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Individual Models (individual + models)
Selected AbstractsGenetic correlations among and between wool, growth and reproduction traits in Merino sheepJOURNAL OF ANIMAL BREEDING AND GENETICS, Issue 2 2007E. Safari Summary Data from seven research resource flocks across Australia were combined to provide accurate estimates of genetic correlations among production traits in Merino sheep. The flocks represented contemporary Australian Merino fine, medium and broad wool strains over the past 30 years. Over 110 000 records were available for analysis for each of the major wool traits, and 50 000 records for reproduction and growth traits with over 2700 sires and 25 000 dams. Individual models developed from the single trait analyses were extended to the various combinations of two-trait models to obtain genetic correlations among six wool traits [clean fleece weight (CFW), greasy fleece weight, fibre diameter (FD), yield, coefficient of variation of fibre diameter and standard deviation of fibre diameter], four growth traits [birth weight, weaning weight, yearling weight (YWT), and hogget weight] and four reproduction traits [fertility, litter size, lambs born per ewe joined, lambs weaned per ewe joined (LW/EJ)]. This study has provided for the first time a comprehensive matrix of genetic correlations among these 14 wool, growth and reproduction traits. The large size of the data set has also provided estimates with very low standard errors. A moderate positive genetic correlation was observed between CFW and FD (0.29 ± 0.02). YWT was positively correlated with CFW (0.23 ± 0.04), FD (0.17 ± 0.04) and LWEJ (0.58 ± 0.06), while LW/EJ was negatively correlated with CFW (,0.26 ± 0.05) and positively correlated with FD (0.06 ± 0.04) and LS (0.68 ± 0.04). These genetic correlations, together with the estimates of heritability and other parameters provide the basis for more accurate prediction of outcomes in complex sheep-breeding programmes designed to improve several traits. [source] Using BiowinÔ, Bayes, and batteries to predict ready biodegradabilityENVIRONMENTAL TOXICOLOGY & CHEMISTRY, Issue 4 2004Robert S. Boethling Abstract Wether or not a given chemical substance is readily biodegradable is an important piece of information in risk screening for both new and existing chemicals. Despite the relatively low cost of Organization for Economic Cooperation and Development tests, data are often unavailable and biodegradability must be estimated. In this paper, we focus on the predictive value of selected BiowinÔ models and model batteries using Bayesian analysis. Posterior probabilities, calculated based on performance with the model training sets using Bayes' theorem, were closely matched by actual performance with an expanded set of 374 premanufacture notice (PMN) substances. Further analysis suggested that a simple battery consisting of Biowin3 (survey ultimate biodegradation model) and Biowin5 (Ministry of International Trade and Industry [MITI] linear model) would have enhanced predictive power in comparison to individual models. Application of the battery to PMN substances showed that performance matched expectation. This approach significantly reduced both false positives for ready biodegradability and the overall misclassification rate. Similar results were obtained for a set of 63 pharmaceuticals using a battery consisting of Biowin3 and Biowin6 (MITI nonlinear model). Biodegradation data for PMNs tested in multiple ready tests or both inherent and ready biodegradation tests yielded additional insights that may be useful in risk screening. [source] Towards a comprehensive computational model for the respiratory system,INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING, Issue 7 2010Wolfgang A. Wall Abstract This paper is concerned with computational modeling of the respiratory system against the background of acute lung diseases and mechanical ventilation. Conceptually, we divide the lung into two major subsystems, namely the conducting airways and the respiratory zone represented by lung parenchyma. Owing to their respective complexity, both parts are themselves out of range for a direct numerical simulation resolving all relevant length scales. Therefore, we develop detailed individual models for parts of the subsystems as a basis for novel multi-scale approaches taking into account the unresolved parts appropriately. In the tracheobronchial region, CT-based geometries up to a maximum of approximately seven generations are employed in fluid,structure interaction simulations, considering not only airway wall deformability but also the influence of surrounding lung tissue. Physiological outflow boundary conditions are derived by considering the impedance of the unresolved parts of the lung in a fully coupled 3D-1D approach. In the respiratory zone, an ensemble of alveoli representing a single ventilatory unit is modeled considering not only soft tissue behavior but also the influence of the covering surfactant film. Novel nested multi-scale procedures are then employed to simulate the dynamic behavior of lung parenchyma as a whole and local alveolar ensembles simultaneously without resolving the alveolar micro-structure completely. Copyright © 2010 John Wiley & Sons, Ltd. [source] Spanning the flow regimes: Generic fluidized-bed reactor modelAICHE JOURNAL, Issue 7 2003I. A. Abba Probabilistic averaging is used to model fluidized-bed reactors across the three fluidlization flow regimes most commonly encountered in industry (bubbling, turbulent, and fast fluidization), extending earlier work, which introduced this approach to bridge the bubbling and turbulent regimes of fluidization. In extending this concept to the fast fluidization regime, the probabilities of being in each of the three regimes are represented as probability density functions derived from regime boundary transition data. The three regime-specific models,a generalized version of a two-phase bubbling bed model at low gas velocities, a dispersed flow model for turbulent beds at intermediate velocities, and a generalized version of a core-annulus model at higher velocities,are employed, leading to improved predictions compared with any of the individual models, while avoiding discontinuities at the regime boundaries. Predictions from the new integrated model are in good agreement with available ozone decomposition data over the full range of applicability covered elsewhere. [source] Effect of Compromised Cortical Bone on Implant Load DistributionJOURNAL OF PROSTHODONTICS, Issue 8 2008vanç Akça DDS Abstract Purpose: To investigate photoelastically the difference in load distribution of dental implants with different implant neck designs in intact and compromised bone. Materials and Methods: Composite photoelastic models were fabricated using two different resins to simulate trabecular bone and a 1-mm thick layer of cortical bone. The following parallel-sided, threaded implants were centrally located in individual models representing intact and compromised cortical bone: Straumann (4.1-mm diameter × 12-mm length), AstraTech (4.0-mm diameter × 13-mm length), and 3i (3.75-mm diameter × 13-mm length). The compromised cortical bone condition was simulated by contaminating a 1-mm neck portion with Vaseline to impair the implant,resin interface. Vertical and oblique static loads were applied on the abutments, and the resulting stresses were monitored photoelastically and recorded photograhphically. Results: For the fully intact condition, the highest stresses were observed around the crest and apical region for all implant designs under vertical and inclined loads. There were no appreciable differences in magnitude or distribution between implant types. With compromised cortical bone, for all designs and load directions, higher stresses in the supporting structures were observed. Increased stresses were noted especially at the cortical bone,trabecular bone interface. Somewhat lower stress levels were observed with the 3i implant. Conclusions: The condition of implant,cortical bone contact has considerable influence on stress distribution. A compromised cortical bone condition caused higher level stresses for all implant designs tested. [source] Data fusion according to the principle of polyrepresentationJOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, Issue 4 2009Birger Larsen We report data fusion experiments carried out on the four best-performing retrieval models from TREC 5. Three were conceptually/algorithmically very different from one another; one was algorithmically similar to one of the former. The objective of the test was to observe the performance of the 11 logical data fusion combinations compared to the performance of the four individual models and their intermediate fusions when following the principle of polyrepresentation. This principle is based on cognitive IR perspective (Ingwersen & Järvelin, 2005) and implies that each retrieval model is regarded as a representation of a unique interpretation of information retrieval (IR). It predicts that only fusions of very different, but equally good, IR models may outperform each constituent as well as their intermediate fusions. Two kinds of experiments were carried out. One tested restricted fusions, which entails that only the inner disjoint overlap documents between fused models are ranked. The second set of experiments was based on traditional data fusion methods. The experiments involved the 30 TREC 5 topics that contain more than 44 relevant documents. In all tests, the Borda and CombSUM scoring methods were used. Performance was measured by precision and recall, with document cutoff values (DCVs) at 100 and 15 documents, respectively. Results show that restricted fusions made of two, three, or four cognitively/algorithmically very different retrieval models perform significantly better than do the individual models at DCV100. At DCV15, however, the results of polyrepresentative fusion were less predictable. The traditional fusion method based on polyrepresentation principles demonstrates a clear picture of performance at both DCV levels and verifies the polyrepresentation predictions for data fusion in IR. Data fusion improves retrieval performance over their constituent IR models only if the models all are quite conceptually/algorithmically dissimilar and equally and well performing, in that order of importance. [source] Effects of stem canker (Leptosphaeria maculans) and light leaf spot (Pyrenopeziza brassicae) on yield of winter oilseed rape (Brassica napus) in southern EnglandPLANT PATHOLOGY, Issue 4 2000Y. Zhou The relationships between yield loss and incidence or severity of stem canker and light leaf spot in winter oilseed rape were analysed by correlation and regression analyses, using data from experiments at Rothamsted, England in 1992/93, 1994/95 and 1995/96. Growth stages (GS) 6,3/6,4 and 4,0/4,5 were identified as the critical points for relating percentage yield loss to stem canker and light leaf spot (on stems), respectively. Critical point (CP) and area under disease progress curve (AUDPC) models relating percentage yield loss to combined incidence or severity of stem canker and light leaf spot (stems) in each experiment were constructed by linear regression. There were no differences in the CP models for incidence between 1992/93, 1994/95 and 1995/96 experiments, or in the AUDPC models for incidence between 1992/93 and 1994/95 experiments. Therefore, a general CP model relating percentage yield loss (,Y) to combined incidence of stem canker (Si) at GS 6,3/6,4 and light leaf spot (stems) (Li) at GS 4,0/4,5 was constructed using data from the three experiments: ,Y = 0·85 + 0·079Si + 0·065Li (R2 = 43·7%, P < 0·001, 92 df). A general AUDPC model relating ,Y to the AUDPC of combined incidence of stem canker (Sia) from GS 5·7 to GS 6·5 and light leaf spot (stems) (Lia) from GS 4·0 to GS 6·3 was constructed using data from the 1992/93 and 1994/95 experiments: ,Y = 0·07 + 0·00096Sia + 0·0026Lia (R2 = 43·6%, P < 0·001, 68 df). These two general yield-loss models were tested with data from Rothamsted in 1993/94 and Boxworth in 1992/93. The predictive accuracy of the CP model based on combined incidence of stem canker and light leaf spot (stems) was better than that of the AUDPC model. Yield losses predicted by summing the estimates from individual models for incidence of stem canker alone (GS 6,3/6,4) and light leaf spot alone (on leaves at GS 3,3) were greater than observed yield losses in experiments at Rothamsted in 1992/93, 1993/94, 1994/95 and 1995/96 and at Boxworth in 1992/93. [source] Local dynamic partial least squares approaches for the modelling of batch processesTHE CANADIAN JOURNAL OF CHEMICAL ENGINEERING, Issue 5 2008N. M. Fletcher Abstract The application of multivariate statistical projection based techniques has been recognized as one approach to contributing to an increased understanding of process behaviour. The key methodologies have included multi-way principal component analysis (PCA), multi-way partial least squares (PLS) and batch observation level analysis. Batch processes typically exhibit nonlinear, time variant behaviour and these characteristics challenge the aforementioned techniques. To address these challenges, dynamic PLS has been proposed to capture the process dynamics. Likewise approaches to removing the process nonlinearities have included the removal of the mean trajectory and the application of nonlinear PLS. An alternative approach is described whereby the batch trajectories are sub-divided into operating regions with a linear/linear dynamic model being fitted to each region. These individual models are spliced together to provide an overall nonlinear global model. Such a structure provides the potential for an alternative approach to batch process performance monitoring. In the paper a number of techniques are considered for developing the local model, including multi-way PLS and dynamic multi-way PLS. Utilising the most promising set of results from a simulation study of a batch process, the local model comprising individual linear dynamic PLS models was benchmarked against global nonlinear dynamic PLS using data from an industrial batch fermentation process. In conclusion the results for the local operating region techniques were comparable to the global model in terms of the residual sum of squares but for the global model structure was evident in the residuals. Consequently, the local modelling approach is statistically more robust. L'application de techniques basées sur la projection statistique multivariée est reconnue comme étant une approche qui contribue à une meilleure compréhension du comportement des procédés. Les méthodologies clés incluent l'analyse des composantes principales (PCA) à plusieurs critères de classification, les moindres carrés partiels (PLS) à plusieurs critères de classification et l'analyse des niveaux d'observation discontinus. Les procédés discontinus présentent typiquement un comportement non linéaire et variable dans le temps et ces caractéristiques mettent au défi les techniques mentionnées ci-dessus. Devant ces défis, la méthode PLS dynamique est proposée pour saisir la dynamique des procédés. Des approches semblables pour supprimer la non linéarité des procédés incluent le retrait de la trajectoire principale et l'application des PLS non linéaires. On décrit une autre approche où les trajectoires discontinues sont subdivisées en régions opératoires avec un modèle dynamique linéaire/linéaire adapté à chaque région. Ces modèles individuels sont raccordés pour obtenir un modèle non linéaire global. Une telle structure présente un potentiel pour une approche différente du suivi des performances des procédés discontinus. Dans cet article, plusieurs techniques sont considérées pour la mise au point du modèle local, incluant les PLS à plusieurs critères de classification et les PLS à plusieurs critères de classification dynamique. En utilisant la série de résultats les plus prometteurs d'une étude de simulation d'un procédé discontinu, le modèle local comprenant les modèles de PLS dynamiques linéaires individuels a été comparé à la méthode de PLS non linéaires dynamique globale utilisant des données d'un procédé de fermentation discontinu industriel. En conclusion, les résultats pour les techniques des régions opératoires locales sont comparables au modèle global en termes de somme des carrés des résidus mais pour le modèle global, la présence d'une structure dans les résidus est évidente. En conséquence, l'approche de modélisation locale est statistiquement plus robuste. [source] Stress Testing of Financial Industries: A Simple New Approach to Joint Stress Testing of Korean Banking, Securities, and Non-Life Insurance Industries,ASIA-PACIFIC JOURNAL OF FINANCIAL STUDIES, Issue 4 2009Kook-Hyun Chang Abstract This paper proposes a simple joint stress testing model useful in studying the effects of specific stress scenarios on a financial sector. In doing so, we adopt the principal component analysis (PCA) as a main device to interpret various financial information contained in figures and numbers on a financial company. We repeat the principal component analysis across different levels from individual company to a financial industry, and eventually to a financial sector as a whole to derive a financial sector risk index. We then link the sector risk index with stress macro variables, which constitute a much simpler task than devising individual models for each financial components. Once a relationship is established, a joint stress test is conducted by repeating PCA conversely. As a sample of stress scenario in the paper, we use the case of the 2003 credit card distress. We find that securities industry is more sensitive to market stresses than two other industries-bank and insurance-and that financial institutions in such a stress-sensitive industry are, consequently, more affected by the stresses than those in other industries. Despite the simplicity of the proposed model, this model is expected to provide substantial information, particularly for financial supervisors without having to build a complicated joint stress testing model. [source] The ,CaP Calculator': an online decision support tool for clinically localized prostate cancerBJU INTERNATIONAL, Issue 10 2010Matthew S. Katz Study Type , Prognosis (risk model) Level of Evidence 2a OBJECTIVE To design a decision-support tool to facilitate evidence-based treatment decisions in clinically localized prostate cancer, as individualized risk assessment and shared decision-making can decrease distress and decisional regret in patients with prostate cancer, but current individual models vary or only predict one outcome of interest. METHODS We searched Medline for previous reports and identified peer-reviewed articles providing pretreatment predictive models that estimated pathological stage and treatment outcomes in men with biopsy-confirmed, clinical T1-3 prostate cancer. Each model was entered into a spreadsheet to provide calculated estimates of extracapsular extension (ECE), seminal vesicle invasion (SVI), and lymph node involvement (LNI). Estimates of the prostate-specific antigen (PSA) outcome after radical prostatectomy (RP) or radiotherapy (RT), and clinical outcomes after RT, were also entered. The data are available at http://www.capcalculator.org. RESULTS Entering a patient's 2002 clinical T stage, Gleason score and pretreatment PSA level, and details from core biopsy findings, into the CaP Calculator provides estimates from predictive models of pathological extent of disease, four models for ECE, four for SVI and eight for LNI. The 5-year estimates of PSA relapse-free survival after RT and 10-year estimates after RP were available. A printout can be generated with individualized results for clinicians to review with each patient. CONCLUSIONS The CaP Calculator is a free, online ,clearing house' of several predictive models for prostate cancer, available in an accessible, user-friendly format. With further development and testing with patients, the CaP Calculator might be a useful decision-support tool to help doctors promote evidence-based shared decision-making in prostate cancer. [source] Modeling memory and perceptionCOGNITIVE SCIENCE - A MULTIDISCIPLINARY JOURNAL, Issue 3 2003Richard M. Shiffrin Abstract I present a framework for modeling memory, retrieval, perception, and their interactions. Recent versions of the models were inspired by Bayesian induction: We chose models that make optimal decisions conditioned on a memory/perceptual system with inherently noisy storage and retrieval. The resultant models are, fortunately, largely consistent with my models dating back to the 1960s, and are therefore natural successors. My recent articles have presented simplified models in order to focus on particular applications. This article takes a larger perspective and places the individual models in a more global framework. I will discuss (1) the storage of episodic traces, the accumulation of these into knowledge (e.g., lexical/semantic traces in the case of words), and the changes in knowledge caused by learning; (2) the retrieval of information from episodic memory and from general knowledge; (3) decisions concerning storage, retrieval, and responding. Examples of applications include episodic recognition and cued and free recall, perceptual identification (naming, yes,no and forced-choice), lexical decision, and long-term and short-term priming. [source] | ||||||||||||||||