplained fluctuation of predicted values caused by aggregation of screening tests, and 2 low accuracy of uncertainty intervals estimations. We developed a new method made it available for practitioners as a web calculator to reduce negative effect of factors given above. The method involves Bayesian methodology of statistical inference which, being computationally expensive, in theory provides most accurate predictions. We implemented and tested this approach on a data set including 571,148 patients registered in the US National Trauma Data Bank (NTDB with 1–20 injuries. These patients were distributed over the following categories: (1 174,647 with 1 injury, (2 381,137 with 2–10 injuries, and (3 15,364 with 11–20 injuries. Survival rates in each category were 0.977, 0.953, and 0.831, respectively. The proposed method has improved prediction accuracy by 0.04%, 0.36%, and 3.64% (p-value <0.05 in the categories 1, 2, and 3, respectively. Hosmer-Lemeshow statistics showed a significant improvement of the new model calibration. The uncertainty 2σ intervals were reduced from 0.628 to 0.569 for patients of the second category and from 1.227 to 0.930 for patients of the third category, both with p-value <0.005. The new method shows the statistically significant improvement (p-value <0.05 in accuracy of predicting survival and estimating the uncertainty intervals. The largest improvement has been achieved for patients with 11–20 injuries. The method is available for practitioners as a web calculator http://www.traumacalc.org.

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...

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…

Tensor analysing power T{sub 2}0 in inelastic (d, d`) X scattering at 0{sup 0} on {sup 1}H and {sup 12}C from 4.5 to 9.0 GeV/c

Energy Technology Data Exchange (ETDEWEB)

Azhgirej, L S; Chernykh, E V [Laboratory of High Energies, Joint Institute for Nuclear Research, Dubna (Russian Federation); Kobushkin, A P [Institute of Theoretical Physics, Ukrainian Academy of Sciences, Kiev (Ukraine); and others

1998-12-01

Tensor analysing power T{sub 20} for inelastic (d, d`) X reaction at deuteron momentum from 4.2 to 9 GeV/c is presented. It is observed that T{sub 20} taken as a function of the four-momentum transfer squared t demonstrates an approximate scaling; its absolute value is small at |t| <{approx_equal} (0.05 - 0.1) GeV{sup 2}/c{sup 2} and has a maximum at -t {approx_equal}0.3 GeV{sup 2}/c{sup 2}. No significant dependence on the type of the target was observed 10 refs., 4 figs., 4 tabs.

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.

Hot Deformation Behavior and a Two-Stage Constitutive Model of 20Mn5 Solid Steel Ingot during Hot Compression

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Min Liu

2018-03-01

Full Text Available 20Mn5 steel is widely used in the manufacture of heavy hydro-generator shaft forging due to its strength, toughness, and wear resistance. However, the hot deformation and recrystallization behaviors of 20Mn5 steel compressed under a high temperature were not studied. For this article, hot compression experiments under temperatures of 850–1200 °C and strain rates of 0.01 s−1–1 s−1 were conducted using a Gleeble-1500D thermo-mechanical simulator. Flow stress-strain curves and microstructure after hot compression were obtained. Effects of temperature and strain rate on microstructure are analyzed. Based on the classical stress-dislocation relationship and the kinetics of dynamic recrystallization, a two-stage constitutive model is developed to predict the flow stress of 20Mn5 steel. Comparisons between experimental flow stress and predicted flow stress show that the predicted flow stress values are in good agreement with the experimental flow stress values, which indicates that the proposed constitutive model is reliable and can be used for numerical simulation of hot forging of 20Mn5 solid steel ingot.

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.

Physiological and enzymatic analyses of pineapple subjected to ionizing radiation

International Nuclear Information System (INIS)

Silva, Josenilda Maria da; Silva, Juliana Pizarro; Spoto, Marta Helena Fillet

2007-01-01

The physiological and enzymatic post-harvest characteristics of the pineapple cultivar Smooth Cayenne were evaluated after the fruits were gamma-irradiated with doses of 100 and 150 Gy and the fruits were stored for 10, 20 and 30 days at 12 deg C (±1) and relative humidity of 85% (±5). Physiological and enzymatic analyses were made for each storage period to evaluate the alterations resulting from the application of ionizing radiation. Control specimens showed higher values of soluble pectins, total pectins, reducing sugars, sucrose and total sugars and lower values of polyphenyloxidase and polygalacturonase enzyme activities. All the analyses indicated that storage time is a significantly influencing factor. The 100 Gy dosage and 20-day storage period presented the best results from the standpoint of maturation and conservation of the fruits quality. (author)

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.)

PRmePRed: A protein arginine methylation prediction tool.

Directory of Open Access Journals (Sweden)

Pawan Kumar

Full Text Available Protein methylation is an important Post-Translational Modification (PTMs of proteins. Arginine methylation carries out and regulates several important biological functions, including gene regulation and signal transduction. Experimental identification of arginine methylation site is a daunting task as it is costly as well as time and labour intensive. Hence reliable prediction tools play an important task in rapid screening and identification of possible methylation sites in proteomes. Our preliminary assessment using the available prediction methods on collected data yielded unimpressive results. This motivated us to perform a comprehensive data analysis and appraisal of features relevant in the context of biological significance, that led to the development of a prediction tool PRmePRed with better performance. The PRmePRed perform reasonably well with an accuracy of 84.10%, 82.38% sensitivity, 83.77% specificity, and Matthew's correlation coefficient of 66.20% in 10-fold cross-validation. PRmePRed is freely available at http://bioinfo.icgeb.res.in/PRmePRed/.

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 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.

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.

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…

Predicting epileptic seizures in advance.

Directory of Open Access Journals (Sweden)

Negin Moghim

Full Text Available Epilepsy is the second most common neurological disorder, affecting 0.6-0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling, is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance.

Cross-species Analyses Unravel the Complexity of H3K27me3 and H4K20me3 in the Context of Neural Stem Progenitor Cells.

Science.gov (United States)

Rhodes, Christopher T; Sandstrom, Richard S; Huang, Shu-Wei Angela; Wang, Yufeng; Schotta, Gunnar; Berger, Mitchel S; Lin, Chin-Hsing Annie

2016-06-01

Neural stem progenitor cells (NSPCs) in the human subventricular zone (SVZ) potentially contribute to life-long neurogenesis, yet subtypes of glioblastoma multiforme (GBM) contain NSPC signatures that highlight the importance of cell fate regulation. Among numerous regulatory mechanisms, the post-translational methylations onto histone tails are crucial regulator of cell fate. The work presented here focuses on the role of two repressive chromatin marks tri-methylations on histone H3 lysine 27 (H3K27me3) and histone H4 lysine 20 (H4K20me3) in the adult NSPC within the SVZ. To best model healthy human NSPCs as they exist in vivo for epigenetic profiling of H3K27me3 and H4K20me3, we utilized NSPCs isolated from the adult SVZ of baboon brain ( Papio anubis ) with brain structure and genomic level similar to human. The putative role of H3K27me3 in normal NSPCs predominantly falls into the regulation of gene expression, cell cycle, and differentiation, whereas H4K20me3 is involved in DNA replication/repair, metabolism, and cell cycle. Using conditional knock-out mouse models to diminish Ezh2 and Suv4-20h responsible for H3K27me3 and H4K20me3, respectively, we found that both repressive marks have irrefutable function for cell cycle regulation in the NSPC population. While both EZH2/H3K27me3 and Suv4-20h/H4K20me3 have implication in cancers, our comparative genomics approach between healthy NSPCs and human GBM specimens revealed that substantial sets of genes enriched with H3K27me3 and H4K20me3 in the NSPCs are altered in the human GBM. In sum, our integrated analyses across species highlight important roles of H3K27me3 and H4K20me3 in normal and disease conditions in the context of NSPC.

Cross-species analyses unravel the complexity of H3K27me3 and H4K20me3 in the context of neural stem progenitor cells

Directory of Open Access Journals (Sweden)

Christopher T. Rhodes

2016-06-01

Full Text Available Neural stem progenitor cells (NSPCs in the human subventricular zone (SVZ potentially contribute to lifelong neurogenesis, yet subtypes of glioblastoma multiforme (GBM contain NSPC signatures that highlight the importance of cell fate regulation. Among numerous regulatory mechanisms, the posttranslational methylations onto histone tails are crucial regulator of cell fate. The work presented here focuses on the role of 2 repressive chromatin marks trimethylations on histone H3 lysine 27 (H3K27me3 and histone H4 lysine 20 (H4K20me3 in the adult NSPC within the SVZ. To best model healthy human NSPCs as they exist in vivo for epigenetic profiling of H3K27me3 and H4K20me3, we used NSPCs isolated from the adult SVZ of baboon brain (Papio anubis with brain structure and genomic level similar to human. The putative role of H3K27me3 in normal NSPCs predominantly falls into the regulation of gene expression, cell cycle, and differentiation, whereas H4K20me3 is involved in DNA replication/repair, metabolism, and cell cycle. Using conditional knockout mouse models to diminish Ezh2 and Suv4-20h responsible for H3K27me3 and H4K20me3, respectively, we found that both repressive marks have irrefutable function for cell cycle regulation in the NSPC population. Although both EZH2/H3K27me3 and Suv4-20h/H4K20me3 have implication in cancers, our comparative genomics approach between healthy NSPCs and human GBM specimens revealed that substantial sets of genes enriched with H3K27me3 and H4K20me3 in the NSPCs are altered in the human GBM. In sum, our integrated analyses across species highlight important roles of H3K27me3 and H4K20me3 in normal and disease conditions in the context of NSPC.

Development of a Thermal Equilibrium Prediction Algorithm

International Nuclear Information System (INIS)

Aviles-Ramos, Cuauhtemoc

2002-01-01

A thermal equilibrium prediction algorithm is developed and tested using a heat conduction model and data sets from calorimetric measurements. The physical model used in this study is the exact solution of a system of two partial differential equations that govern the heat conduction in the calorimeter. A multi-parameter estimation technique is developed and implemented to estimate the effective volumetric heat generation and thermal diffusivity in the calorimeter measurement chamber, and the effective thermal diffusivity of the heat flux sensor. These effective properties and the exact solution are used to predict the heat flux sensor voltage readings at thermal equilibrium. Thermal equilibrium predictions are carried out considering only 20% of the total measurement time required for thermal equilibrium. A comparison of the predicted and experimental thermal equilibrium voltages shows that the average percentage error from 330 data sets is only 0.1%. The data sets used in this study come from calorimeters of different sizes that use different kinds of heat flux sensors. Furthermore, different nuclear material matrices were assayed in the process of generating these data sets. This study shows that the integration of this algorithm into the calorimeter data acquisition software will result in an 80% reduction of measurement time. This reduction results in a significant cutback in operational costs for the calorimetric assay of nuclear materials. (authors)

Validation of ASTEC v2.0 corium jet fragmentation model using FARO experiments

International Nuclear Information System (INIS)

Hermsmeyer, S.; Pla, P.; Sangiorgi, M.

2015-01-01

Highlights: • Model validation base extended to six FARO experiments. • Focus on the calculation of the fragmented particle diameter. • Capability and limits of the ASTEC fragmentation model. • Sensitivity analysis of model outputs. - Abstract: ASTEC is an integral code for the prediction of Severe Accidents in Nuclear Power Plants. As such, it needs to cover all physical processes that could occur during accident progression, yet keeping its models simple enough for the ensemble to stay manageable and produce results within an acceptable time. The present paper is concerned with the validation of the Corium jet fragmentation model of ASTEC v2.0 rev3 by means of a selection of six experiments carried out within the FARO facility. The different conditions applied within these six experiments help to analyse the model behaviour in different situations and to expose model limits. In addition to comparing model outputs with experimental measurements, sensitivity analyses are applied to investigate the model. Results of the paper are (i) validation runs, accompanied by an identification of situations where the implemented fragmentation model does not match the experiments well, and discussion of results; (ii) its special attention to the models calculating the diameter of fragmented particles, the identification of a fault in one model implemented, and the discussion of simplification and ad hoc modification to improve the model fit; and, (iii) an investigation of the sensitivity of predictions towards inputs and parameters. In this way, the paper offers a thorough investigation of the merit and limitation of the fragmentation model used in ASTEC

Parental phonological memory contributes to prediction of outcome of late talkers from 20 months to 4 years: a longitudinal study of precursors of specific language impairment

Directory of Open Access Journals (Sweden)

Bishop Dorothy VM

2012-02-01

Full Text Available Abstract Background Many children who are late talkers go on to develop normal language, but others go on to have longer-term language difficulties. In this study, we considered which factors were predictive of persistent problems in late talkers. Methods Parental report of expressive vocabulary at 18 months of age was used to select 26 late talkers and 70 average talkers, who were assessed for language and cognitive ability at 20 months of age. Follow-up at 4 years of age was carried out for 24 late and 58 average talkers. A psychometric test battery was used to categorize children in terms of language status (unimpaired or impaired and nonverbal ability (normal range or more than 1 SD below average. The vocabulary and non-word repetition skills of the accompanying parent were also assessed. Results Among the late talkers, seven (29% met our criteria for specific language impairment (SLI at 4 years of age, and a further two (8% had low nonverbal ability. In the group of average talkers, eight (14% met the criteria for SLI at 4 years, and five other children (8% had low nonverbal ability. Family history of language problems was slightly better than late-talker status as a predictor of SLI.. The best predictors of SLI at 20 months of age were score on the receptive language scale of the Mullen Scales of Early Learning and the parent's performance on a non-word repetition task. Maternal education was not a significant predictor of outcome. Conclusions In this study, around three-quarters of late talkers did not have any language difficulties at 4 years of age, provided there was no family history of language impairment. A family history of language-literacy problems was found to be a significant predictor for persisting problems. Nevertheless, there are children with SLI for whom prediction is difficult because they did not have early language delay.

Percent free prostate-specific antigen is effective to predict prostate biopsy outcome in Chinese men with prostate-specific antigen between 10.1 and 20.0 ng ml−1

Science.gov (United States)

Chen, Rui; Zhou, Li-Qun; Cai, Xiao-Bing; Xie, Li-Ping; Huang, Yi-Ran; He, Da-Lin; Gao, Xu; Xu, Chuan-Liang; Ding, Qiang; Wei, Qiang; Yin, Chang-Jun; Ren, Shan-Cheng; Wang, Fu-Bo; Tian, Ye; Sun, Zhong-Quan; Fu, Qiang; Ma, Lu-Lin; Zheng, Jun-Hua; Ye, Zhang-Qun; Ye, Ding-Wei; Xu, Dan-Feng; Hou, Jian-Quan; Xu, Ke-Xin; Yuan, Jian-Lin; Gao, Xin; Liu, Chun-Xiao; Pan, Tie-Jun; Sun, Ying-Hao

2015-01-01

Percent free prostatic-specific antigen (%fPSA) has been introduced as a tool to avoid unnecessary biopsies in patients with a serum PSA level of 4.0–10.0 ng ml−1, however, it remains controversial whether %fPSA is effective in PSA range of 10.1–20.0 ng ml−1 in both Chinese and Western population. In this study, the diagnostic performance of %fPSA and serum PSA in predicting prostate cancer (PCa) and high-grade PCa (HGPCa) was analyzed in a multi-center biopsy cohort of 5915 consecutive Chinese patients who underwent prostate biopsy in 22 hospitals across China from January 1, 2010 to December 31, 2013. The indication for biopsy was PSA>4.0 ng ml−1 or/and suspicious digital rectal examination. Total and free serum PSA determinations were performed by three types of electrochemiluminescence immunoassays with recalibration to the World Health Organization standards. The diagnostics accuracy of PSA, %fPSA and %fPSA in combination with PSA (%fPSA + PSA) was determined by the area under the receivers operating characteristic curve (AUC). %fPSA was more effective than PSA in men aged ≥60 years old. The AUC was 0.584 and 0.635 in men aged ≥60 years old with a PSA of 4.0–10.0 ng ml−1 and 10.1–20.0 ng ml−1, respectively. The AUC of %fPSA was superior to that of PSA in predicting HGPCa in patients ≥60 years old in these two PSA range. Our results indicated that %fPSA is both statistically effective and clinical applicable to predict prostate biopsy outcome in Chinese patients aged ≥60 years old with a PSA of 4.0–10.0 ng ml−1 and 10.1–20.0 ng ml−1. PMID:25926603

Percent free prostate-specific antigen is effective to predict prostate biopsy outcome in Chinese men with prostate-specific antigen between 10.1 and 20.0 ng ml(-1).

Science.gov (United States)

Chen, Rui; Zhou, Li-Qun; Cai, Xiao-Bing; Xie, Li-Ping; Huang, Yi-Ran; He, Da-Lin; Gao, Xu; Xu, Chuan-Liang; Ding, Qiang; Wei, Qiang; Yin, Chang-Jun; Ren, Shan-Cheng; Wang, Fu-Bo; Tian, Ye; Sun, Zhong-Quan; Fu, Qiang; Ma, Lu-Lin; Zheng, Jun-Hua; Ye, Zhang-Qun; Ye, Ding-Wei; Xu, Dan-Feng; Hou, Jian-Quan; Xu, Ke-Xin; Yuan, Jian-Lin; Gao, Xin; Liu, Chun-Xiao; Pan, Tie-Jun; Sun, Ying-Hao

2015-01-01

Percent free prostatic-specific antigen (%fPSA) has been introduced as a tool to avoid unnecessary biopsies in patients with a serum PSA level of 4.0-10.0 ng ml-1 , however, it remains controversial whether %fPSA is effective in PSA range of 10.1-20.0 ng ml-1 in both Chinese and Western population. In this study, the diagnostic performance of %fPSA and serum PSA in predicting prostate cancer (PCa) and high-grade PCa (HGPCa) was analyzed in a multi-center biopsy cohort of 5915 consecutive Chinese patients who underwent prostate biopsy in 22 hospitals across China from January 1, 2010 to December 31, 2013. The indication for biopsy was PSA>4.0 ng ml-1 or/and suspicious digital rectal examination. Total and free serum PSA determinations were performed by three types of electrochemiluminescence immunoassays with recalibration to the World Health Organization standards. The diagnostics accuracy of PSA, %fPSA and %fPSA in combination with PSA (%fPSA + PSA) was determined by the area under the receivers operating characteristic curve (AUC). %fPSA was more effective than PSA in men aged ≥60 years old. The AUC was 0.584 and 0.635 in men aged ≥60 years old with a PSA of 4.0-10.0 ng ml-1 and 10.1-20.0 ng ml-1 , respectively. The AUC of %fPSA was superior to that of PSA in predicting HGPCa in patients ≥60 years old in these two PSA range. Our results indicated that %fPSA is both statistically effective and clinical applicable to predict prostate biopsy outcome in Chinese patients aged ≥60 years old with a PSA of 4.0-10.0 ng ml-1 and 10.1-20.0 ng ml-1 .

Use of protection motivation theory, affect, and barriers to understand and predict adherence to outpatient rehabilitation.

Science.gov (United States)

Grindley, Emma J; Zizzi, Samuel J; Nasypany, Alan M

2008-12-01

Protection motivation theory (PMT) has been used in more than 20 different health-related fields to study intentions and behavior, albeit primarily outside the area of injury rehabilitation. In order to examine and predict patient adherence behavior, this study was carried out to explore the use of PMT as a screening tool in a general sample of people with orthopedic conditions. New patients who were more than 18 years old and who were prescribed 4 to 8 weeks of physical therapy treatment (n=229) were administered a screening tool (Sports Injury Rehabilitation Beliefs Scale, Positive and Negative Affect Schedule, and a barriers checklist) prior to treatment. Participants' adherence was assessed with several attendance measures and an in-clinic assessment of behavior. Statistical analyses included correlation, chi-square, multiple regression, and discriminant function analyses. A variety of relationships among affect, barriers, and PMT components were evident. In-clinic behavior and attendance were influenced by affect, whereas dropout status was predicted by affect, severity, self-efficacy, and age. The screening tool used in this study may assist in identifying patients who are at risk for poor adherence and provide valuable information to enhance provider-patient relationships and foster patient adherence. However, it is recommended that more research be conducted to further understand the impact of variables on patient adherence and that the screening tool be enhanced to increase its predictive ability.

Linear filters as a method of real-time prediction of geomagnetic activity

International Nuclear Information System (INIS)

McPherron, R.L.; Baker, D.N.; Bargatze, L.F.

1985-01-01

Important factors controlling geomagnetic activity include the solar wind velocity, the strength of the interplanetary magnetic field (IMF), and the field orientation. Because these quantities change so much in transit through the solar wind, real-time monitoring immediately upstream of the earth provides the best input for any technique of real-time prediction. One such technique is linear prediction filtering which utilizes past histories of the input and output of a linear system to create a time-invariant filter characterizing the system. Problems of nonlinearity or temporal changes of the system can be handled by appropriate choice of input parameters and piecewise approximation in various ranges of the input. We have created prediction filters for all the standard magnetic indices and tested their efficiency. The filters show that the initial response of the magnetosphere to a southward turning of the IMF peaks in 20 minutes and then again in 55 minutes. After a northward turning, auroral zone indices and the midlatitude ASYM index return to background within 2 hours, while Dst decays exponentially with a time constant of about 8 hours. This paper describes a simple, real-time system utilizing these filters which could predict a substantial fraction of the variation in magnetic activity indices 20 to 50 minutes in advance

Numerical prediction of turbulent heat transfer augmentation in an annular fuel channel with two-dimensional square ribs

International Nuclear Information System (INIS)

Takase, Kazuyuki

1996-01-01

The square-ribbed fuel rod for high temperature gas-cooled reactors was developed in order to enhance the turbulent heat transfer in comparison with the standard fuel rod. To evaluate the heat transfer performance of the square-ribbed fuel rod, the turbulent heat transfer coefficients in an annular fuel channel with repeated two-dimensional square ribs were analyzed numerically on a fully developed incompressible flow using the k - ε turbulence model and the two-dimensional axisymmetrical coordinate system. Numerical analyses were carried out for a range of Reynolds numbers from 3000 to 20000 and ratios of square-rib pitch to height of 10, 20 and 40, respectively. The predicted values of the heat transfer coefficients agreed within an error of 10% for the square-rib pitch to height ratio of 10, 20% for 20 and 25% for 40, respectively, with the heat transfer empirical correlations obtained from the experimental data. It was concluded by the present study that the effect of the heat transfer augmentation by square ribs could be predicted sufficiently by the present numerical simulations and also a part of its mechanism could be explained by means of the change in the turbulence kinematic energy distribution along the flow direction. (author)

Novel FAM20A mutation causes autosomal recessive amelogenesis imperfecta.

Science.gov (United States)

Volodarsky, Michael; Zilberman, Uri; Birk, Ohad S

2015-06-01

To relate the peculiar phenotype of amelogenesis imperfecta in a large Bedouin family to the genotype determined by whole genome linkage analysis. Amelogenesis imperfecta (AI) is a broad group of inherited pathologies affecting enamel formation, characterized by variability in phenotypes, causing mutations and modes of inheritance. Autosomal recessive or compound heterozygous mutations in FAM20A, encoding sequence similarity 20, member A, have been shown to cause several AI phenotypes. Five members from a large consanguineous Bedouin family presented with hypoplastic amelogenesis imperfecta with unerupted and resorbed permanent molars. Following Soroka Medical Center IRB approval and informed consent, blood samples were obtained from six affected offspring, five obligatory carriers and two unaffected siblings. Whole genome linkage analysis was performed followed by Sanger sequencing of FAM20A. The sequencing unravelled a novel homozygous deletion mutation in exon 11 (c.1523delC), predicted to insert a premature stop codon (p.Thr508Lysfs*6). We provide an interesting case of novel mutation in this rare disorder, in which the affected kindred is unique in the large number of family members sharing a similar phenotype. Copyright © 2015 Elsevier Ltd. All rights reserved.

Target gene analyses of 39 amelogenesis imperfecta kindreds

Science.gov (United States)

Chan, Hui-Chen; Estrella, Ninna M. R. P.; Milkovich, Rachel N.; Kim, Jung-Wook; Simmer, James P.; Hu, Jan C-C.

2012-01-01

Previously, mutational analyses identified six disease-causing mutations in 24 amelogenesis imperfecta (AI) kindreds. We have since expanded the number of AI kindreds to 39, and performed mutation analyses covering the coding exons and adjoining intron sequences for the six proven AI candidate genes [amelogenin (AMELX), enamelin (ENAM), family with sequence similarity 83, member H (FAM83H), WD repeat containing domain 72 (WDR72), enamelysin (MMP20), and kallikrein-related peptidase 4 (KLK4)] and for ameloblastin (AMBN) (a suspected candidate gene). All four of the X-linked AI families (100%) had disease-causing mutations in AMELX, suggesting that AMELX is the only gene involved in the aetiology of X-linked AI. Eighteen families showed an autosomal-dominant pattern of inheritance. Disease-causing mutations were identified in 12 (67%): eight in FAM83H, and four in ENAM. No FAM83H coding-region or splice-junction mutations were identified in three probands with autosomal-dominant hypocalcification AI (ADHCAI), suggesting that a second gene may contribute to the aetiology of ADHCAI. Six families showed an autosomal-recessive pattern of inheritance, and disease-causing mutations were identified in three (50%): two in MMP20, and one in WDR72. No disease-causing mutations were found in 11 families with only one affected member. We conclude that mutation analyses of the current candidate genes for AI have about a 50% chance of identifying the disease-causing mutation in a given kindred. PMID:22243262

10 CFR 436.20 - Net savings.

Science.gov (United States)

2010-01-01

... ENERGY ENERGY CONSERVATION FEDERAL ENERGY MANAGEMENT AND PLANNING PROGRAMS Methodology and Procedures for Life Cycle Cost Analyses § 436.20 Net savings. For a retrofit project, net savings may be found by subtracting life cycle costs based on the proposed project from life cycle costs based on not having it. For a...

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.

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.

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 literature review and meta-analyses of cannabis use and suicidality.

Science.gov (United States)

Borges, Guilherme; Bagge, Courtney L; Orozco, Ricardo

2016-05-01

We lack a review of the epidemiological literature on cannabis use (acute use and chronic-usual quantity/frequency and heavy use) and suicidality (suicide death, suicide ideation, suicide attempt). The English language literature on Medline, PsychInfo, Google Scholar, and public-use databases was searched for original articles, critical review reports, and public use data on cannabis use and suicide for the period ranging from 1990-2015 (February). Odds ratios (OR) from random effects in meta-analyses for any cannabis use and heavy cannabis use were calculated. The acute cannabis-suicidality literature mostly includes descriptive toxicology reports. In terms of death by suicide, the average positive cannabis rate was 9.50% for studies sampling from all suicides, with higher cannabis detection rates amongst suicide decedents by non-overdose methods. We found only 4 studies providing estimates for any chronic cannabis use and death by suicide (OR=2.56 (1.25-5.27)). After deleting duplicates we found 6 studies on any cannabis use and suicide ideation (OR=1.43 (1.13-1.83)), 5 studies on heavy cannabis use and suicide ideation (OR=2.53 (1.00-6.39)), 6 studies on any cannabis use and suicide attempt (OR=2.23 (1.24-4.00)) and 6 studies on heavy cannabis use and suicide attempt (OR=3.20 (1.72-5.94)). We currently lack evidence that acute cannabis use increases imminent risk for suicidality. The evidence tends to support that chronic cannabis use can predict suicidality, but the lack of homogeneity in the measurement of cannabis exposure and, in some instances, the lack of systematic control for known risk factors tempered this finding. Copyright © 2016 Elsevier B.V. All rights reserved.

Prediction Models for Assessing Lycopene in Open-Field Cultivated Tomatoes by Means of a Portable Reflectance Sensor: Cultivar and Growing-Season Effects.

Science.gov (United States)

Ciaccheri, Leonardo; Tuccio, Lorenza; Mencaglia, Andrea A; Sikorska-Zimny, Kalina; Hallmann, Ewelina; Kowalski, Artur; G Mignani, Anna; Kaniszewski, Stanislaw; Agati, Giovanni

2018-05-09

Reflectance spectroscopy represents a useful tool for the nondestructive assessment of tomato lycopene, even in the field. For this reason, a compact, low-cost, light emitting diode-based sensor has been developed to measure reflectance in the 400-750 nm spectral range. It was calibrated against wet chemistry and evaluated by partial least squares (PLS) regression analyses. The lycopene prediction models were defined for two open-field cultivated red-tomato varieties: the processing oblong tomatoes of the cv. Calista (average weight: 76 g) and the fresh-consumption round tomatoes of the cv. Volna (average weight: 130 g), over a period of two consecutive years. The lycopene prediction models were dependent on both cultivar and season. The lycopene root mean square error of prediction produced by the 2014 single-cultivar calibrations validated on the 2015 samples was large (33 mg kg -1 ) in the Calista tomatoes and acceptable (9.5 mg kg -1 ) in the Volna tomatoes. A more general bicultivar and biyear model could still explain almost 80% of the predicted lycopene variance, with a relative error in red tomatoes of less than 20%. In 2016, the in-field applications of the multiseasonal prediction models, built with the 2014 and 2015 data, showed significant ( P lycopene estimated in the crop on two sampling dates that were 20 days apart: on August 19 and September 7, 2016, the lycopene was 98.9 ± 9.3 and 92.2 ± 10.8 mg kg -1 FW for cv. Calista and 54.6 ± 13.2 and 60.8 ± 6.8 mg kg -1 FW for cv. Volna. The sensor was also able to monitor the temporal evolution of lycopene accumulation on the very same fruits attached to the plants. These results indicated that a simple, compact reflectance device and PLS analysis could provide adequately precise and robust (through-seasons) models for the nondestructive assessment of lycopene in whole tomatoes. This technique could guarantee tomatoes with the highest nutraceutical value from the production, during storage and

Factors Predicting Pre-Service Teachers' Adoption of Web 2.0 Technologies

Science.gov (United States)

Cheon, Jongpil; Coward, Fanni; Song, Jaeki; Lim, Sunho

2012-01-01

Classrooms full of "digital natives" represent the norm in U. S. schools, but like their predecessors, they mostly inhabit spaces characterized by a traditional view of teaching and learning. Understanding contributors to this mismatch, and especially teachers' role, is especially critical as Web 2.0 technologies enable greater learner…

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)

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.

[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.

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.

Model-free prediction and regression a transformation-based approach to inference

CERN Document Server

Politis, Dimitris N

2015-01-01

The Model-Free Prediction Principle expounded upon in this monograph is based on the simple notion of transforming a complex dataset to one that is easier to work with, e.g., i.i.d. or Gaussian. As such, it restores the emphasis on observable quantities, i.e., current and future data, as opposed to unobservable model parameters and estimates thereof, and yields optimal predictors in diverse settings such as regression and time series. Furthermore, the Model-Free Bootstrap takes us beyond point prediction in order to construct frequentist prediction intervals without resort to unrealistic assumptions such as normality. Prediction has been traditionally approached via a model-based paradigm, i.e., (a) fit a model to the data at hand, and (b) use the fitted model to extrapolate/predict future data. Due to both mathematical and computational constraints, 20th century statistical practice focused mostly on parametric models. Fortunately, with the advent of widely accessible powerful computing in the late 1970s, co...

Development of steady-state model for MSPT and detailed analyses of receiver

Science.gov (United States)

Yuasa, Minoru; Sonoda, Masanori; Hino, Koichi

2016-05-01

Molten salt parabolic trough system (MSPT) uses molten salt as heat transfer fluid (HTF) instead of synthetic oil. The demonstration plant of MSPT was constructed by Chiyoda Corporation and Archimede Solar Energy in Italy in 2013. Chiyoda Corporation developed a steady-state model for predicting the theoretical behavior of the demonstration plant. The model was designed to calculate the concentrated solar power and heat loss using ray tracing of incident solar light and finite element modeling of thermal energy transferred into the medium. This report describes the verification of the model using test data on the demonstration plant, detailed analyses on the relation between flow rate and temperature difference on the metal tube of receiver and the effect of defocus angle on concentrated power rate, for solar collector assembly (SCA) development. The model is accurate to an extent of 2.0% as systematic error and 4.2% as random error. The relationships between flow rate and temperature difference on metal tube and the effect of defocus angle on concentrated power rate are shown.

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...

GIMDA: Graphlet interaction-based MiRNA-disease association prediction.

Science.gov (United States)

Chen, Xing; Guan, Na-Na; Li, Jian-Qiang; Yan, Gui-Ying

2018-03-01

MicroRNAs (miRNAs) have been confirmed to be closely related to various human complex diseases by many experimental studies. It is necessary and valuable to develop powerful and effective computational models to predict potential associations between miRNAs and diseases. In this work, we presented a prediction model of Graphlet Interaction for MiRNA-Disease Association prediction (GIMDA) by integrating the disease semantic similarity, miRNA functional similarity, Gaussian interaction profile kernel similarity and the experimentally confirmed miRNA-disease associations. The related score of a miRNA to a disease was calculated by measuring the graphlet interactions between two miRNAs or two diseases. The novelty of GIMDA lies in that we used graphlet interaction to analyse the complex relationships between two nodes in a graph. The AUCs of GIMDA in global and local leave-one-out cross-validation (LOOCV) turned out to be 0.9006 and 0.8455, respectively. The average result of five-fold cross-validation reached to 0.8927 ± 0.0012. In case study for colon neoplasms, kidney neoplasms and prostate neoplasms based on the database of HMDD V2.0, 45, 45, 41 of the top 50 potential miRNAs predicted by GIMDA were validated by dbDEMC and miR2Disease. Additionally, in the case study of new diseases without any known associated miRNAs and the case study of predicting potential miRNA-disease associations using HMDD V1.0, there were also high percentages of top 50 miRNAs verified by the experimental literatures. © 2017 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine.

Designing a Prognostic Scoring System for Predicting the Outcomes of Proximal Fifth Metatarsal Fractures at 20 Weeks

Directory of Open Access Journals (Sweden)

Mohammad Ali Tahririan

2015-03-01

Full Text Available Background: Fractures of the proximal fifth metatarsal bone are among the most common fractures observed in the foot and their classification and management has been subject to much discussion and disagreement. In this study, we aim to identify and quantify the effect of possible predictors of the outcome of the treatment of proximal fifth metatarsal fractures. Methods: Patients with established proximal fifth metatarsal fractures were enrolled in this prospective cohort and the outcome of their treatment was assessed using the AOFAS mid foot scale at 6 and 20 weeks. Results: 143 patients were included in the study. Our study showed that displacement, weight and type III fractures were significant independent predictors of poor outcome at 6 weeks while at 20 weeks in addition to these factors, gender and diabetes mellitus were also shown to be significant independent predictors of poor outcome. A scoring system was designed by assigning weight to these factors and it was shown to be a strong predictor of outcome at 20 weeks. Conclusion: We recommend that our scoring system would help surgeons to decide whether patients’ prognostic factors are significant enough for him/her to opt for a surgical approach to treatment rather than a conservative approach.

PSPP: a protein structure prediction pipeline for computing clusters.

Directory of Open Access Journals (Sweden)

Michael S Lee

2009-07-01

Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

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...

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.;

A fast and robust iterative algorithm for prediction of RNA pseudoknotted secondary structures

Science.gov (United States)

2014-01-01

Background Improving accuracy and efficiency of computational methods that predict pseudoknotted RNA secondary structures is an ongoing challenge. Existing methods based on free energy minimization tend to be very slow and are limited in the types of pseudoknots that they can predict. Incorporating known structural information can improve prediction accuracy; however, there are not many methods for prediction of pseudoknotted structures that can incorporate structural information as input. There is even less understanding of the relative robustness of these methods with respect to partial information. Results We present a new method, Iterative HFold, for pseudoknotted RNA secondary structure prediction. Iterative HFold takes as input a pseudoknot-free structure, and produces a possibly pseudoknotted structure whose energy is at least as low as that of any (density-2) pseudoknotted structure containing the input structure. Iterative HFold leverages strengths of earlier methods, namely the fast running time of HFold, a method that is based on the hierarchical folding hypothesis, and the energy parameters of HotKnots V2.0. Our experimental evaluation on a large data set shows that Iterative HFold is robust with respect to partial information, with average accuracy on pseudoknotted structures steadily increasing from roughly 54% to 79% as the user provides up to 40% of the input structure. Iterative HFold is much faster than HotKnots V2.0, while having comparable accuracy. Iterative HFold also has significantly better accuracy than IPknot on our HK-PK and IP-pk168 data sets. Conclusions Iterative HFold is a robust method for prediction of pseudoknotted RNA secondary structures, whose accuracy with more than 5% information about true pseudoknot-free structures is better than that of IPknot, and with about 35% information about true pseudoknot-free structures compares well with that of HotKnots V2.0 while being significantly faster. Iterative HFold and all data used in

A REDEFINITION OF TELEWORK THROUGH CLOUD COMPUTING - TELEWORK 2.0

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B. Ghilic-Micu

2016-11-01

Full Text Available In this paper we aim to analyse two paradigms, from the perspective of the mutual recursivity between them: telework and cloud computing. The main purpose of this scientific endeavour is to determine the level of support of each paradigm for the other and the synergic effect generated by their interdependence. We will approach functional, juridical and environmental issues. As result, we aim to highlight the way Cloud computing solutions may revolutionize all that is telework and who telework may be redefined through the transition to a superior level, called telework 2.0.

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

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

Rockslide and Impulse Wave Modelling in the Vajont Reservoir by DEM-CFD Analyses

Science.gov (United States)

Zhao, T.; Utili, S.; Crosta, G. B.

2016-06-01

This paper investigates the generation of hydrodynamic water waves due to rockslides plunging into a water reservoir. Quasi-3D DEM analyses in plane strain by a coupled DEM-CFD code are adopted to simulate the rockslide from its onset to the impact with the still water and the subsequent generation of the wave. The employed numerical tools and upscaling of hydraulic properties allow predicting a physical response in broad agreement with the observations notwithstanding the assumptions and characteristics of the adopted methods. The results obtained by the DEM-CFD coupled approach are compared to those published in the literature and those presented by Crosta et al. (Landslide spreading, impulse waves and modelling of the Vajont rockslide. Rock mechanics, 2014) in a companion paper obtained through an ALE-FEM method. Analyses performed along two cross sections are representative of the limit conditions of the eastern and western slope sectors. The max rockslide average velocity and the water wave velocity reach ca. 22 and 20 m/s, respectively. The maximum computed run up amounts to ca. 120 and 170 m for the eastern and western lobe cross sections, respectively. These values are reasonably similar to those recorded during the event (i.e. ca. 130 and 190 m, respectively). Therefore, the overall study lays out a possible DEM-CFD framework for the modelling of the generation of the hydrodynamic wave due to the impact of a rapid moving rockslide or rock-debris avalanche.

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.

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

A predictive coding account of bistable perception - a model-based fMRI study.

Science.gov (United States)

Weilnhammer, Veith; Stuke, Heiner; Hesselmann, Guido; Sterzer, Philipp; Schmack, Katharina

2017-05-01

In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together, our current work

A predictive coding account of bistable perception - a model-based fMRI study.

Directory of Open Access Journals (Sweden)

Veith Weilnhammer

2017-05-01

Full Text Available In bistable vision, subjective perception wavers between two interpretations of a constant ambiguous stimulus. This dissociation between conscious perception and sensory stimulation has motivated various empirical studies on the neural correlates of bistable perception, but the neurocomputational mechanism behind endogenous perceptual transitions has remained elusive. Here, we recurred to a generic Bayesian framework of predictive coding and devised a model that casts endogenous perceptual transitions as a consequence of prediction errors emerging from residual evidence for the suppressed percept. Data simulations revealed close similarities between the model's predictions and key temporal characteristics of perceptual bistability, indicating that the model was able to reproduce bistable perception. Fitting the predictive coding model to behavioural data from an fMRI-experiment on bistable perception, we found a correlation across participants between the model parameter encoding perceptual stabilization and the behaviourally measured frequency of perceptual transitions, corroborating that the model successfully accounted for participants' perception. Formal model comparison with established models of bistable perception based on mutual inhibition and adaptation, noise or a combination of adaptation and noise was used for the validation of the predictive coding model against the established models. Most importantly, model-based analyses of the fMRI data revealed that prediction error time-courses derived from the predictive coding model correlated with neural signal time-courses in bilateral inferior frontal gyri and anterior insulae. Voxel-wise model selection indicated a superiority of the predictive coding model over conventional analysis approaches in explaining neural activity in these frontal areas, suggesting that frontal cortex encodes prediction errors that mediate endogenous perceptual transitions in bistable perception. Taken together

Analyser-based phase contrast image reconstruction using geometrical optics.

Science.gov (United States)

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-07-21

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser.

Deep learning predictions of survival based on MRI in amyotrophic lateral sclerosis.

Science.gov (United States)

van der Burgh, Hannelore K; Schmidt, Ruben; Westeneng, Henk-Jan; de Reus, Marcel A; van den Berg, Leonard H; van den Heuvel, Martijn P

2017-01-01

Amyotrophic lateral sclerosis (ALS) is a progressive neuromuscular disease, with large variation in survival between patients. Currently, it remains rather difficult to predict survival based on clinical parameters alone. Here, we set out to use clinical characteristics in combination with MRI data to predict survival of ALS patients using deep learning, a machine learning technique highly effective in a broad range of big-data analyses. A group of 135 ALS patients was included from whom high-resolution diffusion-weighted and T1-weighted images were acquired at the first visit to the outpatient clinic. Next, each of the patients was monitored carefully and survival time to death was recorded. Patients were labeled as short, medium or long survivors, based on their recorded time to death as measured from the time of disease onset. In the deep learning procedure, the total group of 135 patients was split into a training set for deep learning (n = 83 patients), a validation set (n = 20) and an independent evaluation set (n = 32) to evaluate the performance of the obtained deep learning networks. Deep learning based on clinical characteristics predicted survival category correctly in 68.8% of the cases. Deep learning based on MRI predicted 62.5% correctly using structural connectivity and 62.5% using brain morphology data. Notably, when we combined the three sources of information, deep learning prediction accuracy increased to 84.4%. Taken together, our findings show the added value of MRI with respect to predicting survival in ALS, demonstrating the advantage of deep learning in disease prognostication.

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.

Vaginal birth after caesarean section prediction models: a UK comparative observational study.

Science.gov (United States)

Mone, Fionnuala; Harrity, Conor; Mackie, Adam; Segurado, Ricardo; Toner, Brenda; McCormick, Timothy R; Currie, Aoife; McAuliffe, Fionnuala M

2015-10-01

Primarily, to assess the performance of three statistical models in predicting successful vaginal birth in patients attempting a trial of labour after one previous lower segment caesarean section (TOLAC). The statistically most reliable models were subsequently subjected to validation testing in a local antenatal population. A retrospective observational study was performed with study data collected from the Northern Ireland Maternity Service Database (NIMATs). The study population included all women that underwent a TOLAC (n=385) from 2010 to 2012 in a regional UK obstetric unit. Data was collected from the Northern Ireland Maternity Service Database (NIMATs). Area under the curve (AUC) and correlation analysis was performed. Of the three prediction models evaluated, AUC calculations for the Smith et al., Grobman et al. and Troyer and Parisi Models were 0.74, 0.72 and 0.65, respectively. Using the Smith et al. model, 52% of women had a low risk of caesarean section (CS) (predicted VBAC >72%) and 20% had a high risk of CS (predicted VBAC <60%), of whom 20% and 63% had delivery by CS. The fit between observed and predicted outcome in this study cohort using the Smith et al. and Grobman et al. models were greatest (Chi-square test, p=0.228 and 0.904), validating both within the population. The Smith et al. and Grobman et al. models could potentially be utilized within the UK to provide women with an informed choice when deciding on mode of delivery after a previous CS. Crown Copyright © 2015. Published by Elsevier Ireland Ltd. All rights reserved.

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

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

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.

Increased Expression of microRNA-17 Predicts Poor Prognosis in Human Glioma

Directory of Open Access Journals (Sweden)

Shengkui Lu

2012-01-01

Full Text Available Aim. To investigate the clinical significance of microRNA-17 (miR-17 expression in human gliomas. Methods. Quantitative real-time polymerase chain reaction (qRT-PCR analysis was used to characterize the expression patterns of miR-17 in 108 glioma and 20 normal brain tissues. The associations of miR-17 expression with clinicopathological factors and prognosis of glioma patients were also statistically analyzed. Results. Compared with normal brain tissues, miR-17 expression was significantly higher in glioma tissues (P<0.001. In addition, the increased expression of miR-17 in glioma was significantly associated with advanced pathological grade (P=0.006 and low Karnofsky performance score (KPS, P=0.01. Moreover, Kaplan-Meier survival and Cox regression analyses showed that miR-17 overexpression (P=0.008 and advanced pathological grade (P=0.02 were independent factors predicting poor prognosis for gliomas. Furthermore, subgroup analyses showed that miR-17 expression was significantly associated with poor overall survival in glioma patients with high pathological grades (for grade III~IV: P<0.001. Conclusions. Our data offer the convinced evidence that the increased expression of miR-17 may have potential value for predicting poor prognosis in glioma patients with high pathological grades, indicating that miR-17 may contribute to glioma progression and be a candidate therapeutic target for this disease.

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.

Active Canada 20/20: A physical activity plan for Canada.

Science.gov (United States)

Spence, John C; Faulkner, Guy; Costas Bradstreet, Christa; Duggan, Mary; Tremblay, Mark S

2016-03-16

Physical inactivity is a pressing public health concern. In this commentary we argue that Canada's approach to increasing physical activity (PA) has been fragmented and has lacked coordination, funding and a strategic approach. We then describe a potential solution in Active Canada 20/20 (AC 20/20), which provides both a national plan and a commitment to action from non-government and public sectors with a view to engaging corporate Canada and the general public. It outlines a road map for initiating, coordinating and implementing proactive initiatives to address this prominent health risk factor. The identified actions are based on the best available evidence and have been endorsed by the majority of representatives in the relevant sectors. The next crucial steps are to engage all those involved in public health promotion, service provision and advocacy at the municipal, provincial and national levels in order to incorporate AC 20/20 principles into practice and planning and thus increase the PA level of every person in Canada. Further, governments, as well as the private, not-for-profit and philanthropic sectors, should demonstrate leadership and continue their efforts toward providing the substantial and sustained resources needed to recalibrate Canadians' habitual PA patterns; this will ultimately improve the overall health of our citizens.

Accuracy of algorithms to predict accessory pathway location in children with Wolff-Parkinson-White syndrome.

Science.gov (United States)

Wren, Christopher; Vogel, Melanie; Lord, Stephen; Abrams, Dominic; Bourke, John; Rees, Philip; Rosenthal, Eric

2012-02-01

The aim of this study was to examine the accuracy in predicting pathway location in children with Wolff-Parkinson-White syndrome for each of seven published algorithms. ECGs from 100 consecutive children with Wolff-Parkinson-White syndrome undergoing electrophysiological study were analysed by six investigators using seven published algorithms, six of which had been developed in adult patients. Accuracy and concordance of predictions were adjusted for the number of pathway locations. Accessory pathways were left-sided in 49, septal in 20 and right-sided in 31 children. Overall accuracy of prediction was 30-49% for the exact location and 61-68% including adjacent locations. Concordance between investigators varied between 41% and 86%. No algorithm was better at predicting septal pathways (accuracy 5-35%, improving to 40-78% including adjacent locations), but one was significantly worse. Predictive accuracy was 24-53% for the exact location of right-sided pathways (50-71% including adjacent locations) and 32-55% for the exact location of left-sided pathways (58-73% including adjacent locations). All algorithms were less accurate in our hands than in other authors' own assessment. None performed well in identifying midseptal or right anteroseptal accessory pathway locations.

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...

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.

Cast iron - a predictable material

Directory of Open Access Journals (Sweden)

Jorg C. Sturm

2011-02-01

Full Text Available High strength compacted graphite iron (CGI or alloyed cast iron components are substituting previously used non-ferrous castings in automotive power train applications. The mechanical engineering industry has recognized the value in substituting forged or welded structures with stiff and light-weight cast iron castings. New products such as wind turbines have opened new markets for an entire suite of highly reliable ductile iron cast components. During the last 20 years, casting process simulation has developed from predicting hot spots and solidification to an integral assessment tool for foundries for the entire manufacturing route of castings. The support of the feeding related layout of the casting is still one of the most important duties for casting process simulation. Depending on the alloy poured, different feeding behaviors and self-feeding capabilities need to be considered to provide a defect free casting. Therefore, it is not enough to base the prediction of shrinkage defects solely on hot spots derived from temperature fields. To be able to quantitatively predict these defects, solidification simulation had to be combined with density and mass transport calculations, in order to evaluate the impact of the solidification morphology on the feeding behavior as well as to consider alloy dependent feeding ranges. For cast iron foundries, the use of casting process simulation has become an important instrument to predict the robustness and reliability of their processes, especially since the influence of alloying elements, melting practice and metallurgy need to be considered to quantify the special shrinkage and solidification behavior of cast iron. This allows the prediction of local structures, phases and ultimately the local mechanical properties of cast irons, to asses casting quality in the foundry but also to make use of this quantitative information during design of the casting. Casting quality issues related to thermally driven

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

Motor dual-tasking deficits predict falls in Parkinson's disease: A prospective study.

Science.gov (United States)

Heinzel, Sebastian; Maechtel, Mirjam; Hasmann, Sandra E; Hobert, Markus A; Heger, Tanja; Berg, Daniela; Maetzler, Walter

2016-05-01

Falls severely affect lives of Parkinson's disease (PD) patients. Cognitive impairment including dual-tasking deficits contribute to fall risk in PD. However, types of dual-tasking deficits preceding falls in PD are still unclear. Walking velocities during box-checking and subtracting serial 7s were assessed twice a year in 40 PD patients over 2.8 ± 1.0 years. Fourteen patients reported a fall within this period (4 excluded fallers already reported falls at baseline). Their dual-task costs (DTC; mean ± standard deviation) 4.2 ± 2.2 months before the first fall were compared with 22 patients never reporting falls. ROC analyses and logistic regressions accounting for DTC, UPDRS-III and disease duration were used for faller classification and prediction. Only walking/box-checking predicted fallers. Fallers showed higher DTC for walking while box-checking, p = 0.029, but not for box-checking while walking, p = 0.178 (combined motor DTC, p = 0.022), than non-fallers. Combined motor DTC classified fallers and non-fallers (area under curve: 0.75; 95% confidence interval, CI: 0.60-0.91) with 71.4% sensitivity (95%CI: 41.9%-91.6%) and 77.3% specificity (54.6%-92.2%), and significantly predicted future fallers (p = 0.023). Here, 20.4%-points higher combined motor DTC (i.e. the mean difference between fallers and non-fallers) was associated with a 2.6 (1.1-6.0) times higher odds to be a future faller. Motor dual-tasking is a potentially valuable predictor of falls in PD, suggesting that avoiding dual task situations as well as specific motor dual-task training might help to prevent falls in PD. These findings and their therapeutic relevance need to be further validated in PD patients without fall history, in early PD stages, and with various motor-motor dual-task challenges. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predictive characterization of aging and degradation of reactor materials in extreme environments. Final report, December 20, 2013 - September 20, 2017

Energy Technology Data Exchange (ETDEWEB)

Qu, Jianmin [Northwestern Univ., Evanston, IL (United States)

2017-09-20

Understanding of reactor material behavior in extreme environments is vital not only to the development of new materials for the next generation nuclear reactors, but also to the extension of the operating lifetimes of the current fleet of nuclear reactors. To this end, this project conducted a suite of unique experimental techniques, augmented by a mesoscale computational framework, to understand and predict the long-term effects of irradiation, temperature, and stress on material microstructures and their macroscopic behavior. The experimental techniques and computational tools were demonstrated on two distinctive types of reactor materials, namely, Zr alloys and high-Cr martensitic steels. These materials are chosen as the test beds because they are the archetypes of high-performance reactor materials (cladding, wrappers, ducts, pressure vessel, piping, etc.). To fill the knowledge gaps, and to meet the technology needs, a suite of innovative in situ transmission electron microscopy (TEM) characterization techniques (heating, heavy ion irradiation, He implantation, quantitative small-scale mechanical testing, and various combinations thereof) were developed and used to elucidate and map the fundamental mechanisms of microstructure evolution in both Zr and Cr alloys for a wide range environmental boundary conditions in the thermal-mechanical-irradiation input space. Knowledge gained from the experimental observations of the active mechanisms and the role of local microstructural defects on the response of the material has been incorporated into a mathematically rigorous and comprehensive three-dimensional mesoscale framework capable of accounting for the compositional variation, microstructural evolution and localized deformation (radiation damage) to predict aging and degradation of key reactor materials operating in extreme environments. Predictions from this mesoscale framework were compared with the in situ TEM observations to validate the model.

Predictive characterization of aging and degradation of reactor materials in extreme environments. Final report, December 20, 2013 - September 20, 2017

International Nuclear Information System (INIS)

Qu, Jianmin

2017-01-01

Understanding of reactor material behavior in extreme environments is vital not only to the development of new materials for the next generation nuclear reactors, but also to the extension of the operating lifetimes of the current fleet of nuclear reactors. To this end, this project conducted a suite of unique experimental techniques, augmented by a mesoscale computational framework, to understand and predict the long-term effects of irradiation, temperature, and stress on material microstructures and their macroscopic behavior. The experimental techniques and computational tools were demonstrated on two distinctive types of reactor materials, namely, Zr alloys and high-Cr martensitic steels. These materials are chosen as the test beds because they are the archetypes of high-performance reactor materials (cladding, wrappers, ducts, pressure vessel, piping, etc.). To fill the knowledge gaps, and to meet the technology needs, a suite of innovative in situ transmission electron microscopy (TEM) characterization techniques (heating, heavy ion irradiation, He implantation, quantitative small-scale mechanical testing, and various combinations thereof) were developed and used to elucidate and map the fundamental mechanisms of microstructure evolution in both Zr and Cr alloys for a wide range environmental boundary conditions in the thermal-mechanical-irradiation input space. Knowledge gained from the experimental observations of the active mechanisms and the role of local microstructural defects on the response of the material has been incorporated into a mathematically rigorous and comprehensive three-dimensional mesoscale framework capable of accounting for the compositional variation, microstructural evolution and localized deformation (radiation damage) to predict aging and degradation of key reactor materials operating in extreme environments. Predictions from this mesoscale framework were compared with the in situ TEM observations to validate the model.

Network-derived inhomogeneity in monthly rainfall analyses over western Tasmania

International Nuclear Information System (INIS)

Fawcett, Robert; Trewin, Blair; Barnes-Keoghan, Ian

2010-01-01

Monthly rainfall in the wetter western half of Tasmania was relatively poorly observed in the early to middle parts of the 20th century, and this causes a marked inhomogeneity in the operational gridded monthly rainfall analyses generated by the Australian Bureau of Meteorology up until the end of 2009. These monthly rainfall analyses were generated for the period 1900 to 2009 in two forms; a national analysis at 0.25 0 latitude-longitude resolution, and a southeastern Australia regional analysis at 0.1 0 resolution. For any given month, they used all the monthly data from the standard Bureau rainfall gauge network available in the Australian Data Archive for Meteorology. Since this network has changed markedly since Federation (1901), there is obvious scope for network-derived inhomogeneities in the analyses. In this study, we show that the topography-resolving techniques of the new Australian Water Availability Project analyses, adopted as the official operational analyses from the start of 2010, substantially diminish those inhomogeneities, while using largely the same observation network. One result is an improved characterisation of recent rainfall declines across Tasmania. The new analyses are available at two resolutions, 0.25 0 and 0.05 0 .

Compound-specific isotopic analyses: a novel tool for reconstruction of ancient biogeochemical processes

Science.gov (United States)

Hayes, J. M.; Freeman, K. H.; Popp, B. N.; Hoham, C. H.

1990-01-01

Patterns of isotopic fractionation in biogeochemical processes are reviewed and it is suggested that isotopic fractionations will be small when substrates are large. If so, isotopic compositions of biomarkers will reflect those of their biosynthetic precursors. This prediction is tested by consideration of results of analyses of geoporphyrins and geolipids from the Greenhorn Formation (Cretaceous, Western Interior Seaway of North America) and the Messel Shale (Eocene, lacustrine, southern Germany). It is shown (i) that isotopic compositions of porphyrins that are related to a common source, but which have been altered structurally, cluster tightly and (ii) that isotopic differences between geolipids and porphyrins related to a common source are equal to those observed in modern biosynthetic products. Both of these observations are consistent with preservation of biologically controlled isotopic compositions during diagenesis. Isotopic compositions of individual compounds can thus be interpreted in terms of biogeochemical processes in ancient depositional environments. In the Cretaceous samples, isotopic compositions of n-alkanes are covariant with those of total organic carbon, while delta values for pristane and phytane are covariant with those of porphyrins. In this unit representing an open marine environment, the preserved acyclic polyisoprenoids apparently derive mainly from primary material, while the extractable, n-alkanes derive mainly from lower levels of the food chain. In the Messel Shale, isotopic compositions of individual biomarkers range from -20.9 to -73.4% vs PDB. Isotopic compositions of specific compounds can be interpreted in terms of origin from methylotrophic, chemautotrophic, and chemolithotrophic microorganisms as well as from primary producers that lived in the water column and sediments of this ancient lake.

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

MO-G-304-02: Knowledge Based DVH Prediction Using a Geometric Dose Transform

International Nuclear Information System (INIS)

Staub, D; Wang, J; Jiang, S

2015-01-01

Purpose: To demonstrate a novel method for predicting patient dose-volume histograms (DVHs) using a prior database of optimized radiotherapy treatment plans. Such predicted DVHs could be useful for automating treatment planning. Methods: Our initial demonstration utilized a database of 100 prostate intensity-modulated radiotherapy (IMRT) data-sets. Each data-set contained a CT image with contours of the planning target volume (PTV), rectum, and bladder, the parameters of a clinically approved IMRT plan, and a corresponding simulated dose distribution. We applied a novel geometric transformation to remove the influence of the PTV size, shape, and location on the dose distribution. We termed the transformed distribution the geometrically normalized dose distribution (GNDD). This normalization transform was applied to 80 data-sets randomly selected from the database, and a population GNDD was computed as the average. Next, the population GNDD was mapped onto each of the remaining 20 patient datasets using the reverse of the geometric normalization transform, and predicted DVHs were calculated from the reverse transformed dose distributions (GNDD-DVHs). In addition, a state of the art machine learning based method from the literature was tested for comparison. Results: DVH prediction accuracy was quantified by calculating the relative root mean squared error (rRMSE) on predicted DVHs for the 20 test patients using their known DVHs. For bladder, rectum, and PTV average rRMSEs for the GNDD method were 9.7 ± 4.2%, 13.9 ± 6.0%, and 2.3 ± 0.5% respectively. Prediction results using GNDD were roughly equivalent to that from the machine learning method. Conclusion: We developed a new method for predicting DVH curves from a database of prior patient plans. We demonstrated that our simple approach achieves accuracy comparable to a method using a complicated machine learning based approach

Elastic scattering of 7Li projectiles in the energy range of 20 to 34 MeV

International Nuclear Information System (INIS)

Khallaf, S.A.E.

1983-01-01

As far as it is known, the Watanabe folding model has not been used to analyse the elastic scattering of 7 Li projectiles. The main purpose of the present work is to calculate the differential cross sections for 7 Li elastic scattering von 90 Zr, 48 , 40 Ca, 16 O and 12 C at incident energies of 20 to 34 MeV using the Watanabe folding model and to study the applicability of this model for 7 Li elastic scattering. The potentials of 7 Li ions are revealed by Taylor expansions of alpha and triton cluster potentials. The resulting differential cross sections are compared with the predicted cross sections using phenomenological potentials of 7 Li ions. (orig./WL)

Prediction of the recovery rate after surgery for cervical myelopathy from the view of CT-myelography

International Nuclear Information System (INIS)

Koyanagi, Takahiro; Satomi, Kazuhiko; Asazuma, Takahito; Toyama, Yoshiaki; Fujimura, Shoichi; Hirabayashi, Kiyoshi; Hamano, Yasuyuki; Shiraishi, Takeshi.

1991-01-01

This study was designed to prepare a formula for predicting postoperative recovery in cervical myelopathy. Preoperative CT-myelography (CT-M) was performed in a total of 103 patients, consisting of 44 with cervical spinal myelopathy (CSM), 39 with ossification of the posterior longitudinal ligament (OPLL), and 20 with cervical disk herniation (CDH). Multivariate analyses were used to obtain correlations between CT-M findings (spinal cord area and the rate of spinal cord flatness) and clinical items (age, disease duration, preoperative JOA score, and postoperative recovery rate). There was a strong positive correlation between spinal cord area and postoperative recovery rate. Because both spinal cord area and disease duration for the CSM and OPLL groups had a strong positive correlation with the recovery rate, they were found to predict postoperative recovery. In the CDH group, there was no predictive index. Spinal cord area was more potential index than preoperative severity. Disease duration may also serve as an index complementing spinal cord area in the evaluation of postoperative recovery. (N.K.)

Predicting Coronary Artery Aneurysms in Kawasaki Disease at a North American Center: An Assessment of Baseline z Scores.

Science.gov (United States)

Son, Mary Beth F; Gauvreau, Kimberlee; Kim, Susan; Tang, Alexander; Dedeoglu, Fatma; Fulton, David R; Lo, Mindy S; Baker, Annette L; Sundel, Robert P; Newburger, Jane W

2017-05-31

Accurate risk prediction of coronary artery aneurysms (CAAs) in North American children with Kawasaki disease remains a clinical challenge. We sought to determine the predictive utility of baseline coronary dimensions adjusted for body surface area ( z scores) for future CAAs in Kawasaki disease and explored the extent to which addition of established Japanese risk scores to baseline coronary artery z scores improved discrimination for CAA development. We explored the relationships of CAA with baseline z scores; with Kobayashi, Sano, Egami, and Harada risk scores; and with the combination of baseline z scores and risk scores. We defined CAA as a maximum z score (zMax) ≥2.5 of the left anterior descending or right coronary artery at 4 to 8 weeks of illness. Of 261 patients, 77 patients (29%) had a baseline zMax ≥2.0. CAAs occurred in 15 patients (6%). CAAs were strongly associated with baseline zMax ≥2.0 versus Baseline zMax ≥2.0 had a C statistic of 0.77, good sensitivity (80%), and excellent negative predictive value (98%). None of the risk scores alone had adequate discrimination. When high-risk status per the Japanese risk scores was added to models containing baseline zMax ≥2.0, none were significantly better than baseline zMax ≥2.0 alone. In a North American center, baseline zMax ≥2.0 in children with Kawasaki disease demonstrated high predictive utility for later development of CAA. Future studies should validate the utility of our findings. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

A prediction model for assessing residential radon concentration in Switzerland

International Nuclear Information System (INIS)

Hauri, Dimitri D.; Huss, Anke; Zimmermann, Frank; Kuehni, Claudia E.; Röösli, Martin

2012-01-01

Indoor radon is regularly measured in Switzerland. However, a nationwide model to predict residential radon levels has not been developed. The aim of this study was to develop a prediction model to assess indoor radon concentrations in Switzerland. The model was based on 44,631 measurements from the nationwide Swiss radon database collected between 1994 and 2004. Of these, 80% randomly selected measurements were used for model development and the remaining 20% for an independent model validation. A multivariable log-linear regression model was fitted and relevant predictors selected according to evidence from the literature, the adjusted R², the Akaike's information criterion (AIC), and the Bayesian information criterion (BIC). The prediction model was evaluated by calculating Spearman rank correlation between measured and predicted values. Additionally, the predicted values were categorised into three categories (50th, 50th–90th and 90th percentile) and compared with measured categories using a weighted Kappa statistic. The most relevant predictors for indoor radon levels were tectonic units and year of construction of the building, followed by soil texture, degree of urbanisation, floor of the building where the measurement was taken and housing type (P-values <0.001 for all). Mean predicted radon values (geometric mean) were 66 Bq/m³ (interquartile range 40–111 Bq/m³) in the lowest exposure category, 126 Bq/m³ (69–215 Bq/m³) in the medium category, and 219 Bq/m³ (108–427 Bq/m³) in the highest category. Spearman correlation between predictions and measurements was 0.45 (95%-CI: 0.44; 0.46) for the development dataset and 0.44 (95%-CI: 0.42; 0.46) for the validation dataset. Kappa coefficients were 0.31 for the development and 0.30 for the validation dataset, respectively. The model explained 20% overall variability (adjusted R²). In conclusion, this residential radon prediction model, based on a large number of measurements, was demonstrated to be

The draft genome of watermelon (Citrullus lanatus) and resequencing of 20 diverse accessions.

Science.gov (United States)

Guo, Shaogui; Zhang, Jianguo; Sun, Honghe; Salse, Jerome; Lucas, William J; Zhang, Haiying; Zheng, Yi; Mao, Linyong; Ren, Yi; Wang, Zhiwen; Min, Jiumeng; Guo, Xiaosen; Murat, Florent; Ham, Byung-Kook; Zhang, Zhaoliang; Gao, Shan; Huang, Mingyun; Xu, Yimin; Zhong, Silin; Bombarely, Aureliano; Mueller, Lukas A; Zhao, Hong; He, Hongju; Zhang, Yan; Zhang, Zhonghua; Huang, Sanwen; Tan, Tao; Pang, Erli; Lin, Kui; Hu, Qun; Kuang, Hanhui; Ni, Peixiang; Wang, Bo; Liu, Jingan; Kou, Qinghe; Hou, Wenju; Zou, Xiaohua; Jiang, Jiao; Gong, Guoyi; Klee, Kathrin; Schoof, Heiko; Huang, Ying; Hu, Xuesong; Dong, Shanshan; Liang, Dequan; Wang, Juan; Wu, Kui; Xia, Yang; Zhao, Xiang; Zheng, Zequn; Xing, Miao; Liang, Xinming; Huang, Bangqing; Lv, Tian; Wang, Junyi; Yin, Ye; Yi, Hongping; Li, Ruiqiang; Wu, Mingzhu; Levi, Amnon; Zhang, Xingping; Giovannoni, James J; Wang, Jun; Li, Yunfu; Fei, Zhangjun; Xu, Yong

2013-01-01

Watermelon, Citrullus lanatus, is an important cucurbit crop grown throughout the world. Here we report a high-quality draft genome sequence of the east Asia watermelon cultivar 97103 (2n = 2× = 22) containing 23,440 predicted protein-coding genes. Comparative genomics analysis provided an evolutionary scenario for the origin of the 11 watermelon chromosomes derived from a 7-chromosome paleohexaploid eudicot ancestor. Resequencing of 20 watermelon accessions representing three different C. lanatus subspecies produced numerous haplotypes and identified the extent of genetic diversity and population structure of watermelon germplasm. Genomic regions that were preferentially selected during domestication were identified. Many disease-resistance genes were also found to be lost during domestication. In addition, integrative genomic and transcriptomic analyses yielded important insights into aspects of phloem-based vascular signaling in common between watermelon and cucumber and identified genes crucial to valuable fruit-quality traits, including sugar accumulation and citrulline metabolism.

What Factors are Predictive of Patient-reported Outcomes? A Prospective Study of 337 Shoulder Arthroplasties.

Science.gov (United States)

Matsen, Frederick A; Russ, Stacy M; Vu, Phuong T; Hsu, Jason E; Lucas, Robert M; Comstock, Bryan A

2016-11-01

Although shoulder arthroplasties generally are effective in improving patients' comfort and function, the results are variable for reasons that are not well understood. We posed two questions: (1) What factors are associated with better 2-year outcomes after shoulder arthroplasty? (2) What are the sensitivities, specificities, and positive and negative predictive values of a multivariate predictive model for better outcome? Three hundred thirty-nine patients having a shoulder arthroplasty (hemiarthroplasty, arthroplasty for cuff tear arthropathy, ream and run arthroplasty, total shoulder or reverse total shoulder arthroplasty) between August 24, 2010 and December 31, 2012 consented to participate in this prospective study. Two patients were excluded because they were missing baseline variables. Forty-three patients were missing 2-year data. Univariate and multivariate analyses determined the relationship of baseline patient, shoulder, and surgical characteristics to a "better" outcome, defined as an improvement of at least 30% of the maximal possible improvement in the Simple Shoulder Test. The results were used to develop a predictive model, the accuracy of which was tested using a 10-fold cross-validation. After controlling for potentially relevant confounding variables, the multivariate analysis showed that the factors significantly associated with better outcomes were American Society of Anesthesiologists Class I (odds ratio [OR], 1.94; 95% CI, 1.03-3.65; p = 0.041), shoulder problem not related to work (OR, 5.36; 95% CI, 2.15-13.37; p factors listed above. The area under the receiver operating characteristic curve generated from the cross-validated enhanced predictive model was 0.79 (generally values of 0.7 to 0.8 are considered fair and values of 0.8 to 0.9 are considered good). The false-positive fraction and the true-positive fraction depended on the cutoff probability selected (ie, the selected probability above which the prediction would be classified as

A new, accurate predictive model for incident hypertension.

Science.gov (United States)

Völzke, Henry; Fung, Glenn; Ittermann, Till; Yu, Shipeng; Baumeister, Sebastian E; Dörr, Marcus; Lieb, Wolfgang; Völker, Uwe; Linneberg, Allan; Jørgensen, Torben; Felix, Stephan B; Rettig, Rainer; Rao, Bharat; Kroemer, Heyo K

2013-11-01

Data mining represents an alternative approach to identify new predictors of multifactorial diseases. This work aimed at building an accurate predictive model for incident hypertension using data mining procedures. The primary study population consisted of 1605 normotensive individuals aged 20-79 years with 5-year follow-up from the population-based study, that is the Study of Health in Pomerania (SHIP). The initial set was randomly split into a training and a testing set. We used a probabilistic graphical model applying a Bayesian network to create a predictive model for incident hypertension and compared the predictive performance with the established Framingham risk score for hypertension. Finally, the model was validated in 2887 participants from INTER99, a Danish community-based intervention study. In the training set of SHIP data, the Bayesian network used a small subset of relevant baseline features including age, mean arterial pressure, rs16998073, serum glucose and urinary albumin concentrations. Furthermore, we detected relevant interactions between age and serum glucose as well as between rs16998073 and urinary albumin concentrations [area under the receiver operating characteristic (AUC 0.76)]. The model was confirmed in the SHIP validation set (AUC 0.78) and externally replicated in INTER99 (AUC 0.77). Compared to the established Framingham risk score for hypertension, the predictive performance of the new model was similar in the SHIP validation set and moderately better in INTER99. Data mining procedures identified a predictive model for incident hypertension, which included innovative and easy-to-measure variables. The findings promise great applicability in screening settings and clinical practice.

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)

LOD score exclusion analyses for candidate genes using random population samples.

Science.gov (United States)

Deng, H W; Li, J; Recker, R R

2001-05-01

While extensive analyses have been conducted to test for, no formal analyses have been conducted to test against, the importance of candidate genes with random population samples. We develop a LOD score approach for exclusion analyses of candidate genes with random population samples. Under this approach, specific genetic effects and inheritance models at candidate genes can be analysed and if a LOD score is < or = - 2.0, the locus can be excluded from having an effect larger than that specified. Computer simulations show that, with sample sizes often employed in association studies, this approach has high power to exclude a gene from having moderate genetic effects. In contrast to regular association analyses, population admixture will not affect the robustness of our analyses; in fact, it renders our analyses more conservative and thus any significant exclusion result is robust. Our exclusion analysis complements association analysis for candidate genes in random population samples and is parallel to the exclusion mapping analyses that may be conducted in linkage analyses with pedigrees or relative pairs. The usefulness of the approach is demonstrated by an application to test the importance of vitamin D receptor and estrogen receptor genes underlying the differential risk to osteoporotic fractures.

A Landscape-based model for predicting Mycobacterium ulcerans infection (Buruli Ulcer disease) presence in Benin, West Africa.

Science.gov (United States)

Wagner, Tyler; Benbow, M Eric; Burns, Meghan; Johnson, R Christian; Merritt, Richard W; Qi, Jiaguo; Small, Pamela L C

2008-03-01

Mycobacterium ulcerans infection (Buruli ulcer [BU] disease) is an emerging tropical disease that causes severe morbidity in many communities, especially those in close proximity to aquatic environments. Research and control efforts are severely hampered by the paucity of data regarding the ecology of this disease; for example, the vectors and modes of transmission remain unknown. It is hypothesized that BU presence is associated with altered landscapes that perturb aquatic ecosystems; however, this has yet to be quantified over large spatial scales. We quantified relationships between land use/land cover (LULC) characteristics surrounding individual villages and BU presence in Benin, West Africa. We also examined the effects of other village-level characteristics which we hypothesized to affect BU presence, such as village distance to the nearest river. We found that as the percent urban land use in a 50-km buffer surrounding a village increased, the probability of BU presence decreased. Conversely, as the percent agricultural land use in a 20-km buffer surrounding a village increased, the probability of BU presence increased. Landscape-based models had predictive ability when predicting BU presence using validation data sets from Benin and Ghana, West Africa. Our analyses suggest that relatively small amounts of urbanization are associated with a decrease in the probability of BU presence, and we hypothesize that this is due to the increased availability of pumped water in urban environments. Our models provide an initial approach to predicting the probability of BU presence over large spatial scales in Benin and Ghana, using readily available land use data.

Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

Energy Technology Data Exchange (ETDEWEB)

Mayr, Nina A., E-mail: Nina.Mayr@osumc.edu [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Huang Zhibin [Department of Radiation Oncology and Department of Physics, East Carolina University, Greenville, NC (United States); Wang, Jian Z. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Lo, Simon S. [Department of Radiation Oncology, Case Western Reserve University, Cleveland, OH (United States); Fan, Joline M. [Department of Molecular Biology, Stanford University, Stanford, CA (United States); Grecula, John C. [Department of Radiation Oncology, Ohio State University, Columbus, OH (United States); Sammet, Steffen [Department of Radiology, University of Chicago, Chicago, IL (United States); Department of Radiology, Ohio State University, Columbus, OH (United States); Sammet, Christina L. [Department of Radiology, University of Chicago, Chicago, IL (United States); Jia Guang; Zhang Jun; Knopp, Michael V.; Yuh, William T.C. [Department of Radiology, Ohio State University, Columbus, OH (United States)

2012-07-01

Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the total volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2

Validation of a CFD Analysis Model for Predicting CANDU-6 Moderator Temperature Against SPEL Experiments

International Nuclear Information System (INIS)

Churl Yoon; Bo Wook Rhee; Byung-Joo Min

2002-01-01

A validation of a 3D CFD model for predicting local subcooling of the moderator in the vicinity of calandria tubes in a CANDU-6 reactor is performed. The small scale moderator experiments performed at Sheridan Park Experimental Laboratory (SPEL) in Ontario, Canada[1] is used for the validation. Also a comparison is made between previous CFD analyses based on 2DMOTH and PHOENICS, and the current analysis for the same SPEL experiment. For the current model, a set of grid structures for the same geometry as the experimental test section is generated and the momentum, heat and continuity equations are solved by CFX-4.3, a CFD code developed by AEA technology. The matrix of calandria tubes is simplified by the porous media approach. The standard k-ε turbulence model associated with logarithmic wall treatment and SIMPLEC algorithm on the body fitted grid are used. Buoyancy effects are accounted for by the Boussinesq approximation. For the test conditions simulated in this study, the flow pattern identified is the buoyancy-dominated flow, which is generated by the interaction between the dominant buoyancy force by heating and inertial momentum forces by the inlet jets. As a result, the current CFD moderator analysis model predicts the moderator temperature reasonably, and the maximum error against the experimental data is kept at less than 2.0 deg. C over the whole domain. The simulated velocity field matches with the visualization of SPEL experiments quite well. (authors)

Predicted Aerodynamic Characteristics of a NACA 0015 Airfoil Having a 25% Integral-Type Trailing Edge Flap

Science.gov (United States)

Hassan, Ahmed

1999-01-01

Using the two-dimensional ARC2D Navier-Stokes flow solver analyses were conducted to predict the sectional aerodynamic characteristics of the flapped NACA-0015 airfoil section. To facilitate the analyses and the generation of the computational grids, the airfoil with the deflected trailing edge flap was treated as a single element airfoil with no allowance for a gap between the flap's leading edge and the base of the forward portion of the airfoil. Generation of the O-type computational grids was accomplished using the HYGRID hyperbolic grid generation program. Results were obtained for a wide range of Mach numbers, angles of attack and flap deflections. The predicted sectional lift, drag and pitching moment values for the airfoil were then cast in tabular format (C81) to be used in lifting-line helicopter rotor aerodynamic performance calculations. Similar were also generated for the flap. Mathematical expressions providing the variation of the sectional lift and pitching moment coefficients for the airfoil and for the flap as a function of flap chord length and flap deflection angle were derived within the context of thin airfoil theory. The airfoil's sectional drag coefficient were derived using the ARC2D drag predictions for equivalent two dimensional flow conditions.

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

The predictive value of markers of fibrinolysis and endothelial dysfunction in the post thrombotic syndrome. A systematic review.

Science.gov (United States)

Rabinovich, Anat; Cohen, Jacqueline M; Kahn, Susan R

2014-06-01

The post thrombotic syndrome (PTS) develops in 20-40% of deep venous thrombosis (DVT) patients. Risk factors for PTS have not been well elucidated. Identification of risk factors would facilitate individualised risk assessment for PTS. We conducted a systematic review to determine whether biomarkers of fibrinolysis or endothelial dysfunction can predict the risk for PTS among DVT patients. Studies were identified by searching the electronic databases PubMed, EMBASE, Scopus and Web of science. We included studies published between 1990 and 2013, measured biomarker levels in adult DVT patients, and reported rates of PTS development. Fourteen studies were included: 11 investigated the association between D-dimer and PTS; three examined fibrinogen; two measured von Willebrand factor; one measured plasminogen activator inhibitor-1; one assessed ADAMTS-13 (A Disintegrin and Metalloprotease with Thrombospondin type 1 repeats) and one measured factor XIII activity. Studies varied with regards to inclusion criteria, definition of PTS, time point and method of biomarker measurement. We were unable to meta-analyse results due to marked clinical heterogeneity. Descriptively, a significant association with PTS was found for D-dimer in four studies and factor XIII in one study. Further prospective research is needed to elucidate whether these markers might be useful to predict PTS development.

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

Chemical, laboratory analyses, physical and profile oceanographic data collected aboard the JACK FITZ in the Gulf of Mexico from 2010-06-12 to 2010-06-20 in response to the Deepwater Horizon Oil Spill event (NODC Accession 0069074)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Chemical, laboratory analyses, physical and profile oceanographic data were collected aboard the JACK FITZ in the Gulf of Mexico from 2010-06-12 to 2010-06-20 in...

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

The IEA Annex 20 Two-Dimensional Benchmark Test for CFD Predictions

DEFF Research Database (Denmark)

Nielsen, Peter V.; Rong, Li; Cortes, Ines Olmedo

2010-01-01

predictions both for isothermal flow and for nonisothermal flow. The benchmark is defined on a web page, which also shows about 50 different benchmark tests with studies of e.g. grid dependence, numerical schemes, different source codes, different turbulence models, RANS or LES, different turbulence levels...... in a supply opening, study of local emission and study of airborne chemical reactions. Therefore the web page is also a collection of information which describes the importance of the different elements of a CFD procedure. The benchmark is originally developed for test of two-dimensional flow, but the paper...

A critical pressure based panel method for prediction of unsteady loading of marine propellers under cavitation

International Nuclear Information System (INIS)

Liu, P.; Bose, N.; Colbourne, B.

2002-01-01

A simple numerical procedure is established and implemented into a time domain panel method to predict hydrodynamic performance of marine propellers with sheet cavitation. This paper describes the numerical formulations and procedures to construct this integration. Predicted hydrodynamic loads were compared with both a previous numerical model and experimental measurements for a propeller in steady flow. The current method gives a substantial improvement in thrust and torque coefficient prediction over a previous numerical method at low cavitation numbers of less than 2.0, where severe cavitation occurs. Predicted pressure coefficient distributions are also presented. (author)

Complete genome of a European hepatitis C virus subtype 1g isolate: phylogenetic and genetic analyses.

Science.gov (United States)

Bracho, Maria A; Saludes, Verónica; Martró, Elisa; Bargalló, Ana; González-Candelas, Fernando; Ausina, Vicent

2008-06-05

Hepatitis C virus isolates have been classified into six main genotypes and a variable number of subtypes within each genotype, mainly based on phylogenetic analysis. Analyses of the genetic relationship among genotypes and subtypes are more reliable when complete genome sequences (or at least the full coding region) are used; however, so far 31 of 80 confirmed or proposed subtypes have at least one complete genome available. Of these, 20 correspond to confirmed subtypes of epidemic interest. We present and analyse the first complete genome sequence of a HCV subtype 1g isolate. Phylogenetic and genetic distance analyses reveal that HCV-1g is the most divergent subtype among the HCV-1 confirmed subtypes. Potential genomic recombination events between genotypes or subtype 1 genomes were ruled out. We demonstrate phylogenetic congruence of previously deposited partial sequences of HCV-1g with respect to our sequence. In light of this, we propose changing the current status of its subtype-specific designation from provisional to confirmed.

A Traffic Prediction Algorithm for Street Lighting Control Efficiency

Directory of Open Access Journals (Sweden)

POPA Valentin

2013-01-01

Full Text Available This paper presents the development of a traffic prediction algorithm that can be integrated in a street lighting monitoring and control system. The prediction algorithm must enable the reduction of energy costs and improve energy efficiency by decreasing the light intensity depending on the traffic level. The algorithm analyses and processes the information received at the command center based on the traffic level at different moments. The data is collected by means of the Doppler vehicle detection sensors integrated within the system. Thus, two methods are used for the implementation of the algorithm: a neural network and a k-NN (k-Nearest Neighbor prediction algorithm. For 500 training cycles, the mean square error of the neural network is 9.766 and for 500.000 training cycles the error amounts to 0.877. In case of the k-NN algorithm the error increases from 8.24 for k=5 to 12.27 for a number of 50 neighbors. In terms of a root means square error parameter, the use of a neural network ensures the highest performance level and can be integrated in a street lighting control system.

Use of a portable X-ray analyser for manganese and iron assay in minerals

International Nuclear Information System (INIS)

Taqueda, M.H.S.; Agudo, E.G.

1975-01-01

The use of a protable X-ray fluorescence analyser for manganese and iron assay in minerals is described. The concentration range in the measured samples was 30% to 60% for Mn and 2% to 20% for Fe. The excitation source used was a 3 mCi 109 Cd sealed source. Balanced filters were used for the X-ray analysis. The statistical study of results showed a precision better than 0,5 for Mn, but only 4% for iron. They can be improved either increasing the counting time or using a 238 Pu source

A fast multichannel analyser

International Nuclear Information System (INIS)

Berry, A.; Przybylski, M.M.; Sumner, I.

1982-01-01

A fast multichannel analyser (MCA) capable of sampling at a rate of 10 7 s -1 has been developed. The instrument is based on an 8 bit parallel encoding analogue to digital converter (ADC) reading into a fast histogramming random access memory (RAM) system, giving 256 channels of 64 k count capacity. The prototype unit is in CAMAC format. (orig.)

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...

HbA1c and the Prediction of Type 2 Diabetes in Children and Adults.

Science.gov (United States)

Vijayakumar, Pavithra; Nelson, Robert G; Hanson, Robert L; Knowler, William C; Sinha, Madhumita

2017-01-01

Long-term data validating glycated hemoglobin (HbA 1c ) in assessing the risk of type 2 diabetes in children are limited. HbA 1c , fasting plasma glucose (FPG), and 2-h postload plasma glucose (2hPG) concentrations were measured in a longitudinal study of American Indians to determine their utility in predicting incident diabetes, all of which is thought to be type 2 in this population. Incident diabetes (FPG ≥126 mg/dL [7.0 mmol/L], 2hPG ≥200 mg/dL [11.1 mmol/L], HbA 1c ≥6.5% [8 mmol/mol], or clinical diagnosis) was determined in 2,095 children without diabetes ages 10-19 years monitored through age 39, and in 2,005 adults ages 20-39 monitored through age 59. Areas under the receiver operating characteristic (ROC) curve for HbA 1c , FPG, and 2hPG in predicting diabetes within 10 years were compared. During long-term follow-up of children and adolescents who did not initially have diabetes, the incidence rate of subsequent diabetes was fourfold (in boys) as high and more than sevenfold (in girls) as high in those with HbA 1c ≥5.7% as in those with HbA 1c ≤5.3%-greater rate ratios than experienced by adults in the same HbA 1c categories. Analyses of ROCs revealed no significant differences between HbA 1c , FPG, and 2hPG in sensitivity and specificity for identifying children and adolescents who later developed diabetes. HbA 1c is a useful predictor of diabetes risk in children and can be used to identify prediabetes in children with other type 2 diabetes risk factors with the same predictive value as FPG and 2hPG. © 2017 by the American Diabetes Association.

Analyser-based phase contrast image reconstruction using geometrical optics

International Nuclear Information System (INIS)

Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

2007-01-01

Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 μm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser

Introduction: Analysing Emotion and Theorising Affect

Directory of Open Access Journals (Sweden)

Peta Tait

2016-08-01

Full Text Available This discussion introduces ideas of emotion and affect for a volume of articles demonstrating the scope of approaches used in their study within the humanities and creative arts. The volume offers multiple perspectives on emotion and affect within 20th-century and 21st-century texts, arts and organisations and their histories. The discussion explains how emotion encompasses the emotions, emotional feeling, sensation and mood and how these can be analysed particularly in relation to literature, art and performance. It briefly summarises concepts of affect theory within recent approaches before introducing the articles.

A new approach to predicting environmental transfer of radionuclides to wildlife: A demonstration for freshwater fish and caesium

Energy Technology Data Exchange (ETDEWEB)

Beresford, N.A., E-mail: nab@ceh.ac.uk [NERC Centre for Ecology and Hydrology, Lancaster Environment Centre, Library Av. Bailrigg, Lancaster LA1 4AP (United Kingdom); Yankovich, T.L. [Saskatchewan Research Council, Environment and Forestry, 125, 15 Innovation Blvd., Saskatoon, SK S7N 2X8 (Canada); Wood, M.D. [School of Environment and Life Sciences, Room 323, Peel Building, University of Salford, Manchester, M5 4WT (United Kingdom); Fesenko, S. [International Atomic Energy Agency, 1400 Vienna (Austria); Andersson, P. [Strålsäkerhetsnymdigheten, Swedish Radiation Safety Authority, SE-171 16 Stockholm (Sweden); Muikku, M. [STUK, P.O. Box 14, 00881 Helsinki (Finland); Willey, N.J. [Centre for Research in Biosciences, University of the West of England, Coldharbour Lane, Frenchay, Bristol BS16 1QY (United Kingdom)

2013-10-01

The application of the concentration ratio (CR) to predict radionuclide activity concentrations in wildlife from those in soil or water has become the widely accepted approach for environmental assessments. Recently both the ICRP and IAEA have produced compilations of CR values for application in environmental assessment. However, the CR approach has many limitations, most notably, that the transfer of most radionuclides is largely determined by site-specific factors (e.g. water or soil chemistry). Furthermore, there are few, if any, CR values for many radionuclide-organism combinations. In this paper, we propose an alternative approach and, as an example, demonstrate and test this for caesium and freshwater fish. Using a Residual Maximum Likelihood (REML) mixed-model regression we analysed a dataset comprising 597 entries for 53 freshwater fish species from 67 sites. The REML analysis generated a mean value for each species on a common scale after REML adjustment taking account of the effect of the inter-site variation. Using an independent dataset, we subsequently test the hypothesis that the REML model outputs can be used to predict radionuclide, in this case radiocaesium, activity concentrations in unknown species from the results of a species which has been sampled at a specific site. The outputs of the REML analysis accurately predicted {sup 137}Cs activity concentrations in different species of fish from 27 Finnish lakes; these data had not been used in our initial analyses. We recommend that this alternative approach be further investigated for other radionuclides and ecosystems. - Highlights: • An alternative approach to estimating radionuclide transfer to wildlife is presented. • Analysed a dataset comprising 53 freshwater fish species collected from 67 sites. • Residual Maximum Likelihood mixed model regression is used. • Model output takes account of the effect of inter-site variation. • Successfully predicted {sup 137}Cs concentrations in

Predicting violence in veterans with posttraumatic stress disorder

Directory of Open Access Journals (Sweden)

Jovanović Aleksandar A.

2009-01-01

Full Text Available Background/Aim. Frequent expression of negative affects, hostility and violent behavior in individuals suffering from posttraumatic stress disorder (PTSD were recognized long ago, and have been retrospectively well documented in war veterans with PTSD who were shown to have an elevated risk for violent behavior when compared to both veterans without PTSD and other psychiatric patients. The aim of this study was to evaluate the accuracy of clinical prediction of violence in combat veterans suffering from PTSD. Methods. The subjects of this study, 104 male combat veterans with PTSD were assessed with the Historical, Clinical and Risk Management 20 (HCR-20, a 20-item clinicianrated instrument for assessing the risks for violence, and their acts of violence during one-year follow-up period were registered based on bimonthly check-up interviews. Results. Our findings showed that the HCR-20, as an actuarial measure, had good internal consistency reliability (α = 0.82, excellent interrater reliability (Interaclass Correlation ICC = 0.85, as well as excellent predictive validity for acts of any violence, non-physical violence or physical violence in the follow-up period (AUC = 0.82-0.86. The HCR-20 also had good interrater reliability (Cohen's kappa = 0.74, and acceptable predictive accuracy for each outcome criterion (AUC = 0.73-0.79. Conclusion. The results of this research confirm that the HCR-20 may also be applied in prediction of violent behavior in the population of patients suffering from PTSD with reliability and validity comparable with the results of previous studies where this instrument was administered to other populations of psychiatric patients.

Absence of back disorders in adults and work-related predictive factors in a 5-year perspective.

Science.gov (United States)

Reigo, T; Tropp, H; Timpka, T

2001-06-01

Factors important for avoiding back disorders in different age-groups have seldom been compared and studied over time. We therefore set out to study age-related differences in socio-economic and work-related factors associated with the absence of back disorders in a 5-year comparative cohort study using a mailed questionnaire. Two subgroups (aged 25-34 and 54-59 years) derived from a representative sample of the Swedish population were followed at baseline, 1 year and 5 years. Questions were asked about the duration of back pain episodes, relapses, work changes and work satisfaction. A work adaptability, partnership, growth, affection, resolve (APGAR) score was included in the final questionnaire. Multivariate logistic regression was used to identify factors predicting the absence of back disorders. Absence of physically heavy work predicted an absence of back disorders [odds ratio (OR), 2.86; 95% confidence interval (CI), 1.3-6.3] in the older group. In the younger age-group, the absence of stressful work predicted absence of back disorders (OR, 2.0; 95% CI, 1.1-3.6). Thirty-seven per cent of the younger age-group and 43% of the older age-group did not experience any back pain episodes during the study period. The exploratory work APGAR scores indicated that back disorders were only associated with lower work satisfaction in the older group. The analyses point out the importance of avoiding perceived psychological stress in the young and avoiding perceived physically heavy work in the older age-group for avoiding back disorders. The results suggest a need for different programmes at workplaces to avoid back disorders depending on the age of the employees concerned.

A History of Rotorcraft Comprehensive Analyses

Science.gov (United States)

Johnson, Wayne

2013-01-01

A history of the development of rotorcraft comprehensive analyses is presented. Comprehensive analyses are digital computer programs that calculate the aeromechanical behavior of the rotor and aircraft, bringing together the most advanced models of the geometry, structure, dynamics, and aerodynamics available in rotary wing technology. The development of the major codes of the last five decades from industry, government, and universities is described. A number of common themes observed in this history are discussed.

Approximate techniques for predicting size effects on cleavage fracture toughness (Jc)

International Nuclear Information System (INIS)

Kirk, M.T.; Dodds, R.H. Jr.

1993-07-01

This investigation examines the ability of an elastic T-stress analysis coupled with modified boundary layer (MBL) solution to predict stresses ahead of a crack tip in a variety of planar geometries. The approximate stresses are used as input to estimate the effective driving force for cleavage fracture (J 0 ) using the micromechanically based approach introduced by Dodds and Anderson. Finite element analyses for a wide variety of planar cracked geometries are conducted which have elastic biaxiality parameters (β) ranging from -0.99 (very low constraint) to +2.96 (very high constraint). The magnitude and sign of β indicate the rate at which crack-tip constraint changes with increasing applied load. All results pertain to a moderately strain hardening material (strain hardening exponent (η) of 10). These analyses suggest that β is an effective indicator of both the accuracy of T-MBL estimates of J 0 and of applicability limits on evolving fracture analysis methodologies (i.e. T-MBL, J-Q, and J/J 0 ). Specifically, when 1β1>0.4 these analyses show that the T-MBL approximation of J 0 is accurate to within 20% of a detailed finite-element analysis. As ''structural type'' configurations, i.e. shallow cracks in tension, generally have 1β1>0.4, it appears that only an elastic analysis may be needed to determine reasonably accurate J 0 values for structural conditions

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

Size matters. The width and location of a ureteral stone accurately predict the chance of spontaneous passage

Energy Technology Data Exchange (ETDEWEB)

Jendeberg, Johan; Geijer, Haakan; Alshamari, Muhammed; Liden, Mats [Oerebro University Hospital, Department of Radiology, Faculty of Medicine and Health, Oerebro (Sweden); Cierzniak, Bartosz [Oerebro University, Department of Surgery, Faculty of Medicine and Health, Oerebro (Sweden)

2017-11-15

To determine how to most accurately predict the chance of spontaneous passage of a ureteral stone using information in the diagnostic non-enhanced computed tomography (NECT) and to create predictive models with smaller stone size intervals than previously possible. Retrospectively 392 consecutive patients with ureteric stone on NECT were included. Three radiologists independently measured the stone size. Stone location, side, hydronephrosis, CRP, medical expulsion therapy (MET) and all follow-up radiology until stone expulsion or 26 weeks were recorded. Logistic regressions were performed with spontaneous stone passage in 4 weeks and 20 weeks as the dependent variable. The spontaneous passage rate in 20 weeks was 312 out of 392 stones, 98% in 0-2 mm, 98% in 3 mm, 81% in 4 mm, 65% in 5 mm, 33% in 6 mm and 9% in ≥6.5 mm wide stones. The stone size and location predicted spontaneous ureteric stone passage. The side and the grade of hydronephrosis only predicted stone passage in specific subgroups. Spontaneous passage of a ureteral stone can be predicted with high accuracy with the information available in the NECT. We present a prediction method based on stone size and location. (orig.)

Numerical analyses of a water pool under loadings caused by a condensation induced water hammer

Energy Technology Data Exchange (ETDEWEB)

Timperi, A.; Paettikangas, T.; Calonius, K.; Tuunanen, J.; Poikolainen, J.; Saarenheimo, A. [VTT Industrial Systems (Finland)

2004-03-01

Three-dimensional simulations of a rapidly condensing steam bubble in a water pool have been performed by using the commercial computational fluid dynamics (CFD) code Star-CD. The condensing bubble was modelled by using a mass sink in a single-phase calculation. The pressure load on the wall of the pool was determined and transferred to the structural analyses code ABAQUS. The analyses were done for a test pool at Lappeenranta University of Technology. The structural integrity of the pool during steam experiments was investigated by assuming as a test load the rapid condensation of a steam bubble with a diameter of 20 cm. The mass sink for modelling the collapse of the bubble was deter-mined from the potential theory of incompressible fluid. The rapid condensation of the bubble within 25 ms initiated a strong condensation water hammer. The maximum amplitude of the pressure load on the pool wall was approximately 300 kPa. The loads caused by the high compression waves lasted only about 0.4 ms. The loadings caused by larger bubbles or more rapid collapse could not be calculated with the present method. (au)

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.

The development of a model to predict the effects of worker and task factors on foot placements in manual material handling tasks.

Science.gov (United States)

Wagner, David W; Reed, Matthew P; Chaffin, Don B

2010-11-01

Accurate prediction of foot placements in relation to hand locations during manual materials handling tasks is critical for prospective biomechanical analysis. To address this need, the effects of lifting task conditions and anthropometric variables on foot placements were studied in a laboratory experiment. In total, 20 men and women performed two-handed object transfers that required them to walk to a shelf, lift an object from the shelf at waist height and carry the object to a variety of locations. Five different changes in the direction of progression following the object pickup were used, ranging from 45° to 180° relative to the approach direction. Object weights of 1.0 kg, 4.5 kg, 13.6 kg were used. Whole-body motions were recorded using a 3-D optical retro-reflective marker-based camera system. A new parametric system for describing foot placements, the Quantitative Transition Classification System, was developed to facilitate the parameterisation of foot placement data. Foot placements chosen by the subjects during the transfer tasks appeared to facilitate a change in the whole-body direction of progression, in addition to aiding in performing the lift. Further analysis revealed that five different stepping behaviours accounted for 71% of the stepping patterns observed. More specifically, the most frequently observed behaviour revealed that the orientation of the lead foot during the actual lifting task was primarily affected by the amount of turn angle required after the lift (R(2) = 0.53). One surprising result was that the object mass (scaled by participant body mass) was not found to significantly affect any of the individual step placement parameters. Regression models were developed to predict the most prevalent step placements and are included in this paper to facilitate more accurate human motion simulations and ergonomics analyses of manual material lifting tasks. STATEMENT OF RELEVANCE: This study proposes a method for parameterising the steps

A semi-supervised learning approach for RNA secondary structure prediction.

Science.gov (United States)

Yonemoto, Haruka; Asai, Kiyoshi; Hamada, Michiaki

2015-08-01

RNA secondary structure prediction is a key technology in RNA bioinformatics. Most algorithms for RNA secondary structure prediction use probabilistic models, in which the model parameters are trained with reliable RNA secondary structures. Because of the difficulty of determining RNA secondary structures by experimental procedures, such as NMR or X-ray crystal structural analyses, there are still many RNA sequences that could be useful for training whose secondary structures have not been experimentally determined. In this paper, we introduce a novel semi-supervised learning approach for training parameters in a probabilistic model of RNA secondary structures in which we employ not only RNA sequences with annotated secondary structures but also ones with unknown secondary structures. Our model is based on a hybrid of generative (stochastic context-free grammars) and discriminative models (conditional random fields) that has been successfully applied to natural language processing. Computational experiments indicate that the accuracy of secondary structure prediction is improved by incorporating RNA sequences with unknown secondary structures into training. To our knowledge, this is the first study of a semi-supervised learning approach for RNA secondary structure prediction. This technique will be useful when the number of reliable structures is limited. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Refractory CD20-positive peripheral T-cell lymphoma showing loss of CD20 expression after rituximab therapy and gain of CD20 expression after administration of vorinostat and gemcitabine].

Science.gov (United States)

Teshima, Kazuaki; Ohyagi, Hideaki; Kume, Masaaki; Takahashi, Satsuki; Saito, Masahiro; Takahashi, Naoto

A 79-year-old male patient presented with systemic lymphadenopathy. A lymph node biopsy revealed effacement of the normal nodal architecture with diffuse proliferation of medium-sized atypical lymphoid cells. Southern blot analyses demonstrated rearrangement of the T-cell receptor gene but not the immunoglobulin heavy chain gene. He was diagnosed with CD20-positive peripheral T-cell lymphoma (PTCL), NOS. Although he achieved partial remission after six cycles of R-CHOP, he relapse occurred after 2 months. CD20-negative conversion was confirmed in the lymph node, which was positive for CCR4, and the skin at the time of relapse. The patient received the GDP regimen as salvage therapy with the addition of vorinostat for skin involvement; however, he failed to respond, and the disease systemically progressed. Furthermore, he also exhibited progression in the skin after stopping vorinostat due to hematologic toxicity. A lymph node biopsy at progression revealed CD20 re-expression by immunohistochemistry. At progression, the patient received mogamulizumab but failed to respond, and he died owing to disease progression 8 months after relapse. In this case, we demonstrated CD20-negative conversion following rituximab and CD20-positive reversion after using vorinostat and gemcitabine.

Prediction of arterial oxygen partial pressure after changes in FIO₂: validation and clinical application of a novel formula.

Science.gov (United States)

Al-Otaibi, H M; Hardman, J G

2011-11-01

Existing methods allow prediction of Pa(O₂) during adjustment of Fi(O₂). However, these are cumbersome and lack sufficient accuracy for use in the clinical setting. The present studies aim to extend the validity of a novel formula designed to predict Pa(O₂) during adjustment of Fi(O₂) and to compare it with the current methods. Sixty-seven new data sets were collected from 46 randomly selected, mechanically ventilated patients. Each data set consisted of two subsets (before and 20 min after Fi(O₂) adjustment) and contained ventilator settings, pH, and arterial blood gas values. We compared the accuracy of Pa(O₂) prediction using a new formula (which utilizes only the pre-adjustment Pa(O₂) and pre- and post-adjustment Fi(O₂) with prediction using assumptions of constant Pa(O₂)/Fi(O₂) or constant Pa(O₂)/Pa(O₂). Subsequently, 20 clinicians predicted Pa(O₂) using the new formula and using Nunn's isoshunt diagram. The accuracy of the clinician's predictions was examined. The 95% limits of agreement (LA(95%)) between predicted and measured Pa(O₂) in the patient group were: new formula 0.11 (2.0) kPa, Pa(O₂)/Fi(O₂) -1.9 (4.4) kPa, and Pa(O₂)/Pa(O₂) -1.0 (3.6) kPa. The LA(95%) of clinicians' predictions of Pa(O₂) were 0.56 (3.6) kPa (new formula) and -2.7 (6.4) kPa (isoshunt diagram). The new formula's prediction of changes in Pa(O₂) is acceptably accurate and reliable and better than any other existing method. Its use by clinicians appears to improve accuracy over the most popular existing method. The simplicity of the new method may allow its regular use in the critical care setting.

Cost-of-illness studies and cost-effectiveness analyses in anxiety disorders: a systematic review.

Science.gov (United States)

Konnopka, Alexander; Leichsenring, Falk; Leibing, Eric; König, Hans-Helmut

2009-04-01

To review cost-of-illness studies (COI) and cost-effectiveness analyses (CEA) conducted for anxiety disorders. Based on a database search in Pubmed, PsychINFO and NHS EED, studies were classified according to various criteria. Cost data were inflated and converted to 2005 US-$ purchasing power parities (PPP). We finally identified 20 COI and 11 CEA of which most concentrated on panic disorder (PD) and generalized anxiety disorder (GAD). Differing inclusion of cost categories limited comparability of COI. PD and GAD tended to show higher direct costs per case, but lower direct cost per inhabitant than social and specific phobias. Different measures of effectiveness severely limited comparability of CEA. Overall CEA analysed 26 therapeutic or interventional strategies mostly compared to standard treatment, 8 of them resulting in lower better effectiveness and costs than the comparator. Anxiety disorders cause considerable costs. More research on phobias, more standardised inclusion of cost categories in COI and a wider use of comparable effectiveness measures (like QALYs) in CEA is needed.

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.

Self-Rated Activity Levels and Longevity: Evidence from a 20 Year Longitudinal Study

Science.gov (United States)

Mullee, Mark A.; Coleman, Peter G.; Briggs, Roger S. J.; Stevenson, James E.; Turnbull, Joanne C.

2008-01-01

The study reports on factors predicting the longevity of 328 people over the age of 65 drawn from an English city and followed over 20 years. Both the reported activities score and the individual's comparative evaluation of their own level of activity independently reduced the risk of death, even when health and cognitive status were taken into…

Kernel-based whole-genome prediction of complex traits: a review.

Science.gov (United States)

Morota, Gota; Gianola, Daniel

2014-01-01

Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways), thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

Kernel-based whole-genome prediction of complex traits: a review

Directory of Open Access Journals (Sweden)

Gota eMorota

2014-10-01

Full Text Available Prediction of genetic values has been a focus of applied quantitative genetics since the beginning of the 20th century, with renewed interest following the advent of the era of whole genome-enabled prediction. Opportunities offered by the emergence of high-dimensional genomic data fueled by post-Sanger sequencing technologies, especially molecular markers, have driven researchers to extend Ronald Fisher and Sewall Wright's models to confront new challenges. In particular, kernel methods are gaining consideration as a regression method of choice for genome-enabled prediction. Complex traits are presumably influenced by many genomic regions working in concert with others (clearly so when considering pathways, thus generating interactions. Motivated by this view, a growing number of statistical approaches based on kernels attempt to capture non-additive effects, either parametrically or non-parametrically. This review centers on whole-genome regression using kernel methods applied to a wide range of quantitative traits of agricultural importance in animals and plants. We discuss various kernel-based approaches tailored to capturing total genetic variation, with the aim of arriving at an enhanced predictive performance in the light of available genome annotation information. Connections between prediction machines born in animal breeding, statistics, and machine learning are revisited, and their empirical prediction performance is discussed. Overall, while some encouraging results have been obtained with non-parametric kernels, recovering non-additive genetic variation in a validation dataset remains a challenge in quantitative genetics.

Integration of meanline and one-dimensional methods for prediction of pulsating performance of a turbocharger turbine

International Nuclear Information System (INIS)

Chiong, M.S.; Rajoo, S.; Romagnoli, A.; Costall, A.W.; Martinez-Botas, R.F.

2014-01-01

Highlights: • Unsteady turbine performance prediction by integrating the 1-D and meanline models. • The optimum discretization length/diameter ratio is identified. • No improvement is gained by increasing the number of rotor entries. • The predicted instantaneous mass flow and output power are analysed in detail. - Abstract: Stringent emission regulations are driving engine manufacturers to increase investment into enabling technologies to achieve better specific fuel consumption, thermal efficiency and most importantly carbon reduction. Engine downsizing is seen as a key enabler to successfully achieve all of these requirements. Boosting through turbocharging is widely regarded as one of the most promising technologies for engine downsizing. However, the wide range of engine speeds and loads requires enhanced quality of engine-turbocharger matching, compared to the conventional approach which considers only the full load condition. Thus, development of computational models capable of predicting the unsteady behaviour of a turbocharger turbine is crucial to the overall matching process. A purely one-dimensional (1D) turbine model is capable of good unsteady swallowing capacity predictions, however it has not been fully exploited to predict instantaneous turbine power. On the contrary, meanline models (zero-dimensional) are regarded as a good tool to determine turbine efficiency in steady state but they do not include any information about the pressure wave action occurring within the turbine. This paper explores an alternative methodology to predict instantaneous turbine power and swallowing capacity by integrating one-dimensional and meanline models. A single entry mixed-flow turbine is modelled using a 1D gas dynamic code to solve the unsteady flow state in the volute, consequently used as the input for a meanline model to evaluate the instantaneous turbine power. The key in the effectiveness of this methodology relies on the synchronisation of the flow

[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.

Web 2.0 as a megatrend in eGovernment: An empirical analysis of its preconditions and outcomes

OpenAIRE

Plomp, M.G.A.; Te Velde, R.A.

2011-01-01

In recent years, Web 2.0 and social media were such an enormous hype, that today the popularity of these terms seems to be declining already. However, scientists and practitioners in (e)Goverment are still bothered by important questions, like: what is Web 2.0 and should we do something with it? In this paper, we give an extensive description of what Web 2.0 entails and to what degree it is really something ‘new’. Consequently, we analyse the critical preconditions and main outcomes of workin...

A Particle Swarm Optimization-Based Approach with Local Search for Predicting Protein Folding.

Science.gov (United States)

Yang, Cheng-Hong; Lin, Yu-Shiun; Chuang, Li-Yeh; Chang, Hsueh-Wei

2017-10-01

The hydrophobic-polar (HP) model is commonly used for predicting protein folding structures and hydrophobic interactions. This study developed a particle swarm optimization (PSO)-based algorithm combined with local search algorithms; specifically, the high exploration PSO (HEPSO) algorithm (which can execute global search processes) was combined with three local search algorithms (hill-climbing algorithm, greedy algorithm, and Tabu table), yielding the proposed HE-L-PSO algorithm. By using 20 known protein structures, we evaluated the performance of the HE-L-PSO algorithm in predicting protein folding in the HP model. The proposed HE-L-PSO algorithm exhibited favorable performance in predicting both short and long amino acid sequences with high reproducibility and stability, compared with seven reported algorithms. The HE-L-PSO algorithm yielded optimal solutions for all predicted protein folding structures. All HE-L-PSO-predicted protein folding structures possessed a hydrophobic core that is similar to normal protein folding.

[A prediction model for internet game addiction in adolescents: using a decision tree analysis].

Science.gov (United States)

Kim, Ki Sook; Kim, Kyung Hee

2010-06-01

This study was designed to build a theoretical frame to provide practical help to prevent and manage adolescent internet game addiction by developing a prediction model through a comprehensive analysis of related factors. The participants were 1,318 students studying in elementary, middle, and high schools in Seoul and Gyeonggi Province, Korea. Collected data were analyzed using the SPSS program. Decision Tree Analysis using the Clementine program was applied to build an optimum and significant prediction model to predict internet game addiction related to various factors, especially parent related factors. From the data analyses, the prediction model for factors related to internet game addiction presented with 5 pathways. Causative factors included gender, type of school, siblings, economic status, religion, time spent alone, gaming place, payment to Internet café, frequency, duration, parent's ability to use internet, occupation (mother), trust (father), expectations regarding adolescent's study (mother), supervising (both parents), rearing attitude (both parents). The results suggest preventive and managerial nursing programs for specific groups by path. Use of this predictive model can expand the role of school nurses, not only in counseling addicted adolescents but also, in developing and carrying out programs with parents and approaching adolescents individually through databases and computer programming.

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.

Prediction of Groundwater Arsenic Contamination using Geographic Information System and Artificial Neural Network

Directory of Open Access Journals (Sweden)

Md. Moqbul Hossain

2013-01-01

Full Text Available Ground water arsenic contamination is a well known health and environmental problem in Bangladesh. Sources of this heavy metal are known to be geogenic, however, the processes of its release into groundwater are poorly understood phenomena. In quest of mitigation of the problem it is necessary to predict probable contamination before it causes any damage to human health. Hence our research has been carried out to find the factor relations of arsenic contamination and develop an arsenic contamination prediction model. Researchers have generally agreed that the elevated concentration of arsenic is affected by several factors such as soil reaction (pH, organic matter content, geology, iron content, etc. However, the variability of concentration within short lateral and vertical intervals, and the inter-relationships of variables among themselves, make the statistical analyses highly non-linear and difficult to converge with a meaningful relationship. Artificial Neural Networks (ANN comes in handy for such a black box type problem. This research uses Back propagation Neural Networks (BPNN to train and validate the data derived from Geographic Information System (GIS spatial distribution grids. The neural network architecture with (6-20-1 pattern was able to predict the arsenic concentration with reasonable accuracy.

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.

Code manual for CONTAIN 2.0: A computer code for nuclear reactor containment analysis

International Nuclear Information System (INIS)

Murata, K.K.; Williams, D.C.; Griffith, R.O.; Gido, R.G.; Tadios, E.L.; Davis, F.J.; Martinez, G.M.; Washington, K.E.; Tills, J.

1997-12-01

The CONTAIN 2.0 computer code is an integrated analysis tool used for predicting the physical conditions, chemical compositions, and distributions of radiological materials inside a containment building following the release of material from the primary system in a light-water reactor accident. It can also predict the source term to the environment. CONTAIN 2.0 is intended to replace the earlier CONTAIN 1.12, which was released in 1991. The purpose of this Code Manual is to provide full documentation of the features and models in CONTAIN 2.0. Besides complete descriptions of the models, this Code Manual provides a complete description of the input and output from the code. CONTAIN 2.0 is a highly flexible and modular code that can run problems that are either quite simple or highly complex. An important aspect of CONTAIN is that the interactions among thermal-hydraulic phenomena, aerosol behavior, and fission product behavior are taken into account. The code includes atmospheric models for steam/air thermodynamics, intercell flows, condensation/evaporation on structures and aerosols, aerosol behavior, and gas combustion. It also includes models for reactor cavity phenomena such as core-concrete interactions and coolant pool boiling. Heat conduction in structures, fission product decay and transport, radioactive decay heating, and the thermal-hydraulic and fission product decontamination effects of engineered safety features are also modeled. To the extent possible, the best available models for severe accident phenomena have been incorporated into CONTAIN, but it is intrinsic to the nature of accident analysis that significant uncertainty exists regarding numerous phenomena. In those cases, sensitivity studies can be performed with CONTAIN by means of user-specified input parameters. Thus, the code can be viewed as a tool designed to assist the knowledge reactor safety analyst in evaluating the consequences of specific modeling assumptions

Code manual for CONTAIN 2.0: A computer code for nuclear reactor containment analysis

Energy Technology Data Exchange (ETDEWEB)

Murata, K.K.; Williams, D.C.; Griffith, R.O.; Gido, R.G.; Tadios, E.L.; Davis, F.J.; Martinez, G.M.; Washington, K.E. [Sandia National Labs., Albuquerque, NM (United States); Tills, J. [J. Tills and Associates, Inc., Sandia Park, NM (United States)

1997-12-01

The CONTAIN 2.0 computer code is an integrated analysis tool used for predicting the physical conditions, chemical compositions, and distributions of radiological materials inside a containment building following the release of material from the primary system in a light-water reactor accident. It can also predict the source term to the environment. CONTAIN 2.0 is intended to replace the earlier CONTAIN 1.12, which was released in 1991. The purpose of this Code Manual is to provide full documentation of the features and models in CONTAIN 2.0. Besides complete descriptions of the models, this Code Manual provides a complete description of the input and output from the code. CONTAIN 2.0 is a highly flexible and modular code that can run problems that are either quite simple or highly complex. An important aspect of CONTAIN is that the interactions among thermal-hydraulic phenomena, aerosol behavior, and fission product behavior are taken into account. The code includes atmospheric models for steam/air thermodynamics, intercell flows, condensation/evaporation on structures and aerosols, aerosol behavior, and gas combustion. It also includes models for reactor cavity phenomena such as core-concrete interactions and coolant pool boiling. Heat conduction in structures, fission product decay and transport, radioactive decay heating, and the thermal-hydraulic and fission product decontamination effects of engineered safety features are also modeled. To the extent possible, the best available models for severe accident phenomena have been incorporated into CONTAIN, but it is intrinsic to the nature of accident analysis that significant uncertainty exists regarding numerous phenomena. In those cases, sensitivity studies can be performed with CONTAIN by means of user-specified input parameters. Thus, the code can be viewed as a tool designed to assist the knowledge reactor safety analyst in evaluating the consequences of specific modeling assumptions.

Optimization of C20 isomers structure

International Nuclear Information System (INIS)

Ndjaka, J.M.B.; Charlier, J.C.

2001-07-01

We have performed geometry optimization of various possible planar and three-dimensional C 20 geometries. The planar structures considered include a linear chain, a monoclinic ring, and a bicyclic bow tie; while the three-dimensional geometric; consisted of a bowl or corranulene structure and a fullerene cage. In agreement with Wang et al MP2's calculations, our results predict the corranulene bowl to be the lowest energy structure. From the ground state geometry to the highest energy, considered C 20 structures, listed in increasing energy, are bowl, cage, bow tie, ring and chain. For the ring and bow tie isomers, the shape of the optimized structure deviates from that of the initial configuration; while the shape of the optimised bowl, cage and chain remain unchanged. (author)

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%.

VOC composition of current motor vehicle fuels and vapors, and collinearity analyses for receptor modeling.

Science.gov (United States)

Chin, Jo-Yu; Batterman, Stuart A

2012-03-01

The formulation of motor vehicle fuels can alter the magnitude and composition of evaporative and exhaust emissions occurring throughout the fuel cycle. Information regarding the volatile organic compound (VOC) composition of motor fuels other than gasoline is scarce, especially for bioethanol and biodiesel blends. This study examines the liquid and vapor (headspace) composition of four contemporary and commercially available fuels: gasoline (gasoline), ultra-low sulfur diesel (ULSD), and B20 (20% soy-biodiesel and 80% ULSD). The composition of gasoline and E85 in both neat fuel and headspace vapor was dominated by aromatics and n-heptane. Despite its low gasoline content, E85 vapor contained higher concentrations of several VOCs than those in gasoline vapor, likely due to adjustments in its formulation. Temperature changes produced greater changes in the partial pressures of 17 VOCs in E85 than in gasoline, and large shifts in the VOC composition. B20 and ULSD were dominated by C(9) to C(16)n-alkanes and low levels of the aromatics, and the two fuels had similar headspace vapor composition and concentrations. While the headspace composition predicted using vapor-liquid equilibrium theory was closely correlated to measurements, E85 vapor concentrations were underpredicted. Based on variance decomposition analyses, gasoline and diesel fuels and their vapors VOC were distinct, but B20 and ULSD fuels and vapors were highly collinear. These results can be used to estimate fuel related emissions and exposures, particularly in receptor models that apportion emission sources, and the collinearity analysis suggests that gasoline- and diesel-related emissions can be distinguished. Copyright © 2011 Elsevier Ltd. All rights reserved.