Evidence of low molecular weight components in the organic matrix of the reef building coral, Stylophora pistillata.

Science.gov (United States)

Puverel, S; Houlbrèque, F; Tambutté, E; Zoccola, D; Payan, P; Caminiti, N; Tambutté, S; Allemand, D

2007-08-01

Biominerals contain both inorganic and organic components. Organic components are collectively termed the organic matrix, and this matrix has been reported to play a crucial role in mineralization. Several matrix proteins have been characterized in vertebrates, but only a few in invertebrates, primarily in Molluscs and Echinoderms. Methods classically used to extract organic matrix proteins eliminate potential low molecular weight matrix components, since cut-offs ranging from 3.5 to 10 kDa are used to desalt matrix extracts. Consequently, the presence of such components remains unknown and these are never subjected to further analyses. In the present study, we have used microcolonies from the Scleractinian coral Stylophora pistillata to study newly synthesized matrix components by labelling them with 14C-labelled amino acids. Radioactive matrix components were investigated by a method in which both total organic matrix and fractions of matrix below and above 5 kDa were analyzed. Using this method and SDS-PAGE analyses, we were able to detect the presence of low molecular mass matrix components (weight molecules, these probably form the bulk of newly synthesized organic matrix components. Our results suggest that these low molecular weight components may be peptides, which can be involved in the regulation of coral skeleton mineralization.

Perceived helpfulness of the individual components of a behavioural weight loss program: results from the Hopkins POWER Trial

OpenAIRE

Dalcin, A. T.; Jerome, G. J.; Fitzpatrick, S. L.; Louis, T. A.; Wang, N?Y.; Bennett, W. L.; Durkin, N.; Clark, J. M.; Daumit, G. L.; Appel, L. J.; Coughlin, J. W.

2015-01-01

Summary Background Behavioural weight loss programs are effective first?line treatments for obesity and are recommended by the US Preventive Services Task Force. Gaining an understanding of intervention components that are found helpful by different demographic groups can improve tailoring of weight loss programs. This paper examined the perceived helpfulness of different weight loss program components. Methods Participants (n?=?236) from the active intervention conditions of the Practice?bas...

Subsidence of a cementless femoral component influenced by body weight and body mass index.

Science.gov (United States)

Stihsen, Christoph; Radl, Roman; Keshmiri, Armin; Rehak, Peter; Windhager, Reinhard

2012-05-01

This trial was designed to evaluate the impact of physical characteristics such as body mass index, body weight and height on distal stem migration of a cementless femoral component, as the influence of obesity on the outcome of THA is still debated in literature and conflicting results have been found. In this retrospective cohort study, migration patterns for 102 implants were analysed using the Einzel-Bild-Roentgen-Analyse (EBRA-FCA, femoral component analysis). In all cases the Vision 2000 stem was implanted and combined with the Duraloc acetabular component (DePuy, Warsaw, Indiana). The mean follow-up was 93 months. EBRA-FCA evaluations revealed a mean subsidence of 1.38 mm after two years, 2.06 mm after five and 2.24 mm after seven years. Five stems loosened aseptically. Correlation between increased migration over the whole period and aseptic loosening was highly significant (p < 0.001). Surgical technique had a significant influence on migration and stem stability (p = 0.002) but physical patient characteristics such as body weight over 75 kg and height over 165 cm also significantly influenced stem subsidence towards progressive migration (p = 0.001, p < 0.001). However, a high BMI did not trigger progressive stem migration (p = 0.87). Being of the male gender raised the odds for increased migration (p = 0.03). Physical characteristics such as body weight and height showed significant influence on migration patterns of this cementless femoral component. The operating surgeon should be aware that body weight above 75 kg and height over 165 cm may trigger increased stem migration and the surgeon should aim to fit these prostheses as tightly as possible. However this study demonstrates that a high BMI does not trigger progressive stem migration. Further investigations are needed to confirm our findings.

Component Reification in Systems Modelling

DEFF Research Database (Denmark)

Bendisposto, Jens; Hallerstede, Stefan

When modelling concurrent or distributed systems in Event-B, we often obtain models where the structure of the connected components is specified by constants. Their behaviour is specified by the non-deterministic choice of event parameters for events that operate on shared variables. From a certain......? These components may still refer to shared variables. Events of these components should not refer to the constants specifying the structure. The non-deterministic choice between these components should not be via parameters. We say the components are reified. We need to address how the reified components get...... reflected into the original model. This reflection should indicate the constraints on how to connect the components....

Male pre- and post-pubertal castration effect on live weight, components of empty body weight, estimated nitrogen excretion and efficiency in Piemontese hypertrofic cattle

Directory of Open Access Journals (Sweden)

Davide Biagini

2011-04-01

Full Text Available To evaluate the effect of sexual neutering and age of castration on empty body weight (EBW components and estimated nitrogen excretion and efficiency, a trial was carried out on 3 groups of double-muscled Piemontese calves: early castrated (EC, 5th month of age, late castrated (LC, 12th month of age and intact males (IM, control group. Animals were fed at the same energy and protein level and slaughtered at 18th month of age. Live and slaughtering performances and EBW components were recorded, whereas N excretion was calculated by difference between diet and weight gain N content. In live and slaughtering performances, IM showed higher final, carcass and total meat weight than EC and LC (P<0.01. In EBW components, IM showed higher blood and head weight than EC and LC (P<0.01 and 0.05 respectively, and differences were found between EC and LC for head weights (P<0.01. IM showed higher body crude protein (BCP than EC and LC (P<0.01 and 0.05 respectively, but BCP/EBW ratio was higher only in IM than EC (P<0.05. Estimated N daily gain was higher in IM than EC and LC (P<0.01. Only LC showed higher excretion than IM (P<0.05, and N efficiency was higher in IM than EC and LC (P<0.05 and 0.01 respectively. In conclusion, for the Piemontese hypertrophied cattle castration significantly increases N excretion (+7% and reduces N efficiency (-15%, leading to a lower level of sustainability.

Attentional weights in vision as products of spatial and nonspatial components

DEFF Research Database (Denmark)

Nordfang, Maria; Staugaard, Camilla; Bundesen, Claus

2018-01-01

The relationship between visual attentional selection of items in particular spatial locations and selection by nonspatial criteria was investigated in a partial report experiment with report of letters (as many as possible) from brief postmasked exposures of circular arrays of letters and digits....... The data were fitted by mathematical models based on Bundesen's (Psychological Review, 97, 523-547, 1990) theory of visual attention (TVA). Both attentional weights of targets (letters) and attentional weights of distractors (digits) showed strong variations across the eight possible target locations......, but for each of the ten participants, the ratio of the weight of a distractor at a given location to the weight of a target at the same location was approximately constant. The results were accommodated by revising the weight equation of TVA such that the attentional weight of an object equals a product...

Structural equation modeling of latent growth curves of weight gain among treated tuberculosis patients.

Directory of Open Access Journals (Sweden)

Mahalingam Vasantha

Full Text Available Tuberculosis still remains a major public health problem even though it is treatable and curable. Weight gain measurement during anti tuberculosis (TB treatment period is an important component to assess the progress of TB patients. In this study, Latent Growth Models (LGMs were implemented in a longitudinal design to predict the change in weight of TB patients who were given three different regimens under randomized controlled clinical trial for anti-TB treatment. Linear and Quadratic LGMs were fitted using Mplus software. The age, sex and treatment response of the TB patients were used as time invariant independent variables of the growth trajectories. The quadratic trend was found to be better in explaining the changes in weight without grouping than the quadratic model for three group comparisons. A significant increase in the change of weight over time was identified while a significant quadratic effect indicated that weights were sustained over time. The growth rate was similar in both the groups. The treatment response had significant association with the growth rate of weight scores of the patients.

Component Composition Using Feature Models

DEFF Research Database (Denmark)

Eichberg, Michael; Klose, Karl; Mitschke, Ralf

2010-01-01

interface description languages. If this variability is relevant when selecting a matching component then human interaction is required to decide which components can be bound. We propose to use feature models for making this variability explicit and (re-)enabling automatic component binding. In our...... approach, feature models are one part of service specifications. This enables to declaratively specify which service variant is provided by a component. By referring to a service's variation points, a component that requires a specific service can list the requirements on the desired variant. Using...... these specifications, a component environment can then determine if a binding of the components exists that satisfies all requirements. The prototypical environment Columbus demonstrates the feasibility of the approach....

Geographically weighted regression model on poverty indicator

Science.gov (United States)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

Modeling and numerical simulation of multi-component flow in porous media

International Nuclear Information System (INIS)

Saad, B.

2011-01-01

This work deals with the modelization and numerical simulation of two phase multi-component flow in porous media. The study is divided into two parts. First we study and prove the mathematical existence in a weak sense of two degenerate parabolic systems modeling two phase (liquid and gas) two component (water and hydrogen) flow in porous media. In the first model, we assume that there is a local thermodynamic equilibrium between both phases of hydrogen by using the Henry's law. The second model consists of a relaxation of the previous model: the kinetic of the mass exchange between dissolved hydrogen and hydrogen in the gas phase is no longer instantaneous. The second part is devoted to the numerical analysis of those models. Firstly, we propose a numerical scheme to compare numerical solutions obtained with the first model and numerical solutions obtained with the second model where the characteristic time to recover the thermodynamic equilibrium goes to zero. Secondly, we present a finite volume scheme with a phase-by-phase upstream weighting scheme without simplified assumptions on the state law of gas densities. We also validate this scheme on a 2D test cases. (author)

The effect of weight management interventions that include a diet component on weight-related outcomes in pregnant and postpartum women: a systematic review protocol.

Science.gov (United States)

Spencer, Lisa; Rollo, Megan; Hauck, Yvonne; MacDonald-Wicks, Lesley; Wood, Lisa; Hutchesson, Melinda; Giglia, Roslyn; Smith, Roger; Collins, Clare

2015-01-01

What are the effects of weight management interventions that include a diet component on weight-related outcomes in pregnant and postpartum women?The primary objective of this systematic review is to evaluate the effectiveness of weight management interventions which include a diet component and are aimed at limiting gestational weight gain and postpartum weight retention in women.The second objective of this systematic review is to investigate included intervention components with respect to effect on weight-related outcomes. This may include, but is not limited to: length of intervention, use of face-to-face counselling, group or individual consultations, use of other interventions components including exercise, use of goals and use of support tools like food diaries, coaching, including email or text message support. Around half of all women of reproductive age are either overweight or obese, with women aged 25-34 years having a greater risk of substantial weight gain compared with men of all ages. Excessive gestational weight gain (GWG) and postpartum weight retention (PPWR) may play a significant role in long term obesity. Having one child doubles the five- and 10-year obesity incidence for women, with many women who gain excessive weight during pregnancy remaining obese permanently. Excessive GWG and/or PPWR can also significantly contribute to short- and long-term adverse health outcomes for mother, baby and future pregnancies.Maternal obesity increases the risk of pregnancy related complications such as pre-eclampsia, gestational diabetes mellitus, stillbirth and the rate of caesarean section. Childhood obesity is a further long term complication of maternal obesity for offspring, which may persist in to adulthood. Excess GWG is also a risk factor for PPWR both in the short and long-term. Nehring et al. conducted a meta-analysis with over 65,000 women showing that, compared to women who gained weight within recommendations during pregnancy, women with GWG

Health status monitoring for ICU patients based on locally weighted principal component analysis.

Science.gov (United States)

Ding, Yangyang; Ma, Xin; Wang, Youqing

2018-03-01

Intelligent status monitoring for critically ill patients can help medical stuff quickly discover and assess the changes of disease and then make appropriate treatment strategy. However, general-type monitoring model now widely used is difficult to adapt the changes of intensive care unit (ICU) patients' status due to its fixed pattern, and a more robust, efficient and fast monitoring model should be developed to the individual. A data-driven learning approach combining locally weighted projection regression (LWPR) and principal component analysis (PCA) is firstly proposed and applied to monitor the nonlinear process of patients' health status in ICU. LWPR is used to approximate the complex nonlinear process with local linear models, in which PCA could be further applied to status monitoring, and finally a global weighted statistic will be acquired for detecting the possible abnormalities. Moreover, some improved versions are developed, such as LWPR-MPCA and LWPR-JPCA, which also have superior performance. Eighteen subjects were selected from the Physiobank's Multi-parameter Intelligent Monitoring for Intensive Care II (MIMIC II) database, and two vital signs of each subject were chosen for online monitoring. The proposed method was compared with several existing methods including traditional PCA, Partial least squares (PLS), just in time learning combined with modified PCA (L-PCA), and Kernel PCA (KPCA). The experimental results demonstrated that the mean fault detection rate (FDR) of PCA can be improved by 41.7% after adding LWPR. The mean FDR of LWPR-MPCA was increased by 8.3%, compared with the latest reported method L-PCA. Meanwhile, LWPR spent less training time than others, especially KPCA. LWPR is first introduced into ICU patients monitoring and achieves the best monitoring performance including adaptability to changes in patient status, sensitivity for abnormality detection as well as its fast learning speed and low computational complexity. The algorithm

Skill and independence weighting for multi-model assessments

International Nuclear Information System (INIS)

Sanderson, Benjamin M.; Wehner, Michael; Knutti, Reto

2017-01-01

We present a weighting strategy for use with the CMIP5 multi-model archive in the fourth National Climate Assessment, which considers both skill in the climatological performance of models over North America as well as the inter-dependency of models arising from common parameterizations or tuning practices. The method exploits information relating to the climatological mean state of a number of projection-relevant variables as well as metrics representing long-term statistics of weather extremes. The weights, once computed can be used to simply compute weighted means and significance information from an ensemble containing multiple initial condition members from potentially co-dependent models of varying skill. Two parameters in the algorithm determine the degree to which model climatological skill and model uniqueness are rewarded; these parameters are explored and final values are defended for the assessment. The influence of model weighting on projected temperature and precipitation changes is found to be moderate, partly due to a compensating effect between model skill and uniqueness. However, more aggressive skill weighting and weighting by targeted metrics is found to have a more significant effect on inferred ensemble confidence in future patterns of change for a given projection.

Developing a Model Component

Science.gov (United States)

Fields, Christina M.

2013-01-01

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) was a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The initial purpose of the UCTS was to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The UCTS is designed with the capability of servicing future space vehicles; including all Space Station Requirements necessary for the MPLM Modules. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems during their development. As an intern at Kennedy Space Center (KSC), my assignment was to develop a model component for the UCTS. I was given a fluid component (dryer) to model in Simulink. I completed training for UNIX and Simulink. The dryer is a Catch All replaceable core type filter-dryer. The filter-dryer provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-dryer also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. The filter-dryer was modeled by determining affects it has on the pressure and velocity of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my filter-dryer model in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements. I participated in Simulation meetings and was involved in the subsystem design process and team collaborations. I gained valuable work experience and insight into a career path as an engineer.

Tribological Performance Optimization of Electroless Ni-P-W Coating Using Weighted Principal Component Analysis

Directory of Open Access Journals (Sweden)

S. Roy

2013-12-01

Full Text Available The present investigation is an experimental approach to deposit electroless Ni-P-W coating on mild steel substrate and find out the optimum combination of various tribological performances on the basis of minimum friction and wear, using weighted principal component analysis (WPCA. In this study three main tribological parameters are chosen viz. load (A, speed (B and time(C. The responses are coefficient of friction and wear depth. Here Weighted Principal Component Analysis (WPCA method is adopted to convert the multi-responses into single performance index called multiple performance index (MPI and Taguchi L27 orthogonal array is used to design the experiment and to find the optimum combination of tribological parameters for minimum coefficient of friction and wear depth. ANOVA is performed to find the significance of the each tribological process parameters and their interactions. The EDX analysis, SEM and XRD are performed to study the composition and structural aspects.

Genetic parameters for quail body weights using a random ...

African Journals Online (AJOL)

A model including fixed and random linear regressions is described for analyzing body weights at different ages. In this study, (co)variance components, heritabilities for quail weekly weights and genetic correlations among these weights were estimated using a random regression model by DFREML under DXMRR option.

Can model weighting improve probabilistic projections of climate change?

Energy Technology Data Exchange (ETDEWEB)

Raeisaenen, Jouni; Ylhaeisi, Jussi S. [Department of Physics, P.O. Box 48, University of Helsinki (Finland)

2012-10-15

Recently, Raeisaenen and co-authors proposed a weighting scheme in which the relationship between observable climate and climate change within a multi-model ensemble determines to what extent agreement with observations affects model weights in climate change projection. Within the Third Coupled Model Intercomparison Project (CMIP3) dataset, this scheme slightly improved the cross-validated accuracy of deterministic projections of temperature change. Here the same scheme is applied to probabilistic temperature change projection, under the strong limiting assumption that the CMIP3 ensemble spans the actual modeling uncertainty. Cross-validation suggests that probabilistic temperature change projections may also be improved by this weighting scheme. However, the improvement relative to uniform weighting is smaller in the tail-sensitive logarithmic score than in the continuous ranked probability score. The impact of the weighting on projection of real-world twenty-first century temperature change is modest in most parts of the world. However, in some areas mainly over the high-latitude oceans, the mean of the distribution is substantially changed and/or the distribution is considerably narrowed. The weights of individual models vary strongly with location, so that a model that receives nearly zero weight in some area may still get a large weight elsewhere. Although the details of this variation are method-specific, it suggests that the relative strengths of different models may be difficult to harness by weighting schemes that use spatially uniform model weights. (orig.)

Improving Stiffness-to-weight Ratio of Spot-welded Structures based upon Nonlinear Finite Element Modelling

Science.gov (United States)

Zhang, Shengyong

2017-07-01

Spot welding has been widely used for vehicle body construction due to its advantages of high speed and adaptability for automation. An effort to increase the stiffness-to-weight ratio of spot-welded structures is investigated based upon nonlinear finite element analysis. Topology optimization is conducted for reducing weight in the overlapping regions by choosing an appropriate topology. Three spot-welded models (lap, doubt-hat and T-shape) that approximate “typical” vehicle body components are studied for validating and illustrating the proposed method. It is concluded that removing underutilized material from overlapping regions can result in a significant increase in structural stiffness-to-weight ratio.

Generalized structured component analysis a component-based approach to structural equation modeling

CERN Document Server

Hwang, Heungsun

2014-01-01

Winner of the 2015 Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan Developed by the authors, generalized structured component analysis is an alternative to two longstanding approaches to structural equation modeling: covariance structure analysis and partial least squares path modeling. Generalized structured component analysis allows researchers to evaluate the adequacy of a model as a whole, compare a model to alternative specifications, and conduct complex analyses in a straightforward manner. Generalized Structured Component Analysis: A Component-Based Approach to Structural Equation Modeling provides a detailed account of this novel statistical methodology and its various extensions. The authors present the theoretical underpinnings of generalized structured component analysis and demonstrate how it can be applied to various empirical examples. The book enables quantitative methodologists, applied researchers, and practitioners to grasp the basic concepts behind this new a...

Expression-robust 3D face recognition via weighted sparse representation of multi-scale and multi-component local normal patterns

KAUST Repository

Li, Huibin

2014-06-01

In the theory of differential geometry, surface normal, as a first order surface differential quantity, determines the orientation of a surface at each point and contains informative local surface shape information. To fully exploit this kind of information for 3D face recognition (FR), this paper proposes a novel highly discriminative facial shape descriptor, namely multi-scale and multi-component local normal patterns (MSMC-LNP). Given a normalized facial range image, three components of normal vectors are first estimated, leading to three normal component images. Then, each normal component image is encoded locally to local normal patterns (LNP) on different scales. To utilize spatial information of facial shape, each normal component image is divided into several patches, and their LNP histograms are computed and concatenated according to the facial configuration. Finally, each original facial surface is represented by a set of LNP histograms including both global and local cues. Moreover, to make the proposed solution robust to the variations of facial expressions, we propose to learn the weight of each local patch on a given encoding scale and normal component image. Based on the learned weights and the weighted LNP histograms, we formulate a weighted sparse representation-based classifier (W-SRC). In contrast to the overwhelming majority of 3D FR approaches which were only benchmarked on the FRGC v2.0 database, we carried out extensive experiments on the FRGC v2.0, Bosphorus, BU-3DFE and 3D-TEC databases, thus including 3D face data captured in different scenarios through various sensors and depicting in particular different challenges with respect to facial expressions. The experimental results show that the proposed approach consistently achieves competitive rank-one recognition rates on these databases despite their heterogeneous nature, and thereby demonstrates its effectiveness and its generalizability. © 2014 Elsevier B.V.

Stochastic Modeling Of Wind Turbine Drivetrain Components

DEFF Research Database (Denmark)

Rafsanjani, Hesam Mirzaei; Sørensen, John Dalsgaard

2014-01-01

reliable components are needed for wind turbine. In this paper focus is on reliability of critical components in drivetrain such as bearings and shafts. High failure rates of these components imply a need for more reliable components. To estimate the reliability of these components, stochastic models...... are needed for initial defects and damage accumulation. In this paper, stochastic models are formulated considering some of the failure modes observed in these components. The models are based on theoretical considerations, manufacturing uncertainties, size effects of different scales. It is illustrated how...

Components in models of learning: Different operationalisations and relations between components

Directory of Open Access Journals (Sweden)

Mirkov Snežana

2013-01-01

Full Text Available This paper provides the presentation of different operationalisations of components in different models of learning. Special emphasis is on the empirical verifications of relations between components. Starting from the research of congruence between learning motives and strategies, underlying the general model of school learning that comprises different approaches to learning, we have analyzed the empirical verifications of factor structure of instruments containing the scales of motives and learning strategies corresponding to these motives. Considering the problems in the conceptualization of the achievement approach to learning, we have discussed the ways of operational sing the goal orientations and exploring their role in using learning strategies, especially within the model of the regulation of constructive learning processes. This model has served as the basis for researching learning styles that are the combination of a large number of components. Complex relations between the components point to the need for further investigation of the constructs involved in various models. We have discussed the findings and implications of the studies of relations between the components involved in different models, especially between learning motives/goals and learning strategies. We have analyzed the role of regulation in the learning process, whose elaboration, as indicated by empirical findings, can contribute to a more precise operationalisation of certain learning components. [Projekat Ministarstva nauke Republike Srbije, br. 47008: Unapređivanje kvaliteta i dostupnosti obrazovanja u procesima modernizacije Srbije i br. 179034: Od podsticanja inicijative, saradnje i stvaralaštva u obrazovanju do novih uloga i identiteta u društvu

Vehicle Weight in Gipps' Car-Following Model

OpenAIRE

Nerem, Sebastian

2013-01-01

Car-following models are mathematical models, which describe the situation where vehicles drive behind each other on a single lane road section with no overtaking possibilities. The purpose of the models is to estimate how a vehicle reacts to the behavior of the vehicle ahead. A weakness in these models is that they do not take the weight of each vehicle into account. It can however be shown that a vehicle?s weight affects its driving behavior.The purpose of this master?s thesis is to investi...

Modeling the degradation of nuclear components

International Nuclear Information System (INIS)

Stock, D.; Samanta, P.; Vesely, W.

1993-01-01

This paper describes component level reliability models that use information on degradation to predict component reliability, and which have been used to evaluate different maintenance and testing policies. The models are based on continuous time Markov processes, and are a generalization of reliability models currently used in Probabilistic Risk Assessment. An explanation of the models, the model parameters, and an example of how these models can be used to evaluate maintenance policies are discussed

The Exposure Effects of Online Model Pictures and Weight-Related Persuasive Messages on Women's Weight-Loss Planned Behaviors.

Science.gov (United States)

Pan, Wenjing; Peña, Jorge

2017-10-01

This study examined how exposure to pictures of women with different body sizes (thin, obese), physical attractiveness levels (attractive, unattractive), along with exposure to weight-related messages (pro-anorexia, anti-anorexia) embedded in a fashion website affected female participants' planned behavior toward weight loss. Participants exposed to attractive model pictures showed higher intentions, attitudes, and subjective norms to lose weight compared with unattractive models. Additionally, participants exposed to thin and attractive model pictures indicated the highest attitudes and self-efficacy to lose weight, whereas those exposed to thin and unattractive model pictures indicated the lowest. Furthermore, weight-related messages moderated the effect of model appearance (body size and attractiveness) on controllability of weight-loss activities. However, website pictures' body size differences had no main effects on planned behavior toward weight loss. These effects are discussed in the light of social comparison mechanisms.

A new model for the redundancy allocation problem with component mixing and mixed redundancy strategy

International Nuclear Information System (INIS)

Gholinezhad, Hadi; Zeinal Hamadani, Ali

2017-01-01

This paper develops a new model for redundancy allocation problem. In this paper, like many recent papers, the choice of the redundancy strategy is considered as a decision variable. But, in our model each subsystem can exploit both active and cold-standby strategies simultaneously. Moreover, the model allows for component mixing such that components of different types may be used in each subsystem. The problem, therefore, boils down to determining the types of components, redundancy levels, and number of active and cold-standby units of each type for each subsystem to maximize system reliability by considering such constraints as available budget, weight, and space. Since RAP belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed for solving the problem. Finally, the performance of the proposed algorithm is evaluated by applying it to a well-known test problem from the literature with relatively satisfactory results. - Highlights: • A new model for the redundancy allocation problem in series–parallel systems is proposed. • The redundancy strategy of each subsystem is considered as a decision variable and can be active, cold-standby or mixed. • Component mixing is allowed, in other words components of any subsystem can be non-identical. • A genetic algorithm is developed for solving the problem. • Computational experiments demonstrate that the new model leads to interesting results.

Effects of Plymetrics Training and Weight Training on selected Motor Ability Components among University Male Students

Science.gov (United States)

Shaikh, Alauddin; Mallick, Nazrul Islam

2012-11-01

Introduction: The aim of this study was to find out the effects of plyometrics training and weight training among university male students.Procedure: 60 male students from the different colleges of the Burdwan University were randomly selected as subjects and their age were 19-25 years served as Weight training Group (WTG), second group served as Plyometric Training Group (PTG) and the third group served as Control Group (CT). Eight weeks weight training and six weeks plyometric training were given for experiment accordingly. The control group was not given any training except of their routine. The selected subjects were measured of their motor ability components, speed, endurance, explosive power and agility. ANCOVA was calculation for statistical treatment.Finding: Plyometric training and weight training groups significantly increase speed, endurance, explosive power and agility.Conclusion: The plyometric training has significantly improved speed, explosive power, muscular endurance and agility. The weight training programme has significantly improved agility, muscular endurance, and explosive power. The plometric training is superior to weight training in improving explosive power, agility and muscular endurance.

A multivariate analysis of intrinsic soil components influencing the mean-weight diameter of water-stable aggregates

International Nuclear Information System (INIS)

Mbagwu, J.S.C.; Chukwu, W.I.E.

1994-06-01

A knowledge of the soil properties influencing the water-stability of soil aggregates is needed for selecting those more easily-determined properties that would be useful in areas where lack of facilities makes its direct determination impossible. In this laboratory study we evaluated the main soil physical, chemical and mineralogical properties influencing the stability of macro aggregates of some Italian surface soils in water. The objective is to select a subset of soil properties which predict optimally, soil aggregate stability. The index of stability used is the mean weight diameter of water-stable aggregates whereas the method of evaluation is the principal component analysis (PCA). The range in coefficients of variation (CV) among the properties was least in the physical (12.0-61.0%), medium in the mineralogical (28.0-116.2%) and highest in the chemical (8.2-110.8%) properties. The wider the range in CV in each subset of properties, the greater the number of components extracted by the PCA. The component defining variables, i.e. those with the highest loadings on each component and therefore, provide the best relationship between the variables and aggregate stability, revealed the ratio of total sand/clay and plastic limit as the significant physical properties. The significant chemical properties are Al 2 O 3 , FeO, MgO and MnO which contribute positively to aggregate stability. Feldspar, quartz and muscovite are the significant mineralogical properties each of which is negatively related to aggregate stability. These soil components are useful for developing empirical models for estimating the stability of aggregates of these soils in water. (author). 38 refs, 7 tabs

Layout design of user interface components with multiple objectives

Directory of Open Access Journals (Sweden)

Peer S.K.

2004-01-01

Full Text Available A multi-goal layout problem may be formulated as a Quadratic Assignment model, considering multiple goals (or factors, both qualitative and quantitative in the objective function. The facilities layout problem, in general, varies from the location and layout of facilities in manufacturing plant to the location and layout of textual and graphical user interface components in the human–computer interface. In this paper, we propose two alternate mathematical approaches to the single-objective layout model. The first one presents a multi-goal user interface component layout problem, considering the distance-weighted sum of congruent objectives of closeness relationships and the interactions. The second one considers the distance-weighted sum of congruent objectives of normalized weighted closeness relationships and normalized weighted interactions. The results of first approach are compared with that of an existing single objective model for example task under consideration. Then, the results of first approach and second approach of the proposed model are compared for the example task under consideration.

Genotype by environment interaction for 450-day weight of Nelore cattle analyzed by reaction norm models

Directory of Open Access Journals (Sweden)

Newton T. Pégolo

2009-01-01

Full Text Available Genotype by environment interactions (GEI have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450 Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM and random regression first order reaction norm models for six environmental variables: standard deviations of herd-year (RRMw and herd-year-season-management (RRMw-m groups for mean W450, standard deviations of herd-year (RRMg and herd-year-season-management (RRMg-m groups adjusted for 365-450 days weight gain (G450 averages, and two iterative algorithms using herd-year-season-management group solution estimates from a first RRMw-m and RRMg-m analysis (RRMITw-m and RRMITg-m, respectively. The RRM results showed similar tendencies in the variance components and heritability estimates along environmental gradient. Some of the variation among RRM estimates may have been related to the precision of the predictor and to correlations between environmental variables and the likely components of the weight trait. GEI, which was assessed by estimating the genetic correlation surfaces, had values < 0.5 between extreme environments in all models. Regression analyses showed that the correlation between the expected progeny differences for UM and the corresponding differences estimated by RRM was higher in intermediate and favorable environments than in unfavorable environments (p < 0.0001.

Long-term effects of a weight loss intervention with or without exercise component in postmenopausal women : A randomized trial

NARCIS (Netherlands)

de Roon, Martijn; van Gemert, Willemijn A; Peeters, Petra H; Schuit, A.J.; Monninkhof, Evelyn M

2017-01-01

The aim of this study was to determine the long-term effects of a weight loss intervention with or without an exercise component on body weight and physical activity. Women were randomized to diet (n = 97) or exercise (N = 98) for 16 weeks. During the intervention, both groups had achieved the set

Executive function in weight loss and weight loss maintenance: a conceptual review and novel neuropsychological model of weight control.

Science.gov (United States)

Gettens, Katelyn M; Gorin, Amy A

2017-10-01

Weight loss maintenance is a complex, multifaceted process that presents a significant challenge for most individuals who lose weight. A growing body of literature indicates a strong relationship between cognitive dysfunction and excessive body weight, and suggests that a subset of high-order cognitive processes known as executive functions (EF) likely play an important role in weight management. Recent reviews cover neuropsychological correlates of weight status yet fail to address the role of executive function in the central dilemma of successful weight loss maintenance. In this paper, we provide an overview of the existing literature examining executive functions as they relate to weight status and initial weight loss. Further, we propose a novel conceptual model of the relationships between EF, initial weight loss, and weight loss maintenance, mapping specific executive functions onto strategies known to be associated with both phases of the weight control process. Implications for the development of more efficacious weight loss maintenance interventions are discussed.

The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models

Science.gov (United States)

Koch, Julian; Cüneyd Demirel, Mehmet; Stisen, Simon

2018-05-01

The process of model evaluation is not only an integral part of model development and calibration but also of paramount importance when communicating modelling results to the scientific community and stakeholders. The modelling community has a large and well-tested toolbox of metrics to evaluate temporal model performance. In contrast, spatial performance evaluation does not correspond to the grand availability of spatial observations readily available and to the sophisticate model codes simulating the spatial variability of complex hydrological processes. This study makes a contribution towards advancing spatial-pattern-oriented model calibration by rigorously testing a multiple-component performance metric. The promoted SPAtial EFficiency (SPAEF) metric reflects three equally weighted components: correlation, coefficient of variation and histogram overlap. This multiple-component approach is found to be advantageous in order to achieve the complex task of comparing spatial patterns. SPAEF, its three components individually and two alternative spatial performance metrics, i.e. connectivity analysis and fractions skill score, are applied in a spatial-pattern-oriented model calibration of a catchment model in Denmark. Results suggest the importance of multiple-component metrics because stand-alone metrics tend to fail to provide holistic pattern information. The three SPAEF components are found to be independent, which allows them to complement each other in a meaningful way. In order to optimally exploit spatial observations made available by remote sensing platforms, this study suggests applying bias insensitive metrics which further allow for a comparison of variables which are related but may differ in unit. This study applies SPAEF in the hydrological context using the mesoscale Hydrologic Model (mHM; version 5.8), but we see great potential across disciplines related to spatially distributed earth system modelling.

Variance Component Quantitative Trait Locus Analysis for Body Weight Traits in Purebred Korean Native Chicken

Directory of Open Access Journals (Sweden)

Muhammad Cahyadi

2016-01-01

Full Text Available Quantitative trait locus (QTL is a particular region of the genome containing one or more genes associated with economically important quantitative traits. This study was conducted to identify QTL regions for body weight and growth traits in purebred Korean native chicken (KNC. F1 samples (n = 595 were genotyped using 127 microsatellite markers and 8 single nucleotide polymorphisms that covered 2,616.1 centi Morgan (cM of map length for 26 autosomal linkage groups. Body weight traits were measured every 2 weeks from hatch to 20 weeks of age. Weight of half carcass was also collected together with growth rate. A multipoint variance component linkage approach was used to identify QTLs for the body weight traits. Two significant QTLs for growth were identified on chicken chromosome 3 (GGA3 for growth 16 to18 weeks (logarithm of the odds [LOD] = 3.24, Nominal p value = 0.0001 and GGA4 for growth 6 to 8 weeks (LOD = 2.88, Nominal p value = 0.0003. Additionally, one significant QTL and three suggestive QTLs were detected for body weight traits in KNC; significant QTL for body weight at 4 weeks (LOD = 2.52, nominal p value = 0.0007 and suggestive QTL for 8 weeks (LOD = 1.96, Nominal p value = 0.0027 were detected on GGA4; QTLs were also detected for two different body weight traits: body weight at 16 weeks on GGA3 and body weight at 18 weeks on GGA19. Additionally, two suggestive QTLs for carcass weight were detected at 0 and 70 cM on GGA19. In conclusion, the current study identified several significant and suggestive QTLs that affect growth related traits in a unique resource pedigree in purebred KNC. This information will contribute to improving the body weight traits in native chicken breeds, especially for the Asian native chicken breeds.

Modeling of molecular weight and molecular weight distribution in slurry polymerization of propylene by Ziegler-Natta catalysts

International Nuclear Information System (INIS)

Khorasani, R.; Pourmahdian, S.

2007-01-01

The Precise prediction of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts needs good knowledge of parameters affecting on polymerization. molecular weight and molecular weight distribution are among important characteristics of a polymer determining physical-mechanical properties. broadening of molecular weight distribution is an important and well known characteristic of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts, So it is important to understand the origin of broad molecular weight. Two main factors in broadening molecular weight, namely mass transfer resistances and multiplicity of active sites, are discussed in this paper and a model including these factors is presented. Then we calculate molecular weight and molecular weight distribution by the model and compare our results with

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies.

Science.gov (United States)

Selimkhanov, Jangir; Thompson, W Clayton; Patterson, Terrell A; Hadcock, John R; Scott, Dennis O; Maurer, Tristan S; Musante, Cynthia J

2016-01-01

The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra) study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.

Evaluation of a Mathematical Model of Rat Body Weight Regulation in Application to Caloric Restriction and Drug Treatment Studies.

Directory of Open Access Journals (Sweden)

Jangir Selimkhanov

Full Text Available The purpose of this work is to develop a mathematical model of energy balance and body weight regulation that can predict species-specific response to common pre-clinical interventions. To this end, we evaluate the ability of a previously published mathematical model of mouse metabolism to describe changes in body weight and body composition in rats in response to two short-term interventions. First, we adapt the model to describe body weight and composition changes in Sprague-Dawley rats by fitting to data previously collected from a 26-day caloric restriction study. The calibrated model is subsequently used to describe changes in rat body weight and composition in a 23-day cannabinoid receptor 1 antagonist (CB1Ra study. While the model describes body weight data well, it fails to replicate body composition changes with CB1Ra treatment. Evaluation of a key model assumption about deposition of fat and fat-free masses shows a limitation of the model in short-term studies due to the constraint placed on the relative change in body composition components. We demonstrate that the model can be modified to overcome this limitation, and propose additional measurements to further test the proposed model predictions. These findings illustrate how mathematical models can be used to support drug discovery and development by identifying key knowledge gaps and aiding in the design of additional experiments to further our understanding of disease-relevant and species-specific physiology.

Tweaking the Four-Component Model

Science.gov (United States)

Curzer, Howard J.

2014-01-01

By maintaining that moral functioning depends upon four components (sensitivity, judgment, motivation, and character), the Neo-Kohlbergian account of moral functioning allows for uneven moral development within individuals. However, I argue that the four-component model does not go far enough. I offer a more accurate account of moral functioning…

Multi-objective optimization for generating a weighted multi-model ensemble

Science.gov (United States)

Lee, H.

2017-12-01

Many studies have demonstrated that multi-model ensembles generally show better skill than each ensemble member. When generating weighted multi-model ensembles, the first step is measuring the performance of individual model simulations using observations. There is a consensus on the assignment of weighting factors based on a single evaluation metric. When considering only one evaluation metric, the weighting factor for each model is proportional to a performance score or inversely proportional to an error for the model. While this conventional approach can provide appropriate combinations of multiple models, the approach confronts a big challenge when there are multiple metrics under consideration. When considering multiple evaluation metrics, it is obvious that a simple averaging of multiple performance scores or model ranks does not address the trade-off problem between conflicting metrics. So far, there seems to be no best method to generate weighted multi-model ensembles based on multiple performance metrics. The current study applies the multi-objective optimization, a mathematical process that provides a set of optimal trade-off solutions based on a range of evaluation metrics, to combining multiple performance metrics for the global climate models and their dynamically downscaled regional climate simulations over North America and generating a weighted multi-model ensemble. NASA satellite data and the Regional Climate Model Evaluation System (RCMES) software toolkit are used for assessment of the climate simulations. Overall, the performance of each model differs markedly with strong seasonal dependence. Because of the considerable variability across the climate simulations, it is important to evaluate models systematically and make future projections by assigning optimized weighting factors to the models with relatively good performance. Our results indicate that the optimally weighted multi-model ensemble always shows better performance than an arithmetic

Model dependence of energy-weighted sum rules

International Nuclear Information System (INIS)

Kirson, M.W.

1977-01-01

The contribution of the nucleon-nucleon interaction to energy-weighted sum rules for electromagnetic multipole transitions is investigated. It is found that only isoscalar electric transitions might have model-independent energy-weighted sum rules. For these transitions, explicit momentum and angular momentum dependence of the nuclear force give rise to corrections to the sum rule which are found to be negligibly small, thus confirming the model independence of these specific sum rules. These conclusions are unaffected by correlation effects. (author)

Estimating inverse probability weights using super learner when weight-model specification is unknown in a marginal structural Cox model context.

Science.gov (United States)

Karim, Mohammad Ehsanul; Platt, Robert W

2017-06-15

Correct specification of the inverse probability weighting (IPW) model is necessary for consistent inference from a marginal structural Cox model (MSCM). In practical applications, researchers are typically unaware of the true specification of the weight model. Nonetheless, IPWs are commonly estimated using parametric models, such as the main-effects logistic regression model. In practice, assumptions underlying such models may not hold and data-adaptive statistical learning methods may provide an alternative. Many candidate statistical learning approaches are available in the literature. However, the optimal approach for a given dataset is impossible to predict. Super learner (SL) has been proposed as a tool for selecting an optimal learner from a set of candidates using cross-validation. In this study, we evaluate the usefulness of a SL in estimating IPW in four different MSCM simulation scenarios, in which we varied the specification of the true weight model specification (linear and/or additive). Our simulations show that, in the presence of weight model misspecification, with a rich and diverse set of candidate algorithms, SL can generally offer a better alternative to the commonly used statistical learning approaches in terms of MSE as well as the coverage probabilities of the estimated effect in an MSCM. The findings from the simulation studies guided the application of the MSCM in a multiple sclerosis cohort from British Columbia, Canada (1995-2008), to estimate the impact of beta-interferon treatment in delaying disability progression. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices

KAUST Repository

Dutta, Aritra

2017-07-02

Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.

A Batch-Incremental Video Background Estimation Model using Weighted Low-Rank Approximation of Matrices

KAUST Repository

Dutta, Aritra; Li, Xin; Richtarik, Peter

2017-01-01

Principal component pursuit (PCP) is a state-of-the-art approach for background estimation problems. Due to their higher computational cost, PCP algorithms, such as robust principal component analysis (RPCA) and its variants, are not feasible in processing high definition videos. To avoid the curse of dimensionality in those algorithms, several methods have been proposed to solve the background estimation problem in an incremental manner. We propose a batch-incremental background estimation model using a special weighted low-rank approximation of matrices. Through experiments with real and synthetic video sequences, we demonstrate that our method is superior to the state-of-the-art background estimation algorithms such as GRASTA, ReProCS, incPCP, and GFL.

Time-Weighted Balanced Stochastic Model Reduction

DEFF Research Database (Denmark)

Tahavori, Maryamsadat; Shaker, Hamid Reza

2011-01-01

A new relative error model reduction technique for linear time invariant (LTI) systems is proposed in this paper. Both continuous and discrete time systems can be reduced within this framework. The proposed model reduction method is mainly based upon time-weighted balanced truncation and a recently...

Estimation of Genetic Variance Components Including Mutation and Epistasis using Bayesian Approach in a Selection Experiment on Body Weight in Mice

DEFF Research Database (Denmark)

Widyas, Nuzul; Jensen, Just; Nielsen, Vivi Hunnicke

Selection experiment was performed for weight gain in 13 generations of outbred mice. A total of 18 lines were included in the experiment. Nine lines were allotted to each of the two treatment diets (19.3 and 5.1 % protein). Within each diet three lines were selected upwards, three lines were...... selected downwards and three lines were kept as controls. Bayesian statistical methods are used to estimate the genetic variance components. Mixed model analysis is modified including mutation effect following the methods by Wray (1990). DIC was used to compare the model. Models including mutation effect...... have better fit compared to the model with only additive effect. Mutation as direct effect contributes 3.18% of the total phenotypic variance. While in the model with interactions between additive and mutation, it contributes 1.43% as direct effect and 1.36% as interaction effect of the total variance...

Integration of Simulink Models with Component-based Software Models

DEFF Research Database (Denmark)

Marian, Nicolae

2008-01-01

Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics...... of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical...... constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems) is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI), University of Southern Denmark. Once specified, the software model has...

Models for predicting objective function weights in prostate cancer IMRT

International Nuclear Information System (INIS)

Boutilier, Justin J.; Lee, Taewoo; Craig, Tim; Sharpe, Michael B.; Chan, Timothy C. Y.

2015-01-01

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Models for predicting objective function weights in prostate cancer IMRT

Energy Technology Data Exchange (ETDEWEB)

Boutilier, Justin J., E-mail: j.boutilier@mail.utoronto.ca; Lee, Taewoo [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8 (Canada); Craig, Tim [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9, Canada and Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Sharpe, Michael B. [Radiation Medicine Program, UHN Princess Margaret Cancer Centre, 610 University of Avenue, Toronto, Ontario M5T 2M9 (Canada); Department of Radiation Oncology, University of Toronto, 148 - 150 College Street, Toronto, Ontario M5S 3S2 (Canada); Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada); Chan, Timothy C. Y. [Department of Mechanical and Industrial Engineering, University of Toronto, 5 King’s College Road, Toronto, Ontario M5S 3G8, Canada and Techna Institute for the Advancement of Technology for Health, 124 - 100 College Street, Toronto, Ontario M5G 1P5 (Canada)

2015-04-15

Purpose: To develop and evaluate the clinical applicability of advanced machine learning models that simultaneously predict multiple optimization objective function weights from patient geometry for intensity-modulated radiation therapy of prostate cancer. Methods: A previously developed inverse optimization method was applied retrospectively to determine optimal objective function weights for 315 treated patients. The authors used an overlap volume ratio (OV) of bladder and rectum for different PTV expansions and overlap volume histogram slopes (OVSR and OVSB for the rectum and bladder, respectively) as explanatory variables that quantify patient geometry. Using the optimal weights as ground truth, the authors trained and applied three prediction models: logistic regression (LR), multinomial logistic regression (MLR), and weighted K-nearest neighbor (KNN). The population average of the optimal objective function weights was also calculated. Results: The OV at 0.4 cm and OVSR at 0.1 cm features were found to be the most predictive of the weights. The authors observed comparable performance (i.e., no statistically significant difference) between LR, MLR, and KNN methodologies, with LR appearing to perform the best. All three machine learning models outperformed the population average by a statistically significant amount over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and dose to the bladder, rectum, CTV, and PTV. When comparing the weights directly, the LR model predicted bladder and rectum weights that had, on average, a 73% and 74% relative improvement over the population average weights, respectively. The treatment plans resulting from the LR weights had, on average, a rectum V70Gy that was 35% closer to the clinical plan and a bladder V70Gy that was 29% closer, compared to the population average weights. Similar results were observed for all other clinical metrics. Conclusions: The authors demonstrated that the KNN and MLR

Application of the weighted total field-scattering field technique to 3D-PSTD light scattering model

Science.gov (United States)

Hu, Shuai; Gao, Taichang; Liu, Lei; Li, Hao; Chen, Ming; Yang, Bo

2018-04-01

PSTD (Pseudo Spectral Time Domain) is an excellent model for the light scattering simulation of nonspherical aerosol particles. However, due to the particularity of its discretization form of the Maxwell's equations, the traditional Total Field/Scattering Field (TF/SF) technique for FDTD (Finite Differential Time Domain) is not applicable to PSTD, and the time-consuming pure scattering field technique is mainly applied to introduce the incident wave. To this end, the weighted TF/SF technique proposed by X. Gao is generalized and applied to the 3D-PSTD scattering model. Using this technique, the incident light can be effectively introduced by modifying the electromagnetic components in an inserted connecting region between the total field and the scattering field region with incident terms, where the incident terms are obtained by weighting the incident field by a window function. To optimally determine the thickness of connection region and the window function type for PSTD calculations, their influence on the modeling accuracy is firstly analyzed. To further verify the effectiveness and advantages of the weighted TF/SF technique, the improved PSTD model is validated against the PSTD model equipped with pure scattering field technique in both calculation accuracy and efficiency. The results show that, the performance of PSTD seems to be not sensitive to variation of window functions. The number of the connection layer required decreases with the increasing of spatial resolution, where for spatial resolution of 24 grids per wavelength, a 6-layer region is thick enough. The scattering phase matrices and integral scattering parameters obtained by the improved PSTD show an excellent consistency with those well-tested models for spherical and nonspherical particles, illustrating that the weighted TF/SF technique can introduce the incident precisely. The weighted TF/SF technique shows higher computational efficiency than pure scattering technique.

The CHOP postnatal weight gain, birth weight, and gestational age retinopathy of prematurity risk model.

Science.gov (United States)

Binenbaum, Gil; Ying, Gui-Shuang; Quinn, Graham E; Huang, Jiayan; Dreiseitl, Stephan; Antigua, Jules; Foroughi, Negar; Abbasi, Soraya

2012-12-01

To develop a birth weight (BW), gestational age (GA), and postnatal-weight gain retinopathy of prematurity (ROP) prediction model in a cohort of infants meeting current screening guidelines. Multivariate logistic regression was applied retrospectively to data from infants born with BW less than 1501 g or GA of 30 weeks or less at a single Philadelphia hospital between January 1, 2004, and December 31, 2009. In the model, BW, GA, and daily weight gain rate were used repeatedly each week to predict risk of Early Treatment of Retinopathy of Prematurity type 1 or 2 ROP. If risk was above a cut-point level, examinations would be indicated. Of 524 infants, 20 (4%) had type 1 ROP and received laser treatment; 28 (5%) had type 2 ROP. The model (Children's Hospital of Philadelphia [CHOP]) accurately predicted all infants with type 1 ROP; missed 1 infant with type 2 ROP, who did not require laser treatment; and would have reduced the number of infants requiring examinations by 49%. Raising the cut point to miss one type 1 ROP case would have reduced the need for examinations by 79%. Using daily weight measurements to calculate weight gain rate resulted in slightly higher examination reduction than weekly measurements. The BW-GA-weight gain CHOP ROP model demonstrated accurate ROP risk assessment and a large reduction in the number of ROP examinations compared with current screening guidelines. As a simple logistic equation, it can be calculated by hand or represented as a nomogram for easy clinical use. However, larger studies are needed to achieve a highly precise estimate of sensitivity prior to clinical application.

Fault feature extraction method based on local mean decomposition Shannon entropy and improved kernel principal component analysis model

Directory of Open Access Journals (Sweden)

Jinlu Sheng

2016-07-01

Full Text Available To effectively extract the typical features of the bearing, a new method that related the local mean decomposition Shannon entropy and improved kernel principal component analysis model was proposed. First, the features are extracted by time–frequency domain method, local mean decomposition, and using the Shannon entropy to process the original separated product functions, so as to get the original features. However, the features been extracted still contain superfluous information; the nonlinear multi-features process technique, kernel principal component analysis, is introduced to fuse the characters. The kernel principal component analysis is improved by the weight factor. The extracted characteristic features were inputted in the Morlet wavelet kernel support vector machine to get the bearing running state classification model, bearing running state was thereby identified. Cases of test and actual were analyzed.

Data-Driven Robust RVFLNs Modeling of a Blast Furnace Iron-Making Process Using Cauchy Distribution Weighted M-Estimation

Energy Technology Data Exchange (ETDEWEB)

Zhou, Ping; Lv, Youbin; Wang, Hong; Chai, Tianyou

2017-09-01

Optimal operation of a practical blast furnace (BF) ironmaking process depends largely on a good measurement of molten iron quality (MIQ) indices. However, measuring the MIQ online is not feasible using the available techniques. In this paper, a novel data-driven robust modeling is proposed for online estimation of MIQ using improved random vector functional-link networks (RVFLNs). Since the output weights of traditional RVFLNs are obtained by the least squares approach, a robustness problem may occur when the training dataset is contaminated with outliers. This affects the modeling accuracy of RVFLNs. To solve this problem, a Cauchy distribution weighted M-estimation based robust RFVLNs is proposed. Since the weights of different outlier data are properly determined by the Cauchy distribution, their corresponding contribution on modeling can be properly distinguished. Thus robust and better modeling results can be achieved. Moreover, given that the BF is a complex nonlinear system with numerous coupling variables, the data-driven canonical correlation analysis is employed to identify the most influential components from multitudinous factors that affect the MIQ indices to reduce the model dimension. Finally, experiments using industrial data and comparative studies have demonstrated that the obtained model produces a better modeling and estimating accuracy and stronger robustness than other modeling methods.

An ontology for component-based models of water resource systems

Science.gov (United States)

Elag, Mostafa; Goodall, Jonathan L.

2013-08-01

Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.

Integration of Simulink Models with Component-based Software Models

Directory of Open Access Journals (Sweden)

MARIAN, N.

2008-06-01

Full Text Available Model based development aims to facilitate the development of embedded control systems by emphasizing the separation of the design level from the implementation level. Model based design involves the use of multiple models that represent different views of a system, having different semantics of abstract system descriptions. Usually, in mechatronics systems, design proceeds by iterating model construction, model analysis, and model transformation. Constructing a MATLAB/Simulink model, a plant and controller behavior is simulated using graphical blocks to represent mathematical and logical constructs and process flow, then software code is generated. A Simulink model is a representation of the design or implementation of a physical system that satisfies a set of requirements. A software component-based system aims to organize system architecture and behavior as a means of computation, communication and constraints, using computational blocks and aggregates for both discrete and continuous behavior, different interconnection and execution disciplines for event-based and time-based controllers, and so on, to encompass the demands to more functionality, at even lower prices, and with opposite constraints. COMDES (Component-based Design of Software for Distributed Embedded Systems is such a component-based system framework developed by the software engineering group of Mads Clausen Institute for Product Innovation (MCI, University of Southern Denmark. Once specified, the software model has to be analyzed. One way of doing that is to integrate in wrapper files the model back into Simulink S-functions, and use its extensive simulation features, thus allowing an early exploration of the possible design choices over multiple disciplines. The paper describes a safe translation of a restricted set of MATLAB/Simulink blocks to COMDES software components, both for continuous and discrete behavior, and the transformation of the software system into the S

Predictors of initial weight loss among women with abdominal obesity: a path model using self-efficacy and health-promoting behaviour.

Science.gov (United States)

Choo, Jina; Kang, Hyuncheol

2015-05-01

To identify predictors of initial weight loss among women with abdominal obesity by using a path model. Successful weight loss in the initial stages of long-term weight management may promote weight loss maintenance. A longitudinal study design. Study participants were 75 women with abdominal obesity, who were enrolled in a 12-month Community-based Heart and Weight Management Trial and followed until a 6-month assessment. The Weight Efficacy Lifestyle, Exercise Self-Efficacy and Health Promoting Lifestyle Profile-II measured diet self-efficacy, exercise self-efficacy and health-promoting behaviour respectively. All endogenous and exogenous variables used in our path model were change variables from baseline to 6 months. Data were collected between May 2011-May 2012. Based on the path model, increases in both diet and exercise self-efficacy had significant effects on increases in health-promoting behaviour. Increases in diet self-efficacy had a significant indirect effect on initial weight loss via increases in health-promoting behaviour. Increases in health-promoting behaviour had a significant effect on initial weight loss. Among women with abdominal obesity, increased diet self-efficacy and health-promoting behaviour were predictors of initial weight loss. A mechanism by which increased diet self-efficacy predicts initial weight loss may be partially attributable to health-promoting behavioural change. However, more work is still needed to verify causality. Based on the current findings, intensive nursing strategies for increasing self-efficacy for weight control and health-promoting behaviour may be essential components for better weight loss in the initial stage of a weight management intervention. © 2015 John Wiley & Sons Ltd.

Optimal design of condenser weight

International Nuclear Information System (INIS)

Zheng Jing; Yan Changqi; Wang Jianjun

2011-01-01

The condenser is an important component in nuclear power plants, which dimension and weight will effect the economical performance and the arrangement of the nuclear power plants. In this paper, the calculation model is established according to the design experience. The corresponding codes are also developed, and the sensitivity of design parameters which influence the condenser weight is analyzed. The present design optimization of the condenser, taking the weight minimization as the objective, is carried out with the self-developed complex-genetic algorithm. The results show that the reference condenser design is far from the best scheme, and also verify the feasibility of the complex-genetic algorithm. (authors)

Monitor-Based Statistical Model Checking for Weighted Metric Temporal Logic

DEFF Research Database (Denmark)

Bulychev, Petr; David, Alexandre; Larsen, Kim Guldstrand

2012-01-01

We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction with desi......We present a novel approach and implementation for ana- lysing weighted timed automata (WTA) with respect to the weighted metric temporal logic (WMTL≤ ). Based on a stochastic semantics of WTAs, we apply statistical model checking (SMC) to estimate and test probabilities of satisfaction...

A Multi-Component Day-Camp Weight-Loss Program Is Effective in Reducing BMI in Children after One Year

DEFF Research Database (Denmark)

Larsen, Kristian Traberg; Huang, Tao; Ried-Larsen, Mathias

2016-01-01

The objective of the present study was to evaluate the effectiveness of a one-year multi-component immersive day-camp weight-loss intervention for children with overweight and obesity. The study design was a parallel-group randomized controlled trial. One hundred fifteen 11-13-year-old children...

The Influence of Normalization Weight in Population Pharmacokinetic Covariate Models.

Science.gov (United States)

Goulooze, Sebastiaan C; Völler, Swantje; Välitalo, Pyry A J; Calvier, Elisa A M; Aarons, Leon; Krekels, Elke H J; Knibbe, Catherijne A J

2018-03-23

In covariate (sub)models of population pharmacokinetic models, most covariates are normalized to the median value; however, for body weight, normalization to 70 kg or 1 kg is often applied. In this article, we illustrate the impact of normalization weight on the precision of population clearance (CL pop ) parameter estimates. The influence of normalization weight (70, 1 kg or median weight) on the precision of the CL pop estimate, expressed as relative standard error (RSE), was illustrated using data from a pharmacokinetic study in neonates with a median weight of 2.7 kg. In addition, a simulation study was performed to show the impact of normalization to 70 kg in pharmacokinetic studies with paediatric or obese patients. The RSE of the CL pop parameter estimate in the neonatal dataset was lowest with normalization to median weight (8.1%), compared with normalization to 1 kg (10.5%) or 70 kg (48.8%). Typical clearance (CL) predictions were independent of the normalization weight used. Simulations showed that the increase in RSE of the CL pop estimate with 70 kg normalization was highest in studies with a narrow weight range and a geometric mean weight away from 70 kg. When, instead of normalizing with median weight, a weight outside the observed range is used, the RSE of the CL pop estimate will be inflated, and should therefore not be used for model selection. Instead, established mathematical principles can be used to calculate the RSE of the typical CL (CL TV ) at a relevant weight to evaluate the precision of CL predictions.

Frequency weighted model predictive control of wind turbine

DEFF Research Database (Denmark)

Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

2013-01-01

This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work are the rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...

Feature-based component model for design of embedded systems

Science.gov (United States)

Zha, Xuan Fang; Sriram, Ram D.

2004-11-01

An embedded system is a hybrid of hardware and software, which combines software's flexibility and hardware real-time performance. Embedded systems can be considered as assemblies of hardware and software components. An Open Embedded System Model (OESM) is currently being developed at NIST to provide a standard representation and exchange protocol for embedded systems and system-level design, simulation, and testing information. This paper proposes an approach to representing an embedded system feature-based model in OESM, i.e., Open Embedded System Feature Model (OESFM), addressing models of embedded system artifacts, embedded system components, embedded system features, and embedded system configuration/assembly. The approach provides an object-oriented UML (Unified Modeling Language) representation for the embedded system feature model and defines an extension to the NIST Core Product Model. The model provides a feature-based component framework allowing the designer to develop a virtual embedded system prototype through assembling virtual components. The framework not only provides a formal precise model of the embedded system prototype but also offers the possibility of designing variation of prototypes whose members are derived by changing certain virtual components with different features. A case study example is discussed to illustrate the embedded system model.

Using Avatars to Model Weight Loss Behaviors: Participant Attitudes and Technology Development

Science.gov (United States)

Napolitano, Melissa A.; Hayes, Sharon; Russo, Giuseppe; Muresu, Debora; Giordano, Antonio; Foster, Gary D.

2013-01-01

Background: Virtual reality and other avatar-based technologies are potential methods for demonstrating and modeling weight loss behaviors. This study examined avatar-based technology as a tool for modeling weight loss behaviors. Methods: This study consisted of two phases: (1) an online survey to obtain feedback about using avatars for modeling weight loss behaviors and (2) technology development and usability testing to create an avatar-based technology program for modeling weight loss behaviors. Results: Results of phase 1 (n = 128) revealed that interest was high, with 88.3% stating that they would participate in a program that used an avatar to help practice weight loss skills in a virtual environment. In phase 2, avatars and modules to model weight loss skills were developed. Eight women were recruited to participate in a 4-week usability test, with 100% reporting they would recommend the program and that it influenced their diet/exercise behavior. Most women (87.5%) indicated that the virtual models were helpful. After 4 weeks, average weight loss was 1.6 kg (standard deviation = 1.7). Conclusion: This investigation revealed a high level of interest in an avatar-based program, with formative work indicating promise. Given the high costs associated with in vivo exposure and practice, this study demonstrates the potential use of avatar-based technology as a tool for modeling weight loss behaviors. PMID:23911189

Feedback loops and temporal misalignment in component-based hydrologic modeling

Science.gov (United States)

Elag, Mostafa M.; Goodall, Jonathan L.; Castronova, Anthony M.

2011-12-01

In component-based modeling, a complex system is represented as a series of loosely integrated components with defined interfaces and data exchanges that allow the components to be coupled together through shared boundary conditions. Although the component-based paradigm is commonly used in software engineering, it has only recently been applied for modeling hydrologic and earth systems. As a result, research is needed to test and verify the applicability of the approach for modeling hydrologic systems. The objective of this work was therefore to investigate two aspects of using component-based software architecture for hydrologic modeling: (1) simulation of feedback loops between components that share a boundary condition and (2) data transfers between temporally misaligned model components. We investigated these topics using a simple case study where diffusion of mass is modeled across a water-sediment interface. We simulated the multimedia system using two model components, one for the water and one for the sediment, coupled using the Open Modeling Interface (OpenMI) standard. The results were compared with a more conventional numerical approach for solving the system where the domain is represented by a single multidimensional array. Results showed that the component-based approach was able to produce the same results obtained with the more conventional numerical approach. When the two components were temporally misaligned, we explored the use of different interpolation schemes to minimize mass balance error within the coupled system. The outcome of this work provides evidence that component-based modeling can be used to simulate complicated feedback loops between systems and guidance as to how different interpolation schemes minimize mass balance error introduced when components are temporally misaligned.

Model-integrating software components engineering flexible software systems

CERN Document Server

Derakhshanmanesh, Mahdi

2015-01-01

In his study, Mahdi Derakhshanmanesh builds on the state of the art in modeling by proposing to integrate models into running software on the component-level without translating them to code. Such so-called model-integrating software exploits all advantages of models: models implicitly support a good separation of concerns, they are self-documenting and thus improve understandability and maintainability and in contrast to model-driven approaches there is no synchronization problem anymore between the models and the code generated from them. Using model-integrating components, software will be

A Bayesian posterior predictive framework for weighting ensemble regional climate models

Directory of Open Access Journals (Sweden)

Y. Fan

2017-06-01

Full Text Available We present a novel Bayesian statistical approach to computing model weights in climate change projection ensembles in order to create probabilistic projections. The weight of each climate model is obtained by weighting the current day observed data under the posterior distribution admitted under competing climate models. We use a linear model to describe the model output and observations. The approach accounts for uncertainty in model bias, trend and internal variability, including error in the observations used. Our framework is general, requires very little problem-specific input, and works well with default priors. We carry out cross-validation checks that confirm that the method produces the correct coverage.

Weighted Distances in Scale-Free Configuration Models

Science.gov (United States)

Adriaans, Erwin; Komjáthy, Júlia

2018-01-01

In this paper we study first-passage percolation in the configuration model with empirical degree distribution that follows a power-law with exponent τ \\in (2,3) . We assign independent and identically distributed (i.i.d.) weights to the edges of the graph. We investigate the weighted distance (the length of the shortest weighted path) between two uniformly chosen vertices, called typical distances. When the underlying age-dependent branching process approximating the local neighborhoods of vertices is found to produce infinitely many individuals in finite time—called explosive branching process—Baroni, Hofstad and the second author showed in Baroni et al. (J Appl Probab 54(1):146-164, 2017) that typical distances converge in distribution to a bounded random variable. The order of magnitude of typical distances remained open for the τ \\in (2,3) case when the underlying branching process is not explosive. We close this gap by determining the first order of magnitude of typical distances in this regime for arbitrary, not necessary continuous edge-weight distributions that produce a non-explosive age-dependent branching process with infinite mean power-law offspring distributions. This sequence tends to infinity with the amount of vertices, and, by choosing an appropriate weight distribution, can be tuned to be any growing function that is O(log log n) , where n is the number of vertices in the graph. We show that the result remains valid for the the erased configuration model as well, where we delete loops and any second and further edges between two vertices.

Development of self-image and its components during a one-year follow-up in non-referred adolescents with excess and normal weight.

Science.gov (United States)

Mäkinen, Mauno; Marttunen, Mauri; Komulainen, Erkki; Terevnikov, Viacheslav; Puukko-Viertomies, Leena-Riitta; Aalberg, Veikko; Lindberg, Nina

2015-01-01

The proportion of overweight and obese youths is high. The present study aimed to investigate the development of self-image and its components during a one-year follow-up among non-referred adolescents with excess and normal weight. Furthermore, we separately analyzed the data for girls and boys. Altogether 86 8(th) grades (41 girls and 45 boys) with a relative weight of 26% or more above the median and 91 controls (43 girls and 48 boys) with normal weight participated the follow-up. The Offer Self-Image Questionnaire, Revised (OSIQ-R) was used to assess self-image at baseline and on follow-up. In the OSIQ-R, a low total raw score implies positive adjustment, while a high raw score implies poor adjustment and a negative self-image. The study design was doubly correlated (pairs and time), and a linear mixed model was used in the statistical analysis. In OSIQ-R total scores, a comparative improvement was observed in girls with normal weight. Among these girls, significant change scores compared to zero were seen in impulse control, social functioning, vocational attitudes, self-confidence, self-reliance, body image, sexuality, and ethical values. In girls with excess weight, none of the change scores compared to zero were statistically significant. When the girls with normal and excess weight were compared, the difference in change scores was largest in sexuality and vocational attitudes. Change scores compared to zero were significant in sexuality and idealism for boys with excess weight, and in impulse control, mental health, self-reliance, and sexuality for normal weight boys. When the boys with excess and normal weight were compared, no statistically significant differences emerged in change scores. In mid-adolescent girls, the influence of overweight and obesity on the development of self-image is substantial. Weight management programs directed at overweight adolescent girls should include psychological interventions aiming to diminish self-image distress

Efficient transfer of sensitivity information in multi-component models

International Nuclear Information System (INIS)

Abdel-Khalik, Hany S.; Rabiti, Cristian

2011-01-01

In support of adjoint-based sensitivity analysis, this manuscript presents a new method to efficiently transfer adjoint information between components in a multi-component model, whereas the output of one component is passed as input to the next component. Often, one is interested in evaluating the sensitivities of the responses calculated by the last component to the inputs of the first component in the overall model. The presented method has two advantages over existing methods which may be classified into two broad categories: brute force-type methods and amalgamated-type methods. First, the presented method determines the minimum number of adjoint evaluations for each component as opposed to the brute force-type methods which require full evaluation of all sensitivities for all responses calculated by each component in the overall model, which proves computationally prohibitive for realistic problems. Second, the new method treats each component as a black-box as opposed to amalgamated-type methods which requires explicit knowledge of the system of equations associated with each component in order to reach the minimum number of adjoint evaluations. (author)

Weighted-indexed semi-Markov models for modeling financial returns

International Nuclear Information System (INIS)

D’Amico, Guglielmo; Petroni, Filippo

2012-01-01

In this paper we propose a new stochastic model based on a generalization of semi-Markov chains for studying the high frequency price dynamics of traded stocks. We assume that the financial returns are described by a weighted-indexed semi-Markov chain model. We show, through Monte Carlo simulations, that the model is able to reproduce important stylized facts of financial time series such as the first-passage-time distributions and the persistence of volatility. The model is applied to data from the Italian and German stock markets from 1 January 2007 until the end of December 2010. (paper)

Weight management in community pharmacy: what do the experts think?

Science.gov (United States)

Um, Irene S; Armour, Carol; Krass, Ines; Gill, Timothy; Chaar, Betty B

2013-06-01

The increasing prevalence of obesity and overweight adults creates a significant public health burden and there is great potential for pharmacists to be involved in the provision of weight management services, other than the mundane supply of commercial products. In order to provide optimal services that can be integrated into the healthcare system, a best practice model for weight management services in community pharmacy should be in place. We sought experts' and key stakeholders' opinions on this matter. (1) To identify components of a best practice model of a weight management service feasible in Australian community pharmacy. (2) To identify the role of pharmacists and the training requirements to up-skill pharmacists to competently provide weight management services. (3) To elicit any practical suggestions that would contribute to successful implementation of weight management services in pharmacy. Australian primary care sector. Semi-structured interviews were conducted with a purposive sample of 12 participants including Australian experts in obesity and representatives of main Australian professional organisations in pharmacy. Interviews were digitally recorded, transcribed verbatim and thematically analysed using the framework approach. Recommended components of pharmacy-based weight management services and training requirements. Participants perceived two potential roles for pharmacists involved in weight management: health promotion and individualised service. Multi-component interventions targeting all three areas: diet, physical activity and behaviour change were emphasised. Physical assessment (e.g. weight, waist circumference measurements), goal setting, referral to allied healthcare professionals and on-going support for weight maintenance were also proposed. Participants suggested pharmacists should undergo formal training and identified various training topics to improve pharmacists' knowledge, attributes and skills to acquire competencies

Pump Component Model in SPACE Code

International Nuclear Information System (INIS)

Kim, Byoung Jae; Kim, Kyoung Doo

2010-08-01

This technical report describes the pump component model in SPACE code. A literature survey was made on pump models in existing system codes. The models embedded in SPACE code were examined to check the confliction with intellectual proprietary rights. Design specifications, computer coding implementation, and test results are included in this report

Mindfulness Approaches and Weight Loss, Weight Maintenance, and Weight Regain.

Science.gov (United States)

Dunn, Carolyn; Haubenreiser, Megan; Johnson, Madison; Nordby, Kelly; Aggarwal, Surabhi; Myer, Sarah; Thomas, Cathy

2018-03-01

There is an urgent need for effective weight management techniques, as more than one third of US adults are overweight or obese. Recommendations for weight loss include a combination of reducing caloric intake, increasing physical activity, and behavior modification. Behavior modification includes mindful eating or eating with awareness. The purpose of this review was to summarize the literature and examine the impact of mindful eating on weight management. The practice of mindful eating has been applied to the reduction of food cravings, portion control, body mass index, and body weight. Past reviews evaluating the relationship between mindfulness and weight management did not focus on change in mindful eating as the primary outcome or mindful eating as a measured variable. This review demonstrates strong support for inclusion of mindful eating as a component of weight management programs and may provide substantial benefit to the treatment of overweight and obesity.

How Many Separable Sources? Model Selection In Independent Components Analysis

DEFF Research Database (Denmark)

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though....../Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from...... might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian....

How Many Separable Sources? Model Selection In Independent Components Analysis

Science.gov (United States)

Woods, Roger P.; Hansen, Lars Kai; Strother, Stephen

2015-01-01

Unlike mixtures consisting solely of non-Gaussian sources, mixtures including two or more Gaussian components cannot be separated using standard independent components analysis methods that are based on higher order statistics and independent observations. The mixed Independent Components Analysis/Principal Components Analysis (mixed ICA/PCA) model described here accommodates one or more Gaussian components in the independent components analysis model and uses principal components analysis to characterize contributions from this inseparable Gaussian subspace. Information theory can then be used to select from among potential model categories with differing numbers of Gaussian components. Based on simulation studies, the assumptions and approximations underlying the Akaike Information Criterion do not hold in this setting, even with a very large number of observations. Cross-validation is a suitable, though computationally intensive alternative for model selection. Application of the algorithm is illustrated using Fisher's iris data set and Howells' craniometric data set. Mixed ICA/PCA is of potential interest in any field of scientific investigation where the authenticity of blindly separated non-Gaussian sources might otherwise be questionable. Failure of the Akaike Information Criterion in model selection also has relevance in traditional independent components analysis where all sources are assumed non-Gaussian. PMID:25811988

Implementasi Perbandingan Metode Simple Additive Weighting Dengan Weighted Sum Model Dalam Pemilihan Siswa Berprestasi

OpenAIRE

Siregar, M. Fajrul Falah

2015-01-01

Good Performance Student Selection Program of MIN Tanjung Sari aims to increase students interest in learning. The selection is based on determined criterion. To assist the selection process, then a decision support system is needed. The method used is Simple Additive Weighting and Weighted Sum Model. In this research the results of both methods performed will be tested with the three periods of good performance students data possessed by MIN Tanjung Sari Medan Selayang. This s...

A principal components model of soundscape perception.

Science.gov (United States)

Axelsson, Östen; Nilsson, Mats E; Berglund, Birgitta

2010-11-01

There is a need for a model that identifies underlying dimensions of soundscape perception, and which may guide measurement and improvement of soundscape quality. With the purpose to develop such a model, a listening experiment was conducted. One hundred listeners measured 50 excerpts of binaural recordings of urban outdoor soundscapes on 116 attribute scales. The average attribute scale values were subjected to principal components analysis, resulting in three components: Pleasantness, eventfulness, and familiarity, explaining 50, 18 and 6% of the total variance, respectively. The principal-component scores were correlated with physical soundscape properties, including categories of dominant sounds and acoustic variables. Soundscape excerpts dominated by technological sounds were found to be unpleasant, whereas soundscape excerpts dominated by natural sounds were pleasant, and soundscape excerpts dominated by human sounds were eventful. These relationships remained after controlling for the overall soundscape loudness (Zwicker's N(10)), which shows that 'informational' properties are substantial contributors to the perception of soundscape. The proposed principal components model provides a framework for future soundscape research and practice. In particular, it suggests which basic dimensions are necessary to measure, how to measure them by a defined set of attribute scales, and how to promote high-quality soundscapes.

Estimation of genotype X environment interactions, in a grassbased system, for milk yield, body condition score,and body weight using random regression models

NARCIS (Netherlands)

Berry, D.P.; Buckley, F.; Dillon, P.; Evans, R.D.; Rath, M.; Veerkamp, R.F.

2003-01-01

(Co)variance components for milk yield, body condition score (BCS), body weight (BW), BCS change and BW change over different herd-year mean milk yields (HMY) and nutritional environments (concentrate feeding level, grazing severity and silage quality) were estimated using a random regression model.

Determination of Weight Suspension Rigidity in the Transport-Erector Aggregates

Directory of Open Access Journals (Sweden)

V. A. Zverev

2016-01-01

Full Text Available The aim is to determine weight suspension rigidity in aggregates designed to perform technological transport-erector operations at the miscellaneous launch complexes.We consider the weight suspension comprising the following distinctive structural components: the executive weight-lowering mechanism, polyspast mechanism, rope, traverse, and rods. A created structural dynamic model of suspension allowed us to define weight suspension rigidity. Within the framework of design analysis of a dynamic model we determined the rigidity of its structural units, i.e. traverse, rope, and polyspast.Known analytical relationships were used to calculate the rope rigidity. To determine rigidity of polyspast and traverse have been created special models based on the finite element method. For each model deformation in the specific points under the test load have been defined. Data obtained were used to determine trigidity of traverses and polyspast, and also rigidity of suspension in total. The rigidity models of polispast mechanism and traverse have been developed and calculated using the software complex "Zenit-95".As the research results, the paper presents a dynamic model of the weight suspension of the transport-erector aggregate, the finite element models of the polispast mechanism and traverse, an algorithm for determining the weight suspension rigidity and relevant analytical relationships.Independent calculation of weight suspension rigidity enables us to simplify further dynamic calculation of the aggregate-weight system because it allows attaining a simpler model of the aggregate-weight system that uses the weight suspension model as an element of equivalent rigidity. Despite this simplification the model allows us to determine correctly weight movement parameters and overloads in the aggregate-weight system in the process of technical operations.

3D Weight Matrices in Modeling Real Estate Prices

Science.gov (United States)

Mimis, A.

2016-10-01

Central role in spatial econometric models of real estate data has the definition of the weight matrix by which we capture the spatial dependence between the observations. The weight matrices presented in literature so far, treats space in a two dimensional manner leaving out the effect of the third dimension or in our case the difference in height where the property resides. To overcome this, we propose a new definition of the weight matrix including the third dimensional effect by using the Hadamard product. The results illustrated that the level effect can be absorbed into the new weight matrix.

Variance components for direct and maternal effects on body weights of Katahdin lambs

Science.gov (United States)

The aim of this study was to estimate genetic parameters for BW in Katahdin lambs. Six animal models were used to study direct and maternal effects on birth (BWT), weaning (WWT) and postweaning (PWWT) weights using 41,066 BWT, 33,980 WWT, and 22,793 PWWT records collected over 17 yr in 100 flocks. F...

A probabilistic model for component-based shape synthesis

KAUST Repository

Kalogerakis, Evangelos

2012-07-01

We present an approach to synthesizing shapes from complex domains, by identifying new plausible combinations of components from existing shapes. Our primary contribution is a new generative model of component-based shape structure. The model represents probabilistic relationships between properties of shape components, and relates them to learned underlying causes of structural variability within the domain. These causes are treated as latent variables, leading to a compact representation that can be effectively learned without supervision from a set of compatibly segmented shapes. We evaluate the model on a number of shape datasets with complex structural variability and demonstrate its application to amplification of shape databases and to interactive shape synthesis. © 2012 ACM 0730-0301/2012/08-ART55.

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study).

Science.gov (United States)

Thomas, Diana M; Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

2015-03-01

Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing model. The AUC statistic quantified the ROC curve's capacity to classify participants likely to lose models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. © 2015 American Society for Nutrition.

Measuring the Common Component of Stock Market Fluctuations in the Asia-Pacific Region

OpenAIRE

Mapa, Dennis S.; Briones, Kristine Joy S.

2006-01-01

This paper fits Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) models to the daily closing stock market indices of Australia, China, Hong Kong, Indonesia, Japan, Korea, Malaysia, Philippines, Singapore, and Taiwan to compute for time-varying weights associated with the volatilities of individual indices. These weights and the returns of the various indices were then used to determine the common component of stock market returns. Our results suggest that a common component ...

Egg weights, egg component weights, and laying gaps in Great Tits (Parus major) in relation to ambient temperature

NARCIS (Netherlands)

Lessells, C.M.; Dingemanse, N.J.; Both, C.; Blem, C.

2002-01-01

We collected 328 freshly laid Great Tit (Parus major) eggs from 38 clutches in 1999 to determine the relationship of whole egg weight, wet yolk weight, wet albumen weight, dry shell weight, and the occurrence of laying gaps with mean ambient temperature in the three days preceding laying, while

Egg weights, egg component weights, and laying gaps in great tits (Parus major) in relation to ambient temperature.

NARCIS (Netherlands)

Lessells, C.M.; Dingemanse, N.J.; Both, C.

2002-01-01

We collected 328 freshly laid Great Tit (Parus major) eggs from 38 clutches in 1999 to determine the relationship of whole egg weight, wet yolk weight, wet albumen weight, dry shell weight, and the occurrence of laying gaps with mean ambient temperature in the three days preceding laying, while

Component-based modeling of systems for automated fault tree generation

International Nuclear Information System (INIS)

Majdara, Aref; Wakabayashi, Toshio

2009-01-01

One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented

A Local Weighted Nearest Neighbor Algorithm and a Weighted and Constrained Least-Squared Method for Mixed Odor Analysis by Electronic Nose Systems

Directory of Open Access Journals (Sweden)

Jyuo-Min Shyu

2010-11-01

Full Text Available A great deal of work has been done to develop techniques for odor analysis by electronic nose systems. These analyses mostly focus on identifying a particular odor by comparing with a known odor dataset. However, in many situations, it would be more practical if each individual odorant could be determined directly. This paper proposes two methods for such odor components analysis for electronic nose systems. First, a K-nearest neighbor (KNN-based local weighted nearest neighbor (LWNN algorithm is proposed to determine the components of an odor. According to the component analysis, the odor training data is firstly categorized into several groups, each of which is represented by its centroid. The examined odor is then classified as the class of the nearest centroid. The distance between the examined odor and the centroid is calculated based on a weighting scheme, which captures the local structure of each predefined group. To further determine the concentration of each component, odor models are built by regressions. Then, a weighted and constrained least-squares (WCLS method is proposed to estimate the component concentrations. Experiments were carried out to assess the effectiveness of the proposed methods. The LWNN algorithm is able to classify mixed odors with different mixing ratios, while the WCLS method can provide good estimates on component concentrations.

Interdependency in Multimodel Climate Projections: Component Replication and Result Similarity

Science.gov (United States)

Boé, Julien

2018-03-01

Multimodel ensembles are the main way to deal with model uncertainties in climate projections. However, the interdependencies between models that often share entire components make it difficult to combine their results in a satisfactory way. In this study, how the replication of components (atmosphere, ocean, land, and sea ice) between climate models impacts the proximity of their results is quantified precisely, in terms of climatological means and future changes. A clear relationship exists between the number of components shared by climate models and the proximity of their results. Even the impact of a single shared component is generally visible. These conclusions are true at both the global and regional scales. Given available data, it cannot be robustly concluded that some components are more important than others. Those results provide ways to estimate model interdependencies a priori rather than a posteriori based on their results, in order to define independence weights.

Algorithmic fault tree construction by component-based system modeling

International Nuclear Information System (INIS)

Majdara, Aref; Wakabayashi, Toshio

2008-01-01

Computer-aided fault tree generation can be easier, faster and less vulnerable to errors than the conventional manual fault tree construction. In this paper, a new approach for algorithmic fault tree generation is presented. The method mainly consists of a component-based system modeling procedure an a trace-back algorithm for fault tree synthesis. Components, as the building blocks of systems, are modeled using function tables and state transition tables. The proposed method can be used for a wide range of systems with various kinds of components, if an inclusive component database is developed. (author)

A Systematic Evaluation of Ultrasound-based Fetal Weight Estimation Models on Indian Population

Directory of Open Access Journals (Sweden)

Sujitkumar S. Hiwale

2017-12-01

Conclusion: We found that the existing fetal weight estimation models have high systematic and random errors on Indian population, with a general tendency of overestimation of fetal weight in the LBW category and underestimation in the HBW category. We also observed that these models have a limited ability to predict babies at a risk of either low or high birth weight. It is recommended that the clinicians should consider all these factors, while interpreting estimated weight given by the existing models.

Time-series modeling of long-term weight self-monitoring data.

Science.gov (United States)

Helander, Elina; Pavel, Misha; Jimison, Holly; Korhonen, Ilkka

2015-08-01

Long-term self-monitoring of weight is beneficial for weight maintenance, especially after weight loss. Connected weight scales accumulate time series information over long term and hence enable time series analysis of the data. The analysis can reveal individual patterns, provide more sensitive detection of significant weight trends, and enable more accurate and timely prediction of weight outcomes. However, long term self-weighing data has several challenges which complicate the analysis. Especially, irregular sampling, missing data, and existence of periodic (e.g. diurnal and weekly) patterns are common. In this study, we apply time series modeling approach on daily weight time series from two individuals and describe information that can be extracted from this kind of data. We study the properties of weight time series data, missing data and its link to individuals behavior, periodic patterns and weight series segmentation. Being able to understand behavior through weight data and give relevant feedback is desired to lead to positive intervention on health behaviors.

Component biomass equations for black spruce in Maine

Science.gov (United States)

M. M. Czapowskyj; D. J. Robison; R. D. Briggs; E. H. White; E. H. White

1985-01-01

Component biomass prediction equations are presented for young black spruce (Picea mariana B.S.P. (Mill,:)) in northern Maine. A weighted least squares model was used to construct the eq~iationsfo r small trees from 1 to 15 cm d.b.h., and an ordinary least squares model for trees less than 2 m in height. A linearized allometric model was also tested but was not used....

Parameter estimation of component reliability models in PSA model of Krsko NPP

International Nuclear Information System (INIS)

Jordan Cizelj, R.; Vrbanic, I.

2001-01-01

In the paper, the uncertainty analysis of component reliability models for independent failures is shown. The present approach for parameter estimation of component reliability models in NPP Krsko is presented. Mathematical approaches for different types of uncertainty analyses are introduced and used in accordance with some predisposed requirements. Results of the uncertainty analyses are shown in an example for time-related components. As the most appropriate uncertainty analysis proved the Bayesian estimation with the numerical estimation of a posterior, which can be approximated with some appropriate probability distribution, in this paper with lognormal distribution.(author)

Regional income inequality model based on theil index decomposition and weighted variance coeficient

Science.gov (United States)

Sitepu, H. R.; Darnius, O.; Tambunan, W. N.

2018-03-01

Regional income inequality is an important issue in the study on economic development of a certain region. Rapid economic development may not in accordance with people’s per capita income. The method of measuring the regional income inequality has been suggested by many experts. This research used Theil index and weighted variance coefficient in order to measure the regional income inequality. Regional income decomposition which becomes the productivity of work force and their participation in regional income inequality, based on Theil index, can be presented in linear relation. When the economic assumption in j sector, sectoral income value, and the rate of work force are used, the work force productivity imbalance can be decomposed to become the component in sectors and in intra-sectors. Next, weighted variation coefficient is defined in the revenue and productivity of the work force. From the quadrate of the weighted variation coefficient result, it was found that decomposition of regional revenue imbalance could be analyzed by finding out how far each component contribute to regional imbalance which, in this research, was analyzed in nine sectors of economic business.

Associations of neighbourhood walkability indices with weight gain.

Science.gov (United States)

Koohsari, Mohammad Javad; Oka, Koichiro; Shibata, Ai; Liao, Yung; Hanibuchi, Tomoya; Owen, Neville; Sugiyama, Takemi

2018-04-03

Inconsistent associations of neighbourhood walkability with adults' body weight have been reported. Most studies examining the relationships of walkability and adiposity are cross-sectional in design. We examined the longitudinal relationships of two walkability indices - conventional walkability and space syntax walkability, and their individual components, with weight change among adults over four years. Data were from the Physical Activity in Localities and Community study in Adelaide, Australia. In 2003-2004, 2650 adults living in 154 Census Collection Districts (CCDs) returned baseline questionnaires; in 2007-2008, the follow-up survey was completed by 1098. Participants reported their weight at baseline and at follow-up. Neighbourhood walkability indices were calculated using geographic information systems and space syntax software. Linear marginal models using generalized estimating equations with robust standard errors were fitted to examine associations of the two walkability indices and their individual components with the weight at follow-up, adjusting for baseline weight, socio-demographic variables, and spatial clustering at the level of CCD. The overall mean weight gain over four years was 1.5 kg. The two walkability indices were closely correlated (r = 0.76, p walkability indices and weight change. Among walkability components, there was a marginally significant negative association between space syntax measure of street integration and weight change: one standard deviation increment in street integration was associated with 0.31 kg less weight gain (p = 0.09). Using a prospective study design and a novel space-syntax based measure of walkability, we were not able to identify relationships between neighbourhood walkability with weight gain. This is consistent with other inconclusive findings on the built environment and obesity. Research on the built environment and adults' weight gain may need to consider not just local environments but

Obesity and internalized weight stigma: a formulation model for an emerging psychological problem.

Science.gov (United States)

Ratcliffe, Denise; Ellison, Nell

2015-03-01

Obese individuals frequently experience weight stigma and this is associated with psychological distress and difficulties. The process of external devaluation can lead to negative self-perception and evaluation and some obese individuals develop "internalized weight stigma". The prevalence of weight stigma is well established but there is a lack of information about the interplay between external and internal weight stigma. To synthesize the literature on the psychological effects of weight stigma into a formulation model that addresses the maintenance of internalized weight stigma. Current research on the psychological impact of weight stigma was reviewed. We identify cognitive, behavioural and attentional processes that maintain psychological conditions where self-evaluation plays a central role. A model was developed based on clinical utility. The model focuses on identifying factors that influence and maintain internalized weight stigma. We highlight the impact of negative societal and interpersonal experiences of weight stigma on how individuals view themselves as an obese person. Processing the self as a stigmatized individual is at the core of the model. Maintenance factors include negative self-judgements about the meaning of being an obese individual, attentional and mood shifts, and avoidance and safety behaviours. In addition, eating and weight management behaviours become deregulated and maintain both obesity and weight stigma. As obesity increases, weight stigma and the associated psychological effects are likely to increase. We provide a framework for formulating and intervening with internalized weight stigma as well as making therapists aware of the applicability and transferability of strategies that they may already use with other presenting problems.

Overview of the model component in ECOCLIM

DEFF Research Database (Denmark)

Geels, Camilla; Boegh, Eva; Bendtsen, J

and atmospheric models. We will use the model system to 1) quantify the potential effects of climate change on ecosystem exchange of GHG and 2) estimate the impacts of changes in management practices including land use change and nitrogen (N) loads. Here the various model components will be introduced...

Data Driven Broiler Weight Forecasting using Dynamic Neural Network Models

DEFF Research Database (Denmark)

Johansen, Simon Vestergaard; Bendtsen, Jan Dimon; Riisgaard-Jensen, Martin

2017-01-01

In this article, the dynamic influence of environmental broiler house conditions and broiler growth is investigated. Dynamic neural network forecasting models have been trained on farm-scale broiler batch production data from 12 batches from the same house. The model forecasts future broiler weight...... and uses environmental conditions such as heating, ventilation, and temperature along with broiler behavior such as feed and water consumption. Training data and forecasting data is analyzed to explain when the model might fail at generalizing. We present ensemble broiler weight forecasts to day 7, 14, 21...

Probabilistic Modeling of Wind Turbine Drivetrain Components

DEFF Research Database (Denmark)

Rafsanjani, Hesam Mirzaei

Wind energy is one of several energy sources in the world and a rapidly growing industry in the energy sector. When placed in offshore or onshore locations, wind turbines are exposed to wave excitations, highly dynamic wind loads and/or the wakes from other wind turbines. Therefore, most components...... in a wind turbine experience highly dynamic and time-varying loads. These components may fail due to wear or fatigue, and this can lead to unplanned shutdown repairs that are very costly. The design by deterministic methods using safety factors is generally unable to account for the many uncertainties. Thus......, a reliability assessment should be based on probabilistic methods where stochastic modeling of failures is performed. This thesis focuses on probabilistic models and the stochastic modeling of the fatigue life of the wind turbine drivetrain. Hence, two approaches are considered for stochastic modeling...

Component-Based Development of Runtime Observers in the COMDES Framework

DEFF Research Database (Denmark)

Guan, Wei; Li, Gang; Angelov, Christo K.

2013-01-01

against formally specified properties. This paper presents a component-based design method for runtime observers in the context of COMDES framework—a component-based framework for distributed embedded system and its supporting tools. Therefore, runtime verification is facilitated by model......Formal verification methods, such as exhaustive model checking, are often infeasible because of high computational complexity. Runtime observers (monitors) provide an alternative, light-weight verification method, which offers a non-exhaustive but still feasible approach to monitor system behavior...

Analytical Formulation for Sizing and Estimating the Dimensions and Weight of Wind Turbine Hub and Drivetrain Components

Energy Technology Data Exchange (ETDEWEB)

Guo, Y. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Parsons, T. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); King, R. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dykes, K. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Veers, P. [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2015-06-09

This report summarizes the theory, verification, and validation of a new sizing tool for wind turbine drivetrain components, the Drivetrain Systems Engineering (DriveSE) tool. DriveSE calculates the dimensions and mass properties of the hub, main shaft, main bearing(s), gearbox, bedplate, transformer if up-tower, and yaw system. The level of fi¬ delity for each component varies depending on whether semiempirical parametric or physics-based models are used. The physics-based models have internal iteration schemes based on system constraints and design criteria. Every model is validated against available industry data or finite-element analysis. The verification and validation results show that the models reasonably capture primary drivers for the sizing and design of major drivetrain components.

Predicting successful long-term weight loss from short-term weight-loss outcomes: new insights from a dynamic energy balance model (the POUNDS Lost study)123

Science.gov (United States)

Ivanescu, Andrada E; Martin, Corby K; Heymsfield, Steven B; Marshall, Kaitlyn; Bodrato, Victoria E; Williamson, Donald A; Anton, Stephen D; Sacks, Frank M; Ryan, Donna; Bray, George A

2015-01-01

Background: Currently, early weight-loss predictions of long-term weight-loss success rely on fixed percent-weight-loss thresholds. Objective: The objective was to develop thresholds during the first 3 mo of intervention that include the influence of age, sex, baseline weight, percent weight loss, and deviations from expected weight to predict whether a participant is likely to lose 5% or more body weight by year 1. Design: Data consisting of month 1, 2, 3, and 12 treatment weights were obtained from the 2-y Preventing Obesity Using Novel Dietary Strategies (POUNDS Lost) intervention. Logistic regression models that included covariates of age, height, sex, baseline weight, target energy intake, percent weight loss, and deviation of actual weight from expected were developed for months 1, 2, and 3 that predicted the probability of losing <5% of body weight in 1 y. Receiver operating characteristic (ROC) curves, area under the curve (AUC), and thresholds were calculated for each model. The AUC statistic quantified the ROC curve’s capacity to classify participants likely to lose <5% of their body weight at the end of 1 y. The models yielding the highest AUC were retained as optimal. For comparison with current practice, ROC curves relying solely on percent weight loss were also calculated. Results: Optimal models for months 1, 2, and 3 yielded ROC curves with AUCs of 0.68 (95% CI: 0.63, 0.74), 0.75 (95% CI: 0.71, 0.81), and 0.79 (95% CI: 0.74, 0.84), respectively. Percent weight loss alone was not better at identifying true positives than random chance (AUC ≤0.50). Conclusions: The newly derived models provide a personalized prediction of long-term success from early weight-loss variables. The predictions improve on existing fixed percent-weight-loss thresholds. Future research is needed to explore model application for informing treatment approaches during early intervention. The POUNDS Lost study was registered at clinicaltrials.gov as NCT00072995. PMID:25733628

Conceptual Model of Weight Management in Overweight and Obese African-American Females.

Science.gov (United States)

Sutton, Suzanne M; Magwood, Gayenell S; Nemeth, Lynne S; Jenkins, Carolyn M

2017-04-01

Weight management of overweight and obese (OWO) African-American females (AAFs) is a poorly defined concept, leading to ineffective treatment of overweight and obesity, prevention of health sequelae, and risk reduction. A conceptual model of the phenomenon of weight management in OWO AAFs was developed through dimensional analysis of the literature. Constructs were identified and sorted into the dimensions of perspective, context, conditions, process, and consequences and integrated into an explanatory matrix. Through dimensional analysis, weight management in OWO AAFs was characterized as a multidimensional concept, defined from the perspective of weight loss in community-dwelling AAFs. Behaviors associated with weight management are strongly influenced by intrinsic factors and extrinsic conditions, which influence engagement in the processes and consequences of weight management. The resulting conceptual model of weight management in OWO AAFs provides a framework for research interventions applicable in a variety of settings. © 2016 Wiley Periodicals, Inc.

Accessibility to Nodes of Interest: Demographic Weighting the Logistic Model

Directory of Open Access Journals (Sweden)

Gioacchino DE CANDIA

2015-11-01

Full Text Available This research fits into the genre of spatial analysis, aimed at better understanding of population dynamics in relation to the presence and distribution of infrastructure and related services. Specifically, the analysis uses a model of the gravitational type, based on the assumption of the impedance (attractiveness territorial, based on a curve of type logistics to determine the accessibility of the same, to which to add a system of weights. In this sense, the model was weighted according to the population, to determine the level of “population served” in terms of infrastructure and related services included in the model.

Reduction of bias in neutron multiplicity assay using a weighted point model

Energy Technology Data Exchange (ETDEWEB)

Geist, W. H. (William H.); Krick, M. S. (Merlyn S.); Mayo, D. R. (Douglas R.)

2004-01-01

Accurate assay of most common plutonium samples was the development goal for the nondestructive assay technique of neutron multiplicity counting. Over the past 20 years the technique has been proven for relatively pure oxides and small metal items. Unfortunately, the technique results in large biases when assaying large metal items. Limiting assumptions, such as unifoh multiplication, in the point model used to derive the multiplicity equations causes these biases for large dense items. A weighted point model has been developed to overcome some of the limitations in the standard point model. Weighting factors are detemiined from Monte Carlo calculations using the MCNPX code. Monte Carlo calculations give the dependence of the weighting factors on sample mass and geometry, and simulated assays using Monte Carlo give the theoretical accuracy of the weighted-point-model assay. Measured multiplicity data evaluated with both the standard and weighted point models are compared to reference values to give the experimental accuracy of the assay. Initial results show significant promise for the weighted point model in reducing or eliminating biases in the neutron multiplicity assay of metal items. The negative biases observed in the assay of plutonium metal samples are caused by variations in the neutron multiplication for neutrons originating in various locations in the sample. The bias depends on the mass and shape of the sample and depends on the amount and energy distribution of the ({alpha},n) neutrons in the sample. When the standard point model is used, this variable-multiplication bias overestimates the multiplication and alpha values of the sample, and underestimates the plutonium mass. The weighted point model potentially can provide assay accuracy of {approx}2% (1 {sigma}) for cylindrical plutonium metal samples < 4 kg with {alpha} < 1 without knowing the exact shape of the samples, provided that the ({alpha},n) source is uniformly distributed throughout the

Robustness of Component Models in Energy System Simulators

DEFF Research Database (Denmark)

Elmegaard, Brian

2003-01-01

During the development of the component-based energy system simulator DNA (Dynamic Network Analysis), several obstacles to easy use of the program have been observed. Some of these have to do with the nature of the program being based on a modelling language, not a graphical user interface (GUI......). Others have to do with the interaction between models of the nature of the substances in an energy system (e.g., fuels, air, flue gas), models of the components in a system (e.g., heat exchangers, turbines, pumps), and the solver for the system of equations. This paper proposes that the interaction...

A three-component cognitive behavioural lifestyle program for preconceptional weight-loss in women with polycystic ovary syndrome (PCOS): a protocol for a randomized controlled trial.

Science.gov (United States)

Jiskoot, G; Benneheij, S H; Beerthuizen, A; de Niet, J E; de Klerk, C; Timman, R; Busschbach, J J; Laven, J S E

2017-03-06

Obesity in women with polycystic ovary syndrome (PCOS) negatively affects all clinical features, and a 5 to 10% weight loss has shown promising results on reproductive, metabolic and psychological level. Incorporating a healthy diet, increasing physical activity and changing dysfunctional thought patterns in women with PCOS are key points in losing weight. The biggest challenge in weight management programs is to achieve a reasonable and sustainable weight loss. The aim of this study is to explore whether Cognitive Behavioural Therapy (CBT) by a mental health professional, working in a multidisciplinary team with a dietician and a physical therapist (a three-component intervention), is more effective for weight loss in the long term, within 12 months. We will also explore whether mobile phone applications are effective in supporting behavioural change and sustainable weight loss. The present study is a longitudinal randomized controlled trial (RCT) to study the effectiveness of a three-component 1-year cognitive-behavioural lifestyle intervention in overweight/obese women with PCOS. A total of 210 participants are randomly assigned to three groups: 1) CBT provided by the multidisciplinary team or; 2) CBT provided by the multidisciplinary team and Short Message Service (SMS) or; 3) usual care: encourage weight loss through publicly available services (control group). The primary aim of the 12-month intervention is to explore whether a three-component 1-year cognitive-behavioural lifestyle intervention is effective to decrease weight, when compared to usual care. Secondary outcomes include: the effect of the intervention on the PCOS phenotype, waist circumference, waist to hip ratio, ovulation rates, total testosterone, SHBG, free androgen index (FAI), AMH, hirsutism, acne, fasting glucose, blood pressure and all psychological parameters. Additionally, we assessed time to pregnancy, ongoing pregnancies, clinical pregnancies, miscarriages and birth weight. All

Dynamic monitoring of weight data at the pen vs at the individual level

DEFF Research Database (Denmark)

Jensen, Dan; Toft, Nils; Kristensen, A. R. K.

recorded weight data from finisher pigs. Data are collected at insertion and at the exit of the first pigs in the pen, and in few pens, the weight is recorded weekly. Dynamic linear models are fitted on the weight data, at the pig level (univariate), at the double pen level using averaged weight...... (univariate) and using individual pig values as parameters in a hierarchical (multivariate) model including section, double pen, and individual level. Variance components of the different models are estimated using the Expectation Maximization algorithm. The difference of information obtained...... at the individual vs pen level is thereafter assessed. Whereas weight data is usually monitored after a batch is being sent to the slaughter house, this method provides weekly updating of the data. Perspectives of application include dynamic monitoring of weight data in relation to events such as diarrhoea, tail...

Dynamic monitoring of weight data at the pen vs at the individual level

DEFF Research Database (Denmark)

Jensen, Dan Børge; Toft, Nils; Kristensen, Anders Ringgaard

recorded weight data from finisher pigs. Data are collected at insertion and at the exit of the first pigs in the pen, and in few pens, the weight is recorded weekly. Dynamic linear models are fitted on the weight data, at the pig level (univariate), at the double pen level using averaged weight...... (univariate) and using individual pig values as parameters in a hierarchical (multivariate) model including section, double pen, and individual level. Variance components of the different models are estimated using the Expectation Maximization algorithm. The difference of information obtained...... at the individual vs. pen level is thereafter assessed. Whereas weight data is usually monitored after a batch is being sent to the slaughter house, this method provides with weekly updating of the data. Perspectives of application include dynamic monitoring of weight data in relation to events such as diarrhoea...

Using Patient Demographics and Statistical Modeling to Predict Knee Tibia Component Sizing in Total Knee Arthroplasty.

Science.gov (United States)

Ren, Anna N; Neher, Robert E; Bell, Tyler; Grimm, James

2018-06-01

Preoperative planning is important to achieve successful implantation in primary total knee arthroplasty (TKA). However, traditional TKA templating techniques are not accurate enough to predict the component size to a very close range. With the goal of developing a general predictive statistical model using patient demographic information, ordinal logistic regression was applied to build a proportional odds model to predict the tibia component size. The study retrospectively collected the data of 1992 primary Persona Knee System TKA procedures. Of them, 199 procedures were randomly selected as testing data and the rest of the data were randomly partitioned between model training data and model evaluation data with a ratio of 7:3. Different models were trained and evaluated on the training and validation data sets after data exploration. The final model had patient gender, age, weight, and height as independent variables and predicted the tibia size within 1 size difference 96% of the time on the validation data, 94% of the time on the testing data, and 92% on a prospective cadaver data set. The study results indicated the statistical model built by ordinal logistic regression can increase the accuracy of tibia sizing information for Persona Knee preoperative templating. This research shows statistical modeling may be used with radiographs to dramatically enhance the templating accuracy, efficiency, and quality. In general, this methodology can be applied to other TKA products when the data are applicable. Copyright © 2018 Elsevier Inc. All rights reserved.

Local Model Checking of Weighted CTL with Upper-Bound Constraints

DEFF Research Database (Denmark)

Jensen, Jonas Finnemann; Larsen, Kim Guldstrand; Srba, Jiri

2013-01-01

We present a symbolic extension of dependency graphs by Liu and Smolka in order to model-check weighted Kripke structures against the logic CTL with upper-bound weight constraints. Our extension introduces a new type of edges into dependency graphs and lifts the computation of fixed-points from...

Component based modelling of piezoelectric ultrasonic actuators for machining applications

International Nuclear Information System (INIS)

Saleem, A; Ahmed, N; Salah, M; Silberschmidt, V V

2013-01-01

Ultrasonically Assisted Machining (UAM) is an emerging technology that has been utilized to improve the surface finishing in machining processes such as turning, milling, and drilling. In this context, piezoelectric ultrasonic transducers are being used to vibrate the cutting tip while machining at predetermined amplitude and frequency. However, modelling and simulation of these transducers is a tedious and difficult task. This is due to the inherent nonlinearities associated with smart materials. Therefore, this paper presents a component-based model of ultrasonic transducers that mimics the nonlinear behaviour of such a system. The system is decomposed into components, a mathematical model of each component is created, and the whole system model is accomplished by aggregating the basic components' model. System parameters are identified using Finite Element technique which then has been used to simulate the system in Matlab/SIMULINK. Various operation conditions are tested and performed to demonstrate the system performance

Modeling accelerator structures and RF components

International Nuclear Information System (INIS)

Ko, K., Ng, C.K.; Herrmannsfeldt, W.B.

1993-03-01

Computer modeling has become an integral part of the design and analysis of accelerator structures RF components. Sophisticated 3D codes, powerful workstations and timely theory support all contributed to this development. We will describe our modeling experience with these resources and discuss their impact on ongoing work at SLAC. Specific examples from R ampersand D on a future linear collide and a proposed e + e - storage ring will be included

Weight information labels on media models reduce body dissatisfaction in adolescent girls

NARCIS (Netherlands)

Veldhuis, Jolanda; Konijn, Elly A; Seidell, Jacob C

2012-01-01

PURPOSE: To examine how weight information labels on variously sized media models affect (pre)adolescent girls' body perceptions and how they compare themselves with media models. METHODS: We used a three (body shape: extremely thin vs. thin vs. normal weight) × three (information label: 6-kg

Design and Application of an Ontology for Component-Based Modeling of Water Systems

Science.gov (United States)

Elag, M.; Goodall, J. L.

2012-12-01

Many Earth system modeling frameworks have adopted an approach of componentizing models so that a large model can be assembled by linking a set of smaller model components. These model components can then be more easily reused, extended, and maintained by a large group of model developers and end users. While there has been a notable increase in component-based model frameworks in the Earth sciences in recent years, there has been less work on creating framework-agnostic metadata and ontologies for model components. Well defined model component metadata is needed, however, to facilitate sharing, reuse, and interoperability both within and across Earth system modeling frameworks. To address this need, we have designed an ontology for the water resources community named the Water Resources Component (WRC) ontology in order to advance the application of component-based modeling frameworks across water related disciplines. Here we present the design of the WRC ontology and demonstrate its application for integration of model components used in watershed management. First we show how the watershed modeling system Soil and Water Assessment Tool (SWAT) can be decomposed into a set of hydrological and ecological components that adopt the Open Modeling Interface (OpenMI) standard. Then we show how the components can be used to estimate nitrogen losses from land to surface water for the Baltimore Ecosystem study area. Results of this work are (i) a demonstration of how the WRC ontology advances the conceptual integration between components of water related disciplines by handling the semantic and syntactic heterogeneity present when describing components from different disciplines and (ii) an investigation of a methodology by which large models can be decomposed into a set of model components that can be well described by populating metadata according to the WRC ontology.

Contribution to improving reliability assessments of mechanical structural components requiring a high degree of safety using weighted Monte Carlo simulation

Energy Technology Data Exchange (ETDEWEB)

Kutter, R

1981-12-04

Physical theories to inquire lifetime and reliability of mechanical structures or components under multiscale random stress do not exist. Today those dates were examinated e.g. in development of aircrafts and motorcars by fatigue-testing of original components and sections during long terms. Knowing the distributions of stress and material-parameters the same testing is to be realized simulationary on highspeed computers. This study gives methods to reduce the necessary computation time to attending ones even to proof reliability up to R=1-10/sup -9/. These methods were of Monte-Carlo-Simulation with weighted parameters and respect to life-history.

Experiment planning using high-level component models at W7-X

International Nuclear Information System (INIS)

Lewerentz, Marc; Spring, Anett; Bluhm, Torsten; Heimann, Peter; Hennig, Christine; Kühner, Georg; Kroiss, Hugo; Krom, Johannes G.; Laqua, Heike; Maier, Josef; Riemann, Heike; Schacht, Jörg; Werner, Andreas; Zilker, Manfred

2012-01-01

Highlights: ► Introduction of models for an abstract description of fusion experiments. ► Component models support creating feasible experiment programs at planning time. ► Component models contain knowledge about physical and technical constraints. ► Generated views on models allow to present crucial information. - Abstract: The superconducting stellarator Wendelstein 7-X (W7-X) is a fusion device, which is capable of steady state operation. Furthermore W7-X is a very complex technical system. To cope with these requirements a modular and strongly hierarchical component-based control and data acquisition system has been designed. The behavior of W7-X is characterized by thousands of technical parameters of the participating components. The intended sequential change of those parameters during an experiment is defined in an experiment program. Planning such an experiment program is a crucial and complex task. To reduce the complexity an abstract, more physics-oriented high-level layer has been introduced earlier. The so-called high-level (physics) parameters are used to encapsulate technical details. This contribution will focus on the extension of this layer to a high-level component model. It completely describes the behavior of a component for a certain period of time. It allows not only defining simple value ranges but also complex dependencies between physics parameters. This can be: dependencies within components, dependencies between components or temporal dependencies. Component models can now be analyzed to generate various views of an experiment. A first implementation of such an analyze process is already finished. A graphical preview of a planned discharge can be generated from a chronological sequence of component models. This allows physicists to survey complex planned experiment programs at a glance.

Molecular weight kinetics and chain scission models for dextran polymers during ultrasonic degradation.

Science.gov (United States)

Pu, Yuanyuan; Zou, Qingsong; Hou, Dianzhi; Zhang, Yiping; Chen, Shan

2017-01-20

Ultrasonic degradation of six dextran samples with different initial molecular weights (IMW) has been performed to investigate the degradation behavior and chain scission mechanism of dextrans. The weight-average molecular weight (Mw) and polydispersity index (D value) were monitored by High Performance Gel Permeation Chromatography (HPGPC). Results showed that Mw and D value decreased with increasing ultrasonic time, resulting in a more homologous dextran solution with lower molecular weight. A significant degradation occurred in dextrans with higher IMW, particularly at the initial stage of the ultrasonic treatment. The Malhotra model was found to well describe the molecular weight kinetics for all dextran samples. Experimental data was fitted into two chain scission models to study dextran chain scission mechanism and the model performance was compared. Results indicated that the midpoint scission model agreed well with experimental results, with a linear regression factor of R 2 >0.99. Copyright © 2016 Elsevier Ltd. All rights reserved.

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

Science.gov (United States)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

Dynamic airspace configuration method based on a weighted graph model

Directory of Open Access Journals (Sweden)

Chen Yangzhou

2014-08-01

Full Text Available This paper proposes a new method for dynamic airspace configuration based on a weighted graph model. The method begins with the construction of an undirected graph for the given airspace, where the vertices represent those key points such as airports, waypoints, and the edges represent those air routes. Those vertices are used as the sites of Voronoi diagram, which divides the airspace into units called as cells. Then, aircraft counts of both each cell and of each air-route are computed. Thus, by assigning both the vertices and the edges with those aircraft counts, a weighted graph model comes into being. Accordingly the airspace configuration problem is described as a weighted graph partitioning problem. Then, the problem is solved by a graph partitioning algorithm, which is a mixture of general weighted graph cuts algorithm, an optimal dynamic load balancing algorithm and a heuristic algorithm. After the cuts algorithm partitions the model into sub-graphs, the load balancing algorithm together with the heuristic algorithm transfers aircraft counts to balance workload among sub-graphs. Lastly, airspace configuration is completed by determining the sector boundaries. The simulation result shows that the designed sectors satisfy not only workload balancing condition, but also the constraints such as convexity, connectivity, as well as minimum distance constraint.

Background, design and conceptual model of the cluster randomized multiple-component workplace study

DEFF Research Database (Denmark)

Christensen, Jeanette Reffstrup; Bredahl, Thomas Viskum Gjelstrup; Hadrévi, Jenny

2016-01-01

health care workers. This was done through a multi-component intervention including 1) intelligent physical exercise training (IPET), dietary advice and weight loss (DAW) and cognitive behavioural training (CBT). DISCUSSION: The FRIDOM program has the potential to provide evidence-based knowledge...

BWR Refill-Reflood Program, Task 4.7 - model development: TRAC-BWR component models

International Nuclear Information System (INIS)

Cheung, Y.K.; Parameswaran, V.; Shaug, J.C.

1983-09-01

TRAC (Transient Reactor Analysis Code) is a computer code for best-estimate analysis for the thermal hydraulic conditions in a reactor system. The development and assessment of the BWR component models developed under the Refill/Reflood Program that are necessary to structure a BWR-version of TRAC are described in this report. These component models are the jet pump, steam separator, steam dryer, two-phase level tracking model, and upper-plenum mixing model. These models have been implemented into TRAC-B02. Also a single-channel option has been developed for individual fuel-channel analysis following a system-response calculation

Independent Component Analysis in Multimedia Modeling

DEFF Research Database (Denmark)

Larsen, Jan

2003-01-01

largely refers to text, images/video, audio and combinations of such data. We review a number of applications within single and combined media with the hope that this might provide inspiration for further research in this area. Finally, we provide a detailed presentation of our own recent work on modeling......Modeling of multimedia and multimodal data becomes increasingly important with the digitalization of the world. The objective of this paper is to demonstrate the potential of independent component analysis and blind sources separation methods for modeling and understanding of multimedia data, which...

Detailed finite element method modeling of evaporating multi-component droplets

Energy Technology Data Exchange (ETDEWEB)

Diddens, Christian, E-mail: C.Diddens@tue.nl

2017-07-01

The evaporation of sessile multi-component droplets is modeled with an axisymmetic finite element method. The model comprises the coupled processes of mixture evaporation, multi-component flow with composition-dependent fluid properties and thermal effects. Based on representative examples of water–glycerol and water–ethanol droplets, regular and chaotic examples of solutal Marangoni flows are discussed. Furthermore, the relevance of the substrate thickness for the evaporative cooling of volatile binary mixture droplets is pointed out. It is shown how the evaporation of the more volatile component can drastically decrease the interface temperature, so that ambient vapor of the less volatile component condenses on the droplet. Finally, results of this model are compared with corresponding results of a lubrication theory model, showing that the application of lubrication theory can cause considerable errors even for moderate contact angles of 40°. - Graphical abstract:.

Adherence to a behavioral weight loss treatment program enhances weight loss and improvements in biomarkers

Directory of Open Access Journals (Sweden)

Sushama D Acharya

2009-06-01

Full Text Available Sushama D Acharya3, Okan U Elci3, Susan M Sereika1,2,3, Edvin Music3, Mindi A Styn3, Melanie Warziski Turk3, Lora E Burke2,31Department of Biostatistics, Graduate School of Public Health, 2Department of Epidemiology, Graduate School of Public Health, 3School of Nursing, University of Pittsburgh, Pittsburgh, PA, USAObjectives: To describe participants’ adherence to multiple components (attendance, energy intake, fat gram, exercise goals, and self-monitoring eating and exercise behaviors of a standard behavioral treatment program (SBT for weight loss and how adherence to these components may influence weight loss and biomarkers (triglycerides, low density lipoproteins [LDL], high density lipoprotein, and insulin during the intensive and less-intensive intervention phases. Methods: A secondary analysis of a randomized clinical trial consisting of a SBT with either fat-restricted standard or lacto-ovo vegetarian diet. The 12-month intervention was delivered in 33 group sessions. The first six months reflected the intensive phase; the second six months, the less-intensive intervention phase. We conducted the analysis without regard to treatment assignment. Eligible participants included overweight/obese adults (N = 176; mean body mass index = 34.0 kg/m2. The sample was 86.9% female, 70.5% White, and 44.4 ± 8.6 years old. The outcome measures included weight and biomarkers. Results: There was a significant decline in adherence to each treatment component over time (P < 0.0001. In the first six months, adherence to attendance, self-monitoring and the energy goal were significantly associated with greater weight loss (P < 0.05. Adherence to attendance and exercise remained significantly associated with weight loss in the second six months (P < 0.05. Adherence to attendance, self-monitoring and exercise had indirect effects through weight loss on LDL, triglycerides, and insulin (P < 0.05.Conclusions: We observed a decline in adherence to each

Weight and cost forecasting for advanced manned space vehicles

Science.gov (United States)

Williams, Raymond

1989-01-01

A mass and cost estimating computerized methology for predicting advanced manned space vehicle weights and costs was developed. The user friendly methology designated MERCER (Mass Estimating Relationship/Cost Estimating Relationship) organizes the predictive process according to major vehicle subsystem levels. Design, development, test, evaluation, and flight hardware cost forecasting is treated by the study. This methodology consists of a complete set of mass estimating relationships (MERs) which serve as the control components for the model and cost estimating relationships (CERs) which use MER output as input. To develop this model, numerous MER and CER studies were surveyed and modified where required. Additionally, relationships were regressed from raw data to accommodate the methology. The models and formulations which estimated the cost of historical vehicles to within 20 percent of the actual cost were selected. The result of the research, along with components of the MERCER Program, are reported. On the basis of the analysis, the following conclusions were established: (1) The cost of a spacecraft is best estimated by summing the cost of individual subsystems; (2) No one cost equation can be used for forecasting the cost of all spacecraft; (3) Spacecraft cost is highly correlated with its mass; (4) No study surveyed contained sufficient formulations to autonomously forecast the cost and weight of the entire advanced manned vehicle spacecraft program; (5) No user friendly program was found that linked MERs with CERs to produce spacecraft cost; and (6) The group accumulation weight estimation method (summing the estimated weights of the various subsystems) proved to be a useful method for finding total weight and cost of a spacecraft.

Geographically Weighted Regression Model with Kernel Bisquare and Tricube Weighted Function on Poverty Percentage Data in Central Java Province

Science.gov (United States)

Nugroho, N. F. T. A.; Slamet, I.

2018-05-01

Poverty is a socio-economic condition of a person or group of people who can not fulfil their basic need to maintain and develop a dignified life. This problem still cannot be solved completely in Central Java Province. Currently, the percentage of poverty in Central Java is 13.32% which is higher than the national poverty rate which is 11.13%. In this research, data of percentage of poor people in Central Java Province has been analyzed through geographically weighted regression (GWR). The aim of this research is therefore to model poverty percentage data in Central Java Province using GWR with weighted function of kernel bisquare, and tricube. As the results, we obtained GWR model with bisquare and tricube kernel weighted function on poverty percentage data in Central Java province. From the GWR model, there are three categories of region which are influenced by different of significance factors.

Towards a Component Based Model for Database Systems

Directory of Open Access Journals (Sweden)

Octavian Paul ROTARU

2004-02-01

Full Text Available Due to their effectiveness in the design and development of software applications and due to their recognized advantages in terms of reusability, Component-Based Software Engineering (CBSE concepts have been arousing a great deal of interest in recent years. This paper presents and extends a component-based approach to object-oriented database systems (OODB introduced by us in [1] and [2]. Components are proposed as a new abstraction level for database system, logical partitions of the schema. In this context, the scope is introduced as an escalated property for transactions. Components are studied from the integrity, consistency, and concurrency control perspective. The main benefits of our proposed component model for OODB are the reusability of the database design, including the access statistics required for a proper query optimization, and a smooth information exchange. The integration of crosscutting concerns into the component database model using aspect-oriented techniques is also discussed. One of the main goals is to define a method for the assessment of component composition capabilities. These capabilities are restricted by the component’s interface and measured in terms of adaptability, degree of compose-ability and acceptability level. The above-mentioned metrics are extended from database components to generic software components. This paper extends and consolidates into one common view the ideas previously presented by us in [1, 2, 3].[1] Octavian Paul Rotaru, Marian Dobre, Component Aspects in Object Oriented Databases, Proceedings of the International Conference on Software Engineering Research and Practice (SERP’04, Volume II, ISBN 1-932415-29-7, pages 719-725, Las Vegas, NV, USA, June 2004.[2] Octavian Paul Rotaru, Marian Dobre, Mircea Petrescu, Integrity and Consistency Aspects in Component-Oriented Databases, Proceedings of the International Symposium on Innovation in Information and Communication Technology (ISIICT�

Mixed geographically weighted regression (MGWR) model with weighted adaptive bi-square for case of dengue hemorrhagic fever (DHF) in Surakarta

Science.gov (United States)

Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.

2017-06-01

MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.

Model validation and calibration based on component functions of model output

International Nuclear Information System (INIS)

Wu, Danqing; Lu, Zhenzhou; Wang, Yanping; Cheng, Lei

2015-01-01

The target in this work is to validate the component functions of model output between physical observation and computational model with the area metric. Based on the theory of high dimensional model representations (HDMR) of independent input variables, conditional expectations are component functions of model output, and the conditional expectations reflect partial information of model output. Therefore, the model validation of conditional expectations tells the discrepancy between the partial information of the computational model output and that of the observations. Then a calibration of the conditional expectations is carried out to reduce the value of model validation metric. After that, a recalculation of the model validation metric of model output is taken with the calibrated model parameters, and the result shows that a reduction of the discrepancy in the conditional expectations can help decrease the difference in model output. At last, several examples are employed to demonstrate the rationality and necessity of the methodology in case of both single validation site and multiple validation sites. - Highlights: • A validation metric of conditional expectations of model output is proposed. • HDRM explains the relationship of conditional expectations and model output. • An improved approach of parameter calibration updates the computational models. • Validation and calibration process are applied at single site and multiple sites. • Validation and calibration process show a superiority than existing methods

Dynamic k-out-of-n system reliability with component partnership

International Nuclear Information System (INIS)

Coit, David W.; Chatwattanasiri, Nida; Wattanapongsakorn, Naruemon; Konak, Abdullah

2015-01-01

This paper describes a new k-out-of-n system reliability model that is appropriate for certain design problems when the minimum number of required components, k, changes dynamically in response to failures to maximize the utility of the available collection of functioning components. This new model shares some distinct similarities with weighted k-out-of-n models and for some problems they produce the same result. However, there are subtle and distinct differences, and in practice, there are some complex applications have not been properly explained or modeled by traditional or extended k-out-of-n system models. For this application, components are arranged in a k-out-of-n configuration of heterogeneous components with different performance levels. Component performance is indicated by a component-specific component partnership level; the fewer partners required to operate successfully implies higher performance. The components can work collectively with partners at the same level to maintain system reliability, or they can create a partnership group with components at higher performance levels which serve as replacements to provide the necessary number of working components. When components fail, the dynamic k-out-of-n configuration maintains reliability of the system with changing k by having components create partnerships with other components at the same level or above. To demonstrate the model, a system replacement maintenance policy based on a replacement interval variable is applied to an example system to obtain the optimal replacement time. - Highlights: • A new k-out-of-n system reliability model is presented. • Components can form partnerships with other components. • The new k-out-of-n model is presented with a dynamic or changing k. • The new model is for systems with components that must work together in a group

Iterative Mixture Component Pruning Algorithm for Gaussian Mixture PHD Filter

Directory of Open Access Journals (Sweden)

Xiaoxi Yan

2014-01-01

Full Text Available As far as the increasing number of mixture components in the Gaussian mixture PHD filter is concerned, an iterative mixture component pruning algorithm is proposed. The pruning algorithm is based on maximizing the posterior probability density of the mixture weights. The entropy distribution of the mixture weights is adopted as the prior distribution of mixture component parameters. The iterative update formulations of the mixture weights are derived by Lagrange multiplier and Lambert W function. Mixture components, whose weights become negative during iterative procedure, are pruned by setting corresponding mixture weights to zeros. In addition, multiple mixture components with similar parameters describing the same PHD peak can be merged into one mixture component in the algorithm. Simulation results show that the proposed iterative mixture component pruning algorithm is superior to the typical pruning algorithm based on thresholds.

Low molecular weight components in an aquatic humic substance as characterized by membrane dialysis and orbitrap mass spectrometry.

Science.gov (United States)

Remucal, Christina K; Cory, Rose M; Sander, Michael; McNeill, Kristopher

2012-09-04

Suwannee River fulvic acid (SRFA) was dialyzed through a 100-500 molecular weight cutoff dialysis membrane, and the dialysate and retentate were analyzed by UV-visible absorption and high-resolution Orbitrap mass spectrometry (MS). A significant fraction (36% based on dissolved organic carbon) of SRFA passed through the dialysis membrane. The fraction of SRFA in the dialysate had a different UV-visible absorption spectrum and was enriched in low molecular weight molecules with a more aliphatic composition relative to the initial SRFA solution. Comparison of the SRFA spectra collected by Orbitrap MS and Fourier transform ion cyclotron resonance MS (FT-ICR MS) demonstrated that the mass accuracy of the Orbitrap MS is sufficient for determination of unique molecular formulas of compounds with masses masses detected by Orbitrap MS were found in the 100-200 Da mass range. Many of these low molecular masses corresponded to molecular formulas of previously identified compounds in organic matter, lignin, and plants, and the use of the standard addition method provided an upper concentration estimate of selected target compounds in SRFA. Collectively, these results provide evidence that SRFA contains low molecular weight components that are present individually or in loosely bound assemblies.

Prediction of earth rotation parameters based on improved weighted least squares and autoregressive model

Directory of Open Access Journals (Sweden)

Sun Zhangzhen

2012-08-01

Full Text Available In this paper, an improved weighted least squares (WLS, together with autoregressive (AR model, is proposed to improve prediction accuracy of earth rotation parameters(ERP. Four weighting schemes are developed and the optimal power e for determination of the weight elements is studied. The results show that the improved WLS-AR model can improve the ERP prediction accuracy effectively, and for different prediction intervals of ERP, different weight scheme should be chosen.

Refinement and verification in component-based model-driven design

DEFF Research Database (Denmark)

Chen, Zhenbang; Liu, Zhiming; Ravn, Anders Peter

2009-01-01

Modern software development is complex as it has to deal with many different and yet related aspects of applications. In practical software engineering this is now handled by a UML-like modelling approach in which different aspects are modelled by different notations. Component-based and object-o...... be integrated in computer-aided software engineering (CASE) tools for adding formally supported checking, transformation and generation facilities.......Modern software development is complex as it has to deal with many different and yet related aspects of applications. In practical software engineering this is now handled by a UML-like modelling approach in which different aspects are modelled by different notations. Component-based and object...

A two-component dark matter model with real singlet scalars ...

Indian Academy of Sciences (India)

2016-01-05

Jan 5, 2016 ... We propose a two-component dark matter (DM) model, each component of which is a real singlet scalar, to explain results from both direct and indirect detection experiments. We put the constraints on the model parameters from theoretical bounds, PLANCK relic density results and direct DM experiments.

Wind Tunnel Strain-Gage Balance Calibration Data Analysis Using a Weighted Least Squares Approach

Science.gov (United States)

Ulbrich, N.; Volden, T.

2017-01-01

A new approach is presented that uses a weighted least squares fit to analyze wind tunnel strain-gage balance calibration data. The weighted least squares fit is specifically designed to increase the influence of single-component loadings during the regression analysis. The weighted least squares fit also reduces the impact of calibration load schedule asymmetries on the predicted primary sensitivities of the balance gages. A weighting factor between zero and one is assigned to each calibration data point that depends on a simple count of its intentionally loaded load components or gages. The greater the number of a data point's intentionally loaded load components or gages is, the smaller its weighting factor becomes. The proposed approach is applicable to both the Iterative and Non-Iterative Methods that are used for the analysis of strain-gage balance calibration data in the aerospace testing community. The Iterative Method uses a reasonable estimate of the tare corrected load set as input for the determination of the weighting factors. The Non-Iterative Method, on the other hand, uses gage output differences relative to the natural zeros as input for the determination of the weighting factors. Machine calibration data of a six-component force balance is used to illustrate benefits of the proposed weighted least squares fit. In addition, a detailed derivation of the PRESS residuals associated with a weighted least squares fit is given in the appendices of the paper as this information could not be found in the literature. These PRESS residuals may be needed to evaluate the predictive capabilities of the final regression models that result from a weighted least squares fit of the balance calibration data.

New approaches to the modelling of multi-component fuel droplet heating and evaporation

KAUST Repository

Sazhin, Sergei S

2015-02-25

The previously suggested quasi-discrete model for heating and evaporation of complex multi-component hydrocarbon fuel droplets is described. The dependence of density, viscosity, heat capacity and thermal conductivity of liquid components on carbon numbers n and temperatures is taken into account. The effects of temperature gradient and quasi-component diffusion inside droplets are taken into account. The analysis is based on the Effective Thermal Conductivity/Effective Diffusivity (ETC/ED) model. This model is applied to the analysis of Diesel and gasoline fuel droplet heating and evaporation. The components with relatively close n are replaced by quasi-components with properties calculated as average properties of the a priori defined groups of actual components. Thus the analysis of the heating and evaporation of droplets consisting of many components is replaced with the analysis of the heating and evaporation of droplets consisting of relatively few quasi-components. It is demonstrated that for Diesel and gasoline fuel droplets the predictions of the model based on five quasi-components are almost indistinguishable from the predictions of the model based on twenty quasi-components for Diesel fuel droplets and are very close to the predictions of the model based on thirteen quasi-components for gasoline fuel droplets. It is recommended that in the cases of both Diesel and gasoline spray combustion modelling, the analysis of droplet heating and evaporation is based on as little as five quasi-components.

Electricity Price Forecast Using Combined Models with Adaptive Weights Selected and Errors Calibrated by Hidden Markov Model

Directory of Open Access Journals (Sweden)

Da Liu

2013-01-01

Full Text Available A combined forecast with weights adaptively selected and errors calibrated by Hidden Markov model (HMM is proposed to model the day-ahead electricity price. Firstly several single models were built to forecast the electricity price separately. Then the validation errors from every individual model were transformed into two discrete sequences: an emission sequence and a state sequence to build the HMM, obtaining a transmission matrix and an emission matrix, representing the forecasting ability state of the individual models. The combining weights of the individual models were decided by the state transmission matrixes in HMM and the best predict sample ratio of each individual among all the models in the validation set. The individual forecasts were averaged to get the combining forecast with the weights obtained above. The residuals of combining forecast were calibrated by the possible error calculated by the emission matrix of HMM. A case study of day-ahead electricity market of Pennsylvania-New Jersey-Maryland (PJM, USA, suggests that the proposed method outperforms individual techniques of price forecasting, such as support vector machine (SVM, generalized regression neural networks (GRNN, day-ahead modeling, and self-organized map (SOM similar days modeling.

PCA: Principal Component Analysis for spectra modeling

Science.gov (United States)

Hurley, Peter D.; Oliver, Seb; Farrah, Duncan; Wang, Lingyu; Efstathiou, Andreas

2012-07-01

The mid-infrared spectra of ultraluminous infrared galaxies (ULIRGs) contain a variety of spectral features that can be used as diagnostics to characterize the spectra. However, such diagnostics are biased by our prior prejudices on the origin of the features. Moreover, by using only part of the spectrum they do not utilize the full information content of the spectra. Blind statistical techniques such as principal component analysis (PCA) consider the whole spectrum, find correlated features and separate them out into distinct components. This code, written in IDL, classifies principal components of IRS spectra to define a new classification scheme using 5D Gaussian mixtures modelling. The five PCs and average spectra for the four classifications to classify objects are made available with the code.

Option valuation with the simplified component GARCH model

DEFF Research Database (Denmark)

Dziubinski, Matt P.

We introduce the Simplified Component GARCH (SC-GARCH) option pricing model, show and discuss sufficient conditions for non-negativity of the conditional variance, apply it to low-frequency and high-frequency financial data, and consider the option valuation, comparing the model performance...

Modeling The Skeleton Weight of an Adult Caucasian Man.

Science.gov (United States)

Avtandilashvili, Maia; Tolmachev, Sergei Y

2018-05-17

The reference value for the skeleton weight of an adult male (10.5 kg) recommended by the International Commission on Radiological Protection in Publication 70 is based on weights of dissected skeletons from 44 individuals, including two U.S. Transuranium and Uranium Registries whole-body donors. The International Commission on Radiological Protection analysis of anatomical data from 31 individuals with known values of body height demonstrated significant correlation between skeleton weight and body height. The corresponding regression equation, Wskel (kg) = -10.7 + 0.119 × H (cm), published in International Commission on Radiological Protection Publication 70 is typically used to estimate the skeleton weight from body height. Currently, the U.S. Transuranium and Uranium Registries holds data on individual bone weights from a total of 40 male whole-body donors, which has provided a unique opportunity to update the International Commission on Radiological Protection skeleton weight vs. body height equation. The original International Commission on Radiological Protection Publication 70 and the new U.S. Transuranium and Uranium Registries data were combined in a set of 69 data points representing a group of 33- to 95-y-old individuals with body heights and skeleton weights ranging from 155 to 188 cm and 6.5 to 13.4 kg, respectively. Data were fitted with a linear least-squares regression. A significant correlation between the two parameters was observed (r = 0.28), and an updated skeleton weight vs. body height equation was derived: Wskel (kg) = -6.5 + 0.093 × H (cm). In addition, a correlation of skeleton weight with multiple variables including body height, body weight, and age was evaluated using multiple regression analysis, and a corresponding fit equation was derived: Wskel (kg) = -0.25 + 0.046 × H (cm) + 0.036 × Wbody (kg) - 0.012 × A (y). These equations will be used to estimate skeleton weights and, ultimately, total skeletal actinide activities for

The contribution of fat component to gestational weight gain

Directory of Open Access Journals (Sweden)

2013-12-01

Full Text Available Objective: to estimate the role of adipose tissue in gestational weight gain (GWG and preferential fat deposition among normal-weight women. Subjects and methods: prospective cohort study of 84 pregnancies: maternal body mass index 18,5–24,9 kg/m2, singleton term pregnancy, nondiabetic women, somatically well. GWG and skinfold thickness were evaluated in the 1st, 2nd, 3d trimesters, on the 3d day after delivery. Results: fat mass gain in low GWG was similar to recommended GWG and in the high-GWG group was greater one. Women with recommended and low GWG returned to their initial fat level on the 3d day after delivery, in excessive weight gain fat significantly increased (р=0,025. Compared to initial recommended GWG resulted in triceps skinfold thicknesses loss (р=0,001, in abdominal skinfold gained nothing and in thighs skinfold thicknesses increasing (р=0,021. Inadequate GWG leads to fat loss in arms (р=0,017, fat of abdominal area and thighs return to initial level. In excessive GWG fat in the upper trunk and arms not changed, in the lower area (thighs significantly increased compared to initial level (р=0,001 or other groups (р=0,001. Conclusion: excessive GWG was associated with greater adipose tissue cumulation and its deposition preferentially over the thighs. Inadequate GWG was clearly linked to low fat-free mass gain.

Scale modeling flow-induced vibrations of reactor components

International Nuclear Information System (INIS)

Mulcahy, T.M.

1982-06-01

Similitude relationships currently employed in the design of flow-induced vibration scale-model tests of nuclear reactor components are reviewed. Emphasis is given to understanding the origins of the similitude parameters as a basis for discussion of the inevitable distortions which occur in design verification testing of entire reactor systems and in feature testing of individual component designs for the existence of detrimental flow-induced vibration mechanisms. Distortions of similitude parameters made in current test practice are enumerated and selected example tests are described. Also, limitations in the use of specific distortions in model designs are evaluated based on the current understanding of flow-induced vibration mechanisms and structural response

Unwinding the hairball graph: Pruning algorithms for weighted complex networks

Science.gov (United States)

Dianati, Navid

2016-01-01

Empirical networks of weighted dyadic relations often contain "noisy" edges that alter the global characteristics of the network and obfuscate the most important structures therein. Graph pruning is the process of identifying the most significant edges according to a generative null model and extracting the subgraph consisting of those edges. Here, we focus on integer-weighted graphs commonly arising when weights count the occurrences of an "event" relating the nodes. We introduce a simple and intuitive null model related to the configuration model of network generation and derive two significance filters from it: the marginal likelihood filter (MLF) and the global likelihood filter (GLF). The former is a fast algorithm assigning a significance score to each edge based on the marginal distribution of edge weights, whereas the latter is an ensemble approach which takes into account the correlations among edges. We apply these filters to the network of air traffic volume between US airports and recover a geographically faithful representation of the graph. Furthermore, compared with thresholding based on edge weight, we show that our filters extract a larger and significantly sparser giant component.

Models for integrated components coupled with their EM environment

NARCIS (Netherlands)

Ioan, D.; Schilders, W.H.A.; Ciuprina, G.; Meijs, van der N.P.; Schoenmaker, W.

2008-01-01

Abstract: Purpose – The main aim of this study is the modelling of the interaction of on-chip components with their electromagnetic environment. Design/methodology/approach – The integrated circuit is decomposed in passive and active components interconnected by means of terminals and connectors

The weight of the visual world is modified by recent experience

DEFF Research Database (Denmark)

Ásgeirsson, Árni Gunnar; Kyllingsbæk, Søren; Kristjánsson, Árni

. Recent proposals assume that repetition priming operates at multiple levels. Here we focus on two questions: (1) does repetition priming have a purely perceptual component? and (2) how does such a component fit into the TVA framework? (Bundesen, C. 1990. Psychological bulletin and Review, 97, 523...... not ruling out repetition benefits at other levels. Furthermore, color repetition was only beneficial when the task required attentional selection. The results were fitted to a TVA-based model from which we provided estimates of weights. The results from the modeling procedure indicate that the perceptual...

Modeling Fetal Weight for Gestational Age: A Comparison of a Flexible Multi-level Spline-based Model with Other Approaches

Science.gov (United States)

Villandré, Luc; Hutcheon, Jennifer A; Perez Trejo, Maria Esther; Abenhaim, Haim; Jacobsen, Geir; Platt, Robert W

2011-01-01

We present a model for longitudinal measures of fetal weight as a function of gestational age. We use a linear mixed model, with a Box-Cox transformation of fetal weight values, and restricted cubic splines, in order to flexibly but parsimoniously model median fetal weight. We systematically compare our model to other proposed approaches. All proposed methods are shown to yield similar median estimates, as evidenced by overlapping pointwise confidence bands, except after 40 completed weeks, where our method seems to produce estimates more consistent with observed data. Sex-based stratification affects the estimates of the random effects variance-covariance structure, without significantly changing sex-specific fitted median values. We illustrate the benefits of including sex-gestational age interaction terms in the model over stratification. The comparison leads to the conclusion that the selection of a model for fetal weight for gestational age can be based on the specific goals and configuration of a given study without affecting the precision or value of median estimates for most gestational ages of interest. PMID:21931571

Pool scrubbing models for iodine components

Energy Technology Data Exchange (ETDEWEB)

Fischer, K [Battelle Ingenieurtechnik GmbH, Eschborn (Germany)

1996-12-01

Pool scrubbing is an important mechanism to retain radioactive fission products from being carried into the containment atmosphere or into the secondary piping system. A number of models and computer codes has been developed to predict the retention of aerosols and fission product vapours that are released from the core and injected into water pools of BWR and PWR type reactors during severe accidents. Important codes in this field are BUSCA, SPARC and SUPRA. The present paper summarizes the models for scrubbing of gaseous Iodine components in these codes, discusses the experimental validation, and gives an assessment of the state of knowledge reached and the open questions which persist. The retention of gaseous Iodine components is modelled by the various codes in a very heterogeneous manner. Differences show up in the chemical species considered, the treatment of mass transfer boundary layers on the gaseous and liquid sides, the gas-liquid interface geometry, calculation of equilibrium concentrations and numerical procedures. Especially important is the determination of the pool water pH value. This value is affected by basic aerosols deposited in the water, e.g. Cesium and Rubidium compounds. A consistent model requires a mass balance of these compounds in the pool, thus effectively coupling the pool scrubbing phenomena of aerosols and gaseous Iodine species. Since the water pool conditions are also affected by drainage flow of condensate water from different regions in the containment, and desorption of dissolved gases on the pool surface is determined by the gas concentrations above the pool, some basic limitations of specialized pool scrubbing codes are given. The paper draws conclusions about the necessity of coupling between containment thermal-hydraulics and pool scrubbing models, and proposes ways of further simulation model development in order to improve source term predictions. (author) 2 tabs., refs.

Pool scrubbing models for iodine components

International Nuclear Information System (INIS)

Fischer, K.

1996-01-01

Pool scrubbing is an important mechanism to retain radioactive fission products from being carried into the containment atmosphere or into the secondary piping system. A number of models and computer codes has been developed to predict the retention of aerosols and fission product vapours that are released from the core and injected into water pools of BWR and PWR type reactors during severe accidents. Important codes in this field are BUSCA, SPARC and SUPRA. The present paper summarizes the models for scrubbing of gaseous Iodine components in these codes, discusses the experimental validation, and gives an assessment of the state of knowledge reached and the open questions which persist. The retention of gaseous Iodine components is modelled by the various codes in a very heterogeneous manner. Differences show up in the chemical species considered, the treatment of mass transfer boundary layers on the gaseous and liquid sides, the gas-liquid interface geometry, calculation of equilibrium concentrations and numerical procedures. Especially important is the determination of the pool water pH value. This value is affected by basic aerosols deposited in the water, e.g. Cesium and Rubidium compounds. A consistent model requires a mass balance of these compounds in the pool, thus effectively coupling the pool scrubbing phenomena of aerosols and gaseous Iodine species. Since the water pool conditions are also affected by drainage flow of condensate water from different regions in the containment, and desorption of dissolved gases on the pool surface is determined by the gas concentrations above the pool, some basic limitations of specialized pool scrubbing codes are given. The paper draws conclusions about the necessity of coupling between containment thermal-hydraulics and pool scrubbing models, and proposes ways of further simulation model development in order to improve source term predictions. (author) 2 tabs., refs

Modeling fabrication of nuclear components: An integrative approach

Energy Technology Data Exchange (ETDEWEB)

Hench, K.W.

1996-08-01

Reduction of the nuclear weapons stockpile and the general downsizing of the nuclear weapons complex has presented challenges for Los Alamos. One is to design an optimized fabrication facility to manufacture nuclear weapon primary components in an environment of intense regulation and shrinking budgets. This dissertation presents an integrative two-stage approach to modeling the casting operation for fabrication of nuclear weapon primary components. The first stage optimizes personnel radiation exposure for the casting operation layout by modeling the operation as a facility layout problem formulated as a quadratic assignment problem. The solution procedure uses an evolutionary heuristic technique. The best solutions to the layout problem are used as input to the second stage - a simulation model that assesses the impact of competing layouts on operational performance. The focus of the simulation model is to determine the layout that minimizes personnel radiation exposures and nuclear material movement, and maximizes the utilization of capacity for finished units.

Thermochemical modelling of multi-component systems

International Nuclear Information System (INIS)

Sundman, B.; Gueneau, C.

2015-01-01

Computational thermodynamic, also known as the Calphad method, is a standard tool in industry for the development of materials and improving processes and there is an intense scientific development of new models and databases. The calculations are based on thermodynamic models of the Gibbs energy for each phase as a function of temperature, pressure and constitution. Model parameters are stored in databases that are developed in an international scientific collaboration. In this way, consistent and reliable data for many properties like heat capacity, chemical potentials, solubilities etc. can be obtained for multi-component systems. A brief introduction to this technique is given here and references to more extensive documentation are provided. (authors)

Perceptual weights for loudness reflect central spectral processing

DEFF Research Database (Denmark)

Joshi, Suyash Narendra; Jesteadt, Walt

2011-01-01

Weighting patterns for loudness obtained using the reverse correlation method are thought to reveal the relative contributions of different frequency regions to total loudness, the equivalent of specific loudness. Current models of loudness assume that specific loudness is determined by peripheral...... processes such as compression and masking. Here we test this hypothesis using 20-tone harmonic complexes (200Hz f0, 200 to 4000Hz, 250 ms, 65 dB/Component) added in opposite phase relationships (Schroeder positive and negative). Due to the varying degree of envelope modulations, these time-reversed harmonic...... processes and reflect a central frequency weighting template....

Seismic assessment and performance of nonstructural components affected by structural modeling

Energy Technology Data Exchange (ETDEWEB)

Hur, Jieun; Althoff, Eric; Sezen, Halil; Denning, Richard; Aldemir, Tunc [Ohio State University, Columbus (United States)

2017-03-15

Seismic probabilistic risk assessment (SPRA) requires a large number of simulations to evaluate the seismic vulnerability of structural and nonstructural components in nuclear power plants. The effect of structural modeling and analysis assumptions on dynamic analysis of 3D and simplified 2D stick models of auxiliary buildings and the attached nonstructural components is investigated. Dynamic characteristics and seismic performance of building models are also evaluated, as well as the computational accuracy of the models. The presented results provide a better understanding of the dynamic behavior and seismic performance of auxiliary buildings. The results also help to quantify the impact of uncertainties associated with modeling and analysis of simplified numerical models of structural and nonstructural components subjected to seismic shaking on the predicted seismic failure probabilities of these systems.

A mass-density model can account for the size-weight illusion

Science.gov (United States)

Bergmann Tiest, Wouter M.; Drewing, Knut

2018-01-01

When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the large number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new maximum-likelihood estimation model which describes the illusion as the weighted average of two heaviness estimates with correlated noise: One estimate derived from the object’s mass, and the other from the object’s density, with estimates’ weights based on their relative reliabilities. While information about mass can directly be perceived, information about density will in some cases first have to be derived from mass and volume. However, according to our model at the crucial perceptual level, heaviness judgments will be biased by the objects’ density, not by its size. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. As predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object’s density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In an additional two-alternative forced choice heaviness experiment, we replicated that the illusion strength increased with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as a starting point for a unifying framework for the size-weight illusion and human heaviness

A mass-density model can account for the size-weight illusion.

Science.gov (United States)

Wolf, Christian; Bergmann Tiest, Wouter M; Drewing, Knut

2018-01-01

When judging the heaviness of two objects with equal mass, people perceive the smaller and denser of the two as being heavier. Despite the large number of theories, covering bottom-up and top-down approaches, none of them can fully account for all aspects of this size-weight illusion and thus for human heaviness perception. Here we propose a new maximum-likelihood estimation model which describes the illusion as the weighted average of two heaviness estimates with correlated noise: One estimate derived from the object's mass, and the other from the object's density, with estimates' weights based on their relative reliabilities. While information about mass can directly be perceived, information about density will in some cases first have to be derived from mass and volume. However, according to our model at the crucial perceptual level, heaviness judgments will be biased by the objects' density, not by its size. In two magnitude estimation experiments, we tested model predictions for the visual and the haptic size-weight illusion. Participants lifted objects which varied in mass and density. We additionally varied the reliability of the density estimate by varying the quality of either visual (Experiment 1) or haptic (Experiment 2) volume information. As predicted, with increasing quality of volume information, heaviness judgments were increasingly biased towards the object's density: Objects of the same density were perceived as more similar and big objects were perceived as increasingly lighter than small (denser) objects of the same mass. This perceived difference increased with an increasing difference in density. In an additional two-alternative forced choice heaviness experiment, we replicated that the illusion strength increased with the quality of volume information (Experiment 3). Overall, the results highly corroborate our model, which seems promising as a starting point for a unifying framework for the size-weight illusion and human heaviness perception.

A new weighted mean temperature model in China

Science.gov (United States)

Liu, Jinghong; Yao, Yibin; Sang, Jizhang

2018-01-01

The Global Positioning System (GPS) has been applied in meteorology to monitor the change of Precipitable Water Vapor (PWV) in atmosphere, transformed from Zenith Wet Delay (ZWD). A key factor in converting the ZWD into the PWV is the weighted mean temperature (Tm), which has a direct impact on the accuracy of the transformation. A number of Bevis-type models, like Tm -Ts and Tm -Ts,Ps type models, have been developed by statistics approaches, and are not able to clearly depict the relationship between Tm and the surface temperature, Ts . A new model for Tm , called weighted mean temperature norm model (abbreviated as norm model), is derived as a function of Ts , the lapse rate of temperature, δ, the tropopause height, htrop , and the radiosonde station height, hs . It is found that Tm is better related to Ts through an intermediate temperature. The small effects of lapse rate can be ignored and the tropopause height be obtained from an empirical model. Then the norm model is reduced to a simplified form, which causes fewer loss of accuracy and needs two inputs, Ts and hs . In site-specific fittings, the norm model performs much better, with RMS values reduced averagely by 0.45 K and the Mean of Absolute Differences (MAD) values by 0.2 K. The norm model is also found more appropriate than the linear models to fit Tm in a large area, not only with the RMS value reduced from 4.3 K to 3.80 K, correlation coefficient R2 increased from 0.84 to 0.88, and MAD decreased from 3.24 K to 2.90 K, but also with the distribution of simplified model values to be more reasonable. The RMS and MAD values of the differences between reference and computed PWVs are reduced by on average 16.3% and 14.27%, respectively, when using the new norm models instead of the linear model.

Prediction model of critical weight loss in cancer patients during particle therapy.

Science.gov (United States)

Zhang, Zhihong; Zhu, Yu; Zhang, Lijuan; Wang, Ziying; Wan, Hongwei

2018-01-01

The objective of this study is to investigate the predictors of critical weight loss in cancer patients receiving particle therapy, and build a prediction model based on its predictive factors. Patients receiving particle therapy were enroled between June 2015 and June 2016. Body weight was measured at the start and end of particle therapy. Association between critical weight loss (defined as >5%) during particle therapy and patients' demographic, clinical characteristic, pre-therapeutic nutrition risk screening (NRS 2002) and BMI were evaluated by logistic regression and decision tree analysis. Finally, 375 cancer patients receiving particle therapy were included. Mean weight loss was 0.55 kg, and 11.5% of patients experienced critical weight loss during particle therapy. The main predictors of critical weight loss during particle therapy were head and neck tumour location, total radiation dose ≥70 Gy on the primary tumour, and without post-surgery, as indicated by both logistic regression and decision tree analysis. Prediction model that includes tumour locations, total radiation dose and post-surgery had a good predictive ability, with the area under receiver operating characteristic curve 0.79 (95% CI: 0.71-0.88) and 0.78 (95% CI: 0.69-0.86) for decision tree and logistic regression model, respectively. Cancer patients with head and neck tumour location, total radiation dose ≥70 Gy and without post-surgery were at higher risk of critical weight loss during particle therapy, and early intensive nutrition counselling or intervention should be target at this population. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Weighted Low-Rank Approximation of Matrices and Background Modeling

KAUST Repository

Dutta, Aritra

2018-04-15

We primarily study a special a weighted low-rank approximation of matrices and then apply it to solve the background modeling problem. We propose two algorithms for this purpose: one operates in the batch mode on the entire data and the other one operates in the batch-incremental mode on the data and naturally captures more background variations and computationally more effective. Moreover, we propose a robust technique that learns the background frame indices from the data and does not require any training frames. We demonstrate through extensive experiments that by inserting a simple weight in the Frobenius norm, it can be made robust to the outliers similar to the $\\\\ell_1$ norm. Our methods match or outperform several state-of-the-art online and batch background modeling methods in virtually all quantitative and qualitative measures.

Weighted Low-Rank Approximation of Matrices and Background Modeling

KAUST Repository

Dutta, Aritra; Li, Xin; Richtarik, Peter

2018-01-01

We primarily study a special a weighted low-rank approximation of matrices and then apply it to solve the background modeling problem. We propose two algorithms for this purpose: one operates in the batch mode on the entire data and the other one operates in the batch-incremental mode on the data and naturally captures more background variations and computationally more effective. Moreover, we propose a robust technique that learns the background frame indices from the data and does not require any training frames. We demonstrate through extensive experiments that by inserting a simple weight in the Frobenius norm, it can be made robust to the outliers similar to the $\\ell_1$ norm. Our methods match or outperform several state-of-the-art online and batch background modeling methods in virtually all quantitative and qualitative measures.

Development of body weight support gait training system using antagonistic bi-articular muscle model.

Science.gov (United States)

Shibata, Yoshiyuki; Imai, Shingo; Nobutomo, Tatsuya; Miyoshi, Tasuku; Yamamoto, Shin-Ichiroh

2010-01-01

The purpose of this study is to develop a body weight support gait training system for stroke and spinal cord injury. This system consists of a powered orthosis, treadmill and equipment of body weight support. Attachment of the powered orthosis is able to fit subject who has difference of body size. This powered orthosis is driven by pneumatic McKibben actuator. Actuators are arranged as pair of antagonistic bi-articular muscle model and two pairs of antagonistic mono-articular muscle model like human musculoskeletal system. Part of the equipment of body weight support suspend subject by wire harness, and body weight of subject is supported continuously by counter weight. The powered orthosis is attached equipment of body weight support by parallel linkage, and movement of the powered orthosis is limited at sagittal plane. Weight of the powered orthosis is compensated by parallel linkage with gas-spring. In this study, we developed system that has orthosis powered by pneumatic McKibben actuators and equipment of body weight support. We report detail of our developed body weight support gait training system.

Bridging Weighted Rules and Graph Random Walks for Statistical Relational Models

Directory of Open Access Journals (Sweden)

Seyed Mehran Kazemi

2018-02-01

Full Text Available The aim of statistical relational learning is to learn statistical models from relational or graph-structured data. Three main statistical relational learning paradigms include weighted rule learning, random walks on graphs, and tensor factorization. These paradigms have been mostly developed and studied in isolation for many years, with few works attempting at understanding the relationship among them or combining them. In this article, we study the relationship between the path ranking algorithm (PRA, one of the most well-known relational learning methods in the graph random walk paradigm, and relational logistic regression (RLR, one of the recent developments in weighted rule learning. We provide a simple way to normalize relations and prove that relational logistic regression using normalized relations generalizes the path ranking algorithm. This result provides a better understanding of relational learning, especially for the weighted rule learning and graph random walk paradigms. It opens up the possibility of using the more flexible RLR rules within PRA models and even generalizing both by including normalized and unnormalized relations in the same model.

A Component-Based Modeling and Validation Method for PLC Systems

Directory of Open Access Journals (Sweden)

Rui Wang

2014-05-01

Full Text Available Programmable logic controllers (PLCs are complex embedded systems that are widely used in industry. This paper presents a component-based modeling and validation method for PLC systems using the behavior-interaction-priority (BIP framework. We designed a general system architecture and a component library for a type of device control system. The control software and hardware of the environment were all modeled as BIP components. System requirements were formalized as monitors. Simulation was carried out to validate the system model. A realistic example from industry of the gates control system was employed to illustrate our strategies. We found a couple of design errors during the simulation, which helped us to improve the dependability of the original systems. The results of experiment demonstrated the effectiveness of our approach.

Evaluating the effect of neighbourhood weight matrices on smoothing properties of Conditional Autoregressive (CAR models

Directory of Open Access Journals (Sweden)

Ryan Louise

2007-11-01

Full Text Available Abstract Background The Conditional Autoregressive (CAR model is widely used in many small-area ecological studies to analyse outcomes measured at an areal level. There has been little evaluation of the influence of different neighbourhood weight matrix structures on the amount of smoothing performed by the CAR model. We examined this issue in detail. Methods We created several neighbourhood weight matrices and applied them to a large dataset of births and birth defects in New South Wales (NSW, Australia within 198 Statistical Local Areas. Between the years 1995–2003, there were 17,595 geocoded birth defects and 770,638 geocoded birth records with available data. Spatio-temporal models were developed with data from 1995–2000 and their fit evaluated within the following time period: 2001–2003. Results We were able to create four adjacency-based weight matrices, seven distance-based weight matrices and one matrix based on similarity in terms of a key covariate (i.e. maternal age. In terms of agreement between observed and predicted relative risks, categorised in epidemiologically relevant groups, generally the distance-based matrices performed better than the adjacency-based neighbourhoods. In terms of recovering the underlying risk structure, the weight-7 model (smoothing by maternal-age 'Covariate model' was able to correctly classify 35/47 high-risk areas (sensitivity 74% with a specificity of 47%, and the 'Gravity' model had sensitivity and specificity values of 74% and 39% respectively. Conclusion We found considerable differences in the smoothing properties of the CAR model, depending on the type of neighbours specified. This in turn had an effect on the models' ability to recover the observed risk in an area. Prior to risk mapping or ecological modelling, an exploratory analysis of the neighbourhood weight matrix to guide the choice of a suitable weight matrix is recommended. Alternatively, the weight matrix can be chosen a priori

Relationship between the fluidity of heat-treated coals and molecular weight distributions of their solvent-soluble component; Netsushoritan no yobai kayo seibun no bunshiryo bunpu to ryudosei no kanren

Energy Technology Data Exchange (ETDEWEB)

Yoshida, T.; Takanohashi, T.; Iino, M. [Tohoku University, Sendai (Japan). Institute for Chemical Reaction Science; Kato, K. [Nippon Steel Co. Ltd., Tokyo (Japan); Fukada, K. [NKK Corp., Tokyo (Japan)

1996-10-28

In order to improve the coke manufacturing process, considerations were given on fluidity manifestation mechanism of heat-treated coals from molecular weight distributions of extracts of a solvent mixed with CS2-N-methyl-2-pyrrolidinone (CS2-NMP). The heat treatment was performed in an autoclave under nitrogen atmosphere at a rate of 3{degree}C/min to settings of 200 to 550{degree}C. The resultant heat-treated coal was quenched, and then extracted by using the CS2-NMP mixed solvent. The fluidity was measured by using a Gieseler plastometer. Maximum extraction rate and the highest fluidity are in linear relationship, which suggests that the extracts govern the fluidity. Since heavy caking coal has no difference in the extraction rates due to heat treatment temperature, and its molecular weight distribution trend does not change, the extracted components which have existed primarily in the original coal govern the fluidity. In semi-caking coals, polymer molecular components are extracted in a large quantity at the softening starting temperature, but the quantity decreases as the temperature rises. However, low-molecular components present no quantitative change, while polymer molecular components decompose, decrease in molecular weight, get solubilized with rising temperature, and act as a binder to cause a flow. 7 figs., 1 tab.

Data and information needs for WPP testing and component modeling

International Nuclear Information System (INIS)

Kuhn, W.L.

1987-01-01

The modeling task of the Waste Package Program (WPP) is to develop conceptual models that describe the interactions of waste package components with their environment and the interactions among waste package components. The task includes development and maintenance of a database of experimental data, and statistical analyses to fit model coefficients, test the significance of the fits, and propose experimental designs. The modeling task collaborates with experimentalists to apply physicochemical principles to develop the conceptual models, with emphasis on the subsequent mathematical development. The reason for including the modeling task in the predominantly experimental WPP is to keep the modeling of component behavior closely associated with the experimentation. Whenever possible, waste package degradation processes are described in terms of chemical reactions or transport processes. The integration of equations for assumed or calculated repository conditions predicts variations with time in the repository. Within the context of the waste package program, the composition and rate of arrival of brine to the waste package are environmental variables. These define the environment to be simulated or explored during waste package component and interactions testing. The containment period is characterized by rapid changes in temperature, pressure, oxygen fugacity, and salt porosity. Brine migration is expected to be most rapid during this period. The release period is characterized by modest and slowly changing temperatures, high pressure, low oxygen fugacity, and low porosity. The need is to define the scenario within which waste package degradation calculations are to be made and to quantify the rate of arrival and composition of the brine. Appendix contains 4 vugraphs

Sistem Pendukung Keputusan Pemilihan Perguruan Tinggi Swasta Terbaik Jurusan Komputer Menggunakan Metode Weighted Product dan Weighted Sum Model (Studi Kasus : Perguruan Tinggi Swasta)

OpenAIRE

Tampubolon, Meabeng

2016-01-01

Decision support system (DSS) is a system that can assist a person in making decisions more effectively and efficiently. Given this system, problems faced can be solved, such as the determination of the best private universities. There beberpa methods that can be used in building a Weighted Method SPK like product and weighted sum models. Methods weighted product (WP) use multiplication to connect rating attributes, where each rating should be used with attribute weights pangka...

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

Science.gov (United States)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Dynamics of an SAITS alcoholism model on unweighted and weighted networks

Science.gov (United States)

Huo, Hai-Feng; Cui, Fang-Fang; Xiang, Hong

2018-04-01

A novel SAITS alcoholism model on networks is introduced, in which alcoholics are divided into light problem alcoholics and heavy problem alcoholics. Susceptible individuals can enter into the compartment of heavy problem alcoholics directly by contacting with light problem alcoholics or heavy problem alcoholics and the heavy problem alcoholics who receive treatment can relapse into the compartment of heavy problem alcoholics are also considered. First, the dynamics of our model on unweighted networks, including the basic reproduction number, existence and stability of equilibria are studied. Second, the models with fixed weighted and adaptive weighted networks are introduced and investigated. At last, some simulations are presented to illustrate and extend our results. Our results show that it is very important to treat alcoholics to quit the drinking.

A proposed centralised distribution model for the South African automotive component industry

Directory of Open Access Journals (Sweden)

Micheline J. Naude

2009-12-01

Full Text Available Purpose: This article explores the possibility of developing a distribution model, similar to the model developed and implemented by the South African pharmaceutical industry, which could be implemented by automotive component manufacturers for supply to independent retailers. Problem Investigated: The South African automotive components distribution chain is extensive with a number of players of varying sizes, from the larger spares distribution groups to a number of independent retailers. Distributing to the smaller independent retailers is costly for the automotive component manufacturers. Methodology: This study is based on a preliminary study of an explorative nature. Interviews were conducted with a senior staff member from a leading automotive component manufacturer in KwaZulu Natal and nine participants at a senior management level at five of their main customers (aftermarket retailers. Findings: The findings from the empirical study suggest that the aftermarket component industry is mature with the role players well established. The distribution chain to the independent retailer is expensive in terms of transaction and distribution costs for the automotive component manufacturer. A proposed centralised distribution model for supply to independent retailers has been developed which should reduce distribution costs for the automotive component manufacturer in terms of (1 the lowest possible freight rate; (2 timely and controlled delivery; and (3 reduced congestion at the customer's receiving dock. Originality: This research is original in that it explores the possibility of implementing a centralised distribution model for independent retailers in the automotive component industry. Furthermore, there is a dearth of published research on the South African automotive component industry particularly addressing distribution issues. Conclusion: The distribution model as suggested is a practical one and should deliver added value to automotive

Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors

KAUST Repository

Simpson, Daniel

2017-04-06

In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys\\' priors, are designed to support Occam\\'s razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.

Penalising Model Component Complexity: A Principled, Practical Approach to Constructing Priors

KAUST Repository

Simpson, Daniel; Rue, Haavard; Riebler, Andrea; Martins, Thiago G.; Sø rbye, Sigrunn H.

2017-01-01

In this paper, we introduce a new concept for constructing prior distributions. We exploit the natural nested structure inherent to many model components, which defines the model component to be a flexible extension of a base model. Proper priors are defined to penalise the complexity induced by deviating from the simpler base model and are formulated after the input of a user-defined scaling parameter for that model component, both in the univariate and the multivariate case. These priors are invariant to repa-rameterisations, have a natural connection to Jeffreys' priors, are designed to support Occam's razor and seem to have excellent robustness properties, all which are highly desirable and allow us to use this approach to define default prior distributions. Through examples and theoretical results, we demonstrate the appropriateness of this approach and how it can be applied in various situations.

Introduction of the transtheoretical model and organisational development theory in weight management: A narrative review.

Science.gov (United States)

Wu, Ya-Ke; Chu, Nain-Feng

2015-01-01

Overweight and obesity are serious public health and medical problems among children and adults worldwide. Behavioural change has been demonstrably contributory to weight management programs. Behavioural change-based weight loss programs require a theoretical framework. We will review the transtheoretical model and the organisational development theory in weight management. The transtheoretical model is a behaviour theory of individual level frequently used for weight management programs. The organisational development theory is a more complicated behaviour theory that applies to behavioural change on the system level. Both of these two theories have their respective strengths and weaknesses. In this manuscript, we try to introduce the transtheoretical model and the organisational development theory in the context of weight loss programs among population that are overweight or obese. Ultimately, we wish to present a new framework/strategy of weight management by integrating these two theories together. Copyright © 2015 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Reliability analysis of nuclear component cooling water system using semi-Markov process model

International Nuclear Information System (INIS)

Veeramany, Arun; Pandey, Mahesh D.

2011-01-01

Research highlights: → Semi-Markov process (SMP) model is used to evaluate system failure probability of the nuclear component cooling water (NCCW) system. → SMP is used because it can solve reliability block diagram with a mixture of redundant repairable and non-repairable components. → The primary objective is to demonstrate that SMP can consider Weibull failure time distribution for components while a Markov model cannot → Result: the variability in component failure time is directly proportional to the NCCW system failure probability. → The result can be utilized as an initiating event probability in probabilistic safety assessment projects. - Abstract: A reliability analysis of nuclear component cooling water (NCCW) system is carried out. Semi-Markov process model is used in the analysis because it has potential to solve a reliability block diagram with a mixture of repairable and non-repairable components. With Markov models it is only possible to assume an exponential profile for component failure times. An advantage of the proposed model is the ability to assume Weibull distribution for the failure time of components. In an attempt to reduce the number of states in the model, it is shown that usage of poly-Weibull distribution arises. The objective of the paper is to determine system failure probability under these assumptions. Monte Carlo simulation is used to validate the model result. This result can be utilized as an initiating event probability in probabilistic safety assessment projects.

Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis

Directory of Open Access Journals (Sweden)

Xiaoming Xu

2017-01-01

Full Text Available In traditional principle component analysis (PCA, because of the neglect of the dimensions influence between different variables in the system, the selected principal components (PCs often fail to be representative. While the relative transformation PCA is able to solve the above problem, it is not easy to calculate the weight for each characteristic variable. In order to solve it, this paper proposes a kind of fault diagnosis method based on information entropy and Relative Principle Component Analysis. Firstly, the algorithm calculates the information entropy for each characteristic variable in the original dataset based on the information gain algorithm. Secondly, it standardizes every variable’s dimension in the dataset. And, then, according to the information entropy, it allocates the weight for each standardized characteristic variable. Finally, it utilizes the relative-principal-components model established for fault diagnosis. Furthermore, the simulation experiments based on Tennessee Eastman process and Wine datasets demonstrate the feasibility and effectiveness of the new method.

Focused information criterion and model averaging based on weighted composite quantile regression

KAUST Repository

Xu, Ganggang; Wang, Suojin; Huang, Jianhua Z.

2013-01-01

We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non

Bioactivity of Minor Milk Components

DEFF Research Database (Denmark)

Nguyen, Duc Ninh

. In particular, 3-15% of very low birth weight preterm infants suffer from the most servere form of intestinal inflammation, known as necrotizing enterocolitis (NEC). This disease is incurable with a high mortality rate of 15-30%. Mother’s breast milk consists of different bioactive constituents...... of infant formula. Thereafter, bioactive milk components which were preserved in gently-processed infant formula were selected for further investigation of their immunomodulatory activity in cell and preterm pig models. We hope this project will contribute to the research on the development of new...

Evaluating fugacity models for trace components in landfill gas

Energy Technology Data Exchange (ETDEWEB)

Shafi, Sophie [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Sweetman, Andrew [Department of Environmental Science, Lancaster University, Lancaster LA1 4YQ (United Kingdom); Hough, Rupert L. [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Smith, Richard [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom); Rosevear, Alan [Science Group - Waste and Remediation, Environment Agency, Reading RG1 8DQ (United Kingdom); Pollard, Simon J.T. [Integrated Waste Management Centre, Sustainable Systems Department, Building 61, School of Industrial and Manufacturing Science, Cranfield University, Cranfield, Bedfordshire MK43 0AL (United Kingdom)]. E-mail: s.pollard@cranfield.ac.uk

2006-12-15

A fugacity approach was evaluated to reconcile loadings of vinyl chloride (chloroethene), benzene, 1,3-butadiene and trichloroethylene in waste with concentrations observed in landfill gas monitoring studies. An evaluative environment derived from fictitious but realistic properties such as volume, composition, and temperature, constructed with data from the Brogborough landfill (UK) test cells was used to test a fugacity approach to generating the source term for use in landfill gas risk assessment models (e.g. GasSim). SOILVE, a dynamic Level II model adapted here for landfills, showed greatest utility for benzene and 1,3-butadiene, modelled under anaerobic conditions over a 10 year simulation. Modelled concentrations of these components (95 300 {mu}g m{sup -3}; 43 {mu}g m{sup -3}) fell within measured ranges observed in gas from landfills (24 300-180 000 {mu}g m{sup -3}; 20-70 {mu}g m{sup -3}). This study highlights the need (i) for representative and time-referenced biotransformation data; (ii) to evaluate the partitioning characteristics of organic matter within waste systems and (iii) for a better understanding of the role that gas extraction rate (flux) plays in producing trace component concentrations in landfill gas. - Fugacity for trace component in landfill gas.

A minimal model for two-component dark matter

International Nuclear Information System (INIS)

Esch, Sonja; Klasen, Michael; Yaguna, Carlos E.

2014-01-01

We propose and study a new minimal model for two-component dark matter. The model contains only three additional fields, one fermion and two scalars, all singlets under the Standard Model gauge group. Two of these fields, one fermion and one scalar, are odd under a Z_2 symmetry that renders them simultaneously stable. Thus, both particles contribute to the observed dark matter density. This model resembles the union of the singlet scalar and the singlet fermionic models but it contains some new features of its own. We analyze in some detail its dark matter phenomenology. Regarding the relic density, the main novelty is the possible annihilation of one dark matter particle into the other, which can affect the predicted relic density in a significant way. Regarding dark matter detection, we identify a new contribution that can lead either to an enhancement or to a suppression of the spin-independent cross section for the scalar dark matter particle. Finally, we define a set of five benchmarks models compatible with all present bounds and examine their direct detection prospects at planned experiments. A generic feature of this model is that both particles give rise to observable signals in 1-ton direct detection experiments. In fact, such experiments will be able to probe even a subdominant dark matter component at the percent level.

Integrating environmental component models. Development of a software framework

NARCIS (Netherlands)

Schmitz, O.

2014-01-01

Integrated models consist of interacting component models that represent various natural and social systems. They are important tools to improve our understanding of environmental systems, to evaluate cause–effect relationships of human–natural interactions, and to forecast the behaviour of

Effects of different components of Mao Dongqing's total flavonoids and total saponins on transient ischemic attack (TIA) model of rats.

Science.gov (United States)

Miao, Ming-San; Peng, Meng-Fan; Ma, Rui-Juan; Bai, Ming; Liu, Bao-Song

2018-03-01

Objective: To study the effects of the different components of the total flavonoids and total saponins from Mao Dongqing's active site on the rats of TIA model, determine the optimal reactive components ratio of Mao Dongqing on the rats of TIA. Methods: TIA rat model was induced by tail vein injection of tert butyl alcohol, the blank group was injected with the same amount of physiological saline, then behavioral score wasevaluated. Determination the level of glutamic acid in serum, the activity of Na+-K+-ATP enzyme, CA ++ -ATP enzyme and Mg ++ -ATP enzyme in Brain tissue, observe the changes of hippocampus in brain tissue, the comprehensive weight method was used to evaluate the efficacy of each component finally. Results: The contents of total flavonoids and total saponins in the active part of Mao Dongqing can significantly improve the pathological changes of brain tissue in rats, improve the activity of Na + -K + -ATP enzyme, Ca ++ -ATP enzyme and Mg ++ -ATP enzyme in the brain of rats, and reduce the level of glutamic acid in serum. The most significant of the contents was the ratio of 10:6. The different proportions of total flavonoids and total saponins in the active part of Mao Dongqing all has a better effect on the rats with TIA, and the ratio of 10:6 is the best active component for preventing and controlling TIA.

Generalized modeling of multi-component vaporization/condensation phenomena for multi-phase-flow analysis

International Nuclear Information System (INIS)

Morita, K.; Fukuda, K.; Tobita, Y.; Kondo, Sa.; Suzuki, T.; Maschek, W.

2003-01-01

A new multi-component vaporization/condensation (V/C) model was developed to provide a generalized model for safety analysis codes of liquid metal cooled reactors (LMRs). These codes simulate thermal-hydraulic phenomena of multi-phase, multi-component flows, which is essential to investigate core disruptive accidents of LMRs such as fast breeder reactors and accelerator driven systems. The developed model characterizes the V/C processes associated with phase transition by employing heat transfer and mass-diffusion limited models for analyses of relatively short-time-scale multi-phase, multi-component hydraulic problems, among which vaporization and condensation, or simultaneous heat and mass transfer, play an important role. The heat transfer limited model describes the non-equilibrium phase transition processes occurring at interfaces, while the mass-diffusion limited model is employed to represent effects of non-condensable gases and multi-component mixture on V/C processes. Verification of the model and method employed in the multi-component V/C model of a multi-phase flow code was performed successfully by analyzing a series of multi-bubble condensation experiments. The applicability of the model to the accident analysis of LMRs is also discussed by comparison between steam and metallic vapor systems. (orig.)

Prostate cancer detection from model-free T1-weighted time series and diffusion imaging

Science.gov (United States)

Haq, Nandinee F.; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi

2015-03-01

The combination of Dynamic Contrast Enhanced (DCE) images with diffusion MRI has shown great potential in prostate cancer detection. The parameterization of DCE images to generate cancer markers is traditionally performed based on pharmacokinetic modeling. However, pharmacokinetic models make simplistic assumptions about the tissue perfusion process, require the knowledge of contrast agent concentration in a major artery, and the modeling process is sensitive to noise and fitting instabilities. We address this issue by extracting features directly from the DCE T1-weighted time course without modeling. In this work, we employed a set of data-driven features generated by mapping the DCE T1 time course to its principal component space, along with diffusion MRI features to detect prostate cancer. The optimal set of DCE features is extracted with sparse regularized regression through a Least Absolute Shrinkage and Selection Operator (LASSO) model. We show that when our proposed features are used within the multiparametric MRI protocol to replace the pharmacokinetic parameters, the area under ROC curve is 0.91 for peripheral zone classification and 0.87 for whole gland classification. We were able to correctly classify 32 out of 35 peripheral tumor areas identified in the data when the proposed features were used with support vector machine classification. The proposed feature set was used to generate cancer likelihood maps for the prostate gland.

Equivalent charge source model based iterative maximum neighbor weight for sparse EEG source localization.

Science.gov (United States)

Xu, Peng; Tian, Yin; Lei, Xu; Hu, Xiao; Yao, Dezhong

2008-12-01

How to localize the neural electric activities within brain effectively and precisely from the scalp electroencephalogram (EEG) recordings is a critical issue for current study in clinical neurology and cognitive neuroscience. In this paper, based on the charge source model and the iterative re-weighted strategy, proposed is a new maximum neighbor weight based iterative sparse source imaging method, termed as CMOSS (Charge source model based Maximum neighbOr weight Sparse Solution). Different from the weight used in focal underdetermined system solver (FOCUSS) where the weight for each point in the discrete solution space is independently updated in iterations, the new designed weight for each point in each iteration is determined by the source solution of the last iteration at both the point and its neighbors. Using such a new weight, the next iteration may have a bigger chance to rectify the local source location bias existed in the previous iteration solution. The simulation studies with comparison to FOCUSS and LORETA for various source configurations were conducted on a realistic 3-shell head model, and the results confirmed the validation of CMOSS for sparse EEG source localization. Finally, CMOSS was applied to localize sources elicited in a visual stimuli experiment, and the result was consistent with those source areas involved in visual processing reported in previous studies.

Chronic treatment with antipsychotics in rats as a model for antipsychotic-induced weight gain in human

DEFF Research Database (Denmark)

Pouzet, B; Mow, T; Kreilgaard, Mads

2003-01-01

compounds in an animal model of weight gain. With the aim of evaluating whether the rat can be used as a model for antipsychotic-induced weight gain, we have investigated the effect of chronic treatment (3 weeks) with one antipsychotic drug inducing weight gain in clinic (olanzapine) and one antipsychotic...

Analysis of litter size and average litter weight in pigs using a recursive model

DEFF Research Database (Denmark)

Varona, Luis; Sorensen, Daniel; Thompson, Robin

2007-01-01

An analysis of litter size and average piglet weight at birth in Landrace and Yorkshire using a standard two-trait mixed model (SMM) and a recursive mixed model (RMM) is presented. The RMM establishes a one-way link from litter size to average piglet weight. It is shown that there is a one......-to-one correspondence between the parameters of SMM and RMM and that they generate equivalent likelihoods. As parameterized in this work, the RMM tests for the presence of a recursive relationship between additive genetic values, permanent environmental effects, and specific environmental effects of litter size......, on average piglet weight. The equivalent standard mixed model tests whether or not the covariance matrices of the random effects have a diagonal structure. In Landrace, posterior predictive model checking supports a model without any form of recursion or, alternatively, a SMM with diagonal covariance...

Estimation of genetic parameters for body weights of Kurdish sheep ...

African Journals Online (AJOL)

Genetic parameters and (co)variance components were estimated by restricted maximum likelihood (REML) procedure, using animal models of kind 1, 2, 3, 4, 5 and 6, for body weight in birth, three, six, nine and 12 months of age in a Kurdish sheep flock. Direct and maternal breeding values were estimated using the best ...

Composition-Based Prediction of Temperature-Dependent Thermophysical Food Properties: Reevaluating Component Groups and Prediction Models.

Science.gov (United States)

Phinney, David Martin; Frelka, John C; Heldman, Dennis Ray

2017-01-01

Prediction of temperature-dependent thermophysical properties (thermal conductivity, density, specific heat, and thermal diffusivity) is an important component of process design for food manufacturing. Current models for prediction of thermophysical properties of foods are based on the composition, specifically, fat, carbohydrate, protein, fiber, water, and ash contents, all of which change with temperature. The objectives of this investigation were to reevaluate and improve the prediction expressions for thermophysical properties. Previously published data were analyzed over the temperature range from 10 to 150 °C. These data were analyzed to create a series of relationships between the thermophysical properties and temperature for each food component, as well as to identify the dependence of the thermophysical properties on more specific structural properties of the fats, carbohydrates, and proteins. Results from this investigation revealed that the relationships between the thermophysical properties of the major constituents of foods and temperature can be statistically described by linear expressions, in contrast to the current polynomial models. Links between variability in thermophysical properties and structural properties were observed. Relationships for several thermophysical properties based on more specific constituents have been identified. Distinctions between simple sugars (fructose, glucose, and lactose) and complex carbohydrates (starch, pectin, and cellulose) have been proposed. The relationships between the thermophysical properties and proteins revealed a potential correlation with the molecular weight of the protein. The significance of relating variability in constituent thermophysical properties with structural properties--such as molecular mass--could significantly improve composition-based prediction models and, consequently, the effectiveness of process design. © 2016 Institute of Food Technologists®.

Exposure–response model for sibutramine and placebo: suggestion for application to long-term weight-control drug development

Science.gov (United States)

Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok

2015-01-01

No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure–response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure–response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects’ sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure–response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs. PMID:26392753

Exposure-response model for sibutramine and placebo: suggestion for application to long-term weight-control drug development.

Science.gov (United States)

Han, Seunghoon; Jeon, Sangil; Hong, Taegon; Lee, Jongtae; Bae, Soo Hyeon; Park, Wan-su; Park, Gab-jin; Youn, Sunil; Jang, Doo Yeon; Kim, Kyung-Soo; Yim, Dong-Seok

2015-01-01

No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure-response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120). Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure-response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects' sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg) and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure-response model, which included the placebo effect, is the first example of a quantitative model that can be used to predict the efficacy of weight-control drugs. Similar approaches can help decision-making during clinical development of novel weight-loss drugs.

Analytical probabilistic modeling of RBE-weighted dose for ion therapy

Science.gov (United States)

Wieser, H. P.; Hennig, P.; Wahl, N.; Bangert, M.

2017-12-01

Particle therapy is especially prone to uncertainties. This issue is usually addressed with uncertainty quantification and minimization techniques based on scenario sampling. For proton therapy, however, it was recently shown that it is also possible to use closed-form computations based on analytical probabilistic modeling (APM) for this purpose. APM yields unique features compared to sampling-based approaches, motivating further research in this context. This paper demonstrates the application of APM for intensity-modulated carbon ion therapy to quantify the influence of setup and range uncertainties on the RBE-weighted dose. In particular, we derive analytical forms for the nonlinear computations of the expectation value and variance of the RBE-weighted dose by propagating linearly correlated Gaussian input uncertainties through a pencil beam dose calculation algorithm. Both exact and approximation formulas are presented for the expectation value and variance of the RBE-weighted dose and are subsequently studied in-depth for a one-dimensional carbon ion spread-out Bragg peak. With V and B being the number of voxels and pencil beams, respectively, the proposed approximations induce only a marginal loss of accuracy while lowering the computational complexity from order O(V × B^2) to O(V × B) for the expectation value and from O(V × B^4) to O(V × B^2) for the variance of the RBE-weighted dose. Moreover, we evaluated the approximated calculation of the expectation value and standard deviation of the RBE-weighted dose in combination with a probabilistic effect-based optimization on three patient cases considering carbon ions as radiation modality against sampled references. The resulting global γ-pass rates (2 mm,2%) are > 99.15% for the expectation value and > 94.95% for the standard deviation of the RBE-weighted dose, respectively. We applied the derived analytical model to carbon ion treatment planning, although the concept is in general applicable to other

Parental perspectives regarding primary-care weight-management strategies for school-age children.

Science.gov (United States)

Turer, Christy Boling; Mehta, Megha; Durante, Richard; Wazni, Fatima; Flores, Glenn

2016-04-01

To identify parental perspectives regarding weight-management strategies for school-age children, focus groups were conducted of parents of overweight and obese (body mass index ≥ 85th percentile) 6-12-year-old children recruited from primary-care clinics. Questions focused on the role of the primary-care provider, effective components of weight-management strategies and feasibility of specific dietary strategies. Focus groups were recorded, transcribed and analysed using margin coding and grounded theory. Six focus groups were held. The mean age (in years) for parents was 32, and for children, eight; 44% of participants were Latino, 33%, African-American and 23%, white. Parents' recommendations on the primary-care provider's role in weight management included monitoring weight, providing guidance regarding health risks and lifestyle changes, consistent follow-up and using discretion during weight discussions. Weight-management components identified as key included emphasising healthy lifestyles and enjoyment, small changes to routines and parental role modelling. Parents prefer guidance regarding healthy dietary practices rather than specific weight-loss diets, but identified principles that could enhance the acceptability of these diets. For dietary guidance to be feasible, parents recommended easy-to-follow instructions and emphasising servings over counting calories. Effective weight-management strategies identified by parents include primary-care provider engagement in weight management, simple instructions regarding healthy lifestyle changes, parental involvement and deemphasising specific weight-loss diets. These findings may prove useful in developing primary-care weight-management strategies for children that maximise parental acceptance. © 2014 John Wiley & Sons Ltd.

A New Integrated Weighted Model in SNOW-V10: Verification of Categorical Variables

Science.gov (United States)

Huang, Laura X.; Isaac, George A.; Sheng, Grant

2014-01-01

This paper presents the verification results for nowcasts of seven categorical variables from an integrated weighted model (INTW) and the underlying numerical weather prediction (NWP) models. Nowcasting, or short range forecasting (0-6 h), over complex terrain with sufficient accuracy is highly desirable but a very challenging task. A weighting, evaluation, bias correction and integration system (WEBIS) for generating nowcasts by integrating NWP forecasts and high frequency observations was used during the Vancouver 2010 Olympic and Paralympic Winter Games as part of the Science of Nowcasting Olympic Weather for Vancouver 2010 (SNOW-V10) project. Forecast data from Canadian high-resolution deterministic NWP system with three nested grids (at 15-, 2.5- and 1-km horizontal grid-spacing) were selected as background gridded data for generating the integrated nowcasts. Seven forecast variables of temperature, relative humidity, wind speed, wind gust, visibility, ceiling and precipitation rate are treated as categorical variables for verifying the integrated weighted forecasts. By analyzing the verification of forecasts from INTW and the NWP models among 15 sites, the integrated weighted model was found to produce more accurate forecasts for the 7 selected forecast variables, regardless of location. This is based on the multi-categorical Heidke skill scores for the test period 12 February to 21 March 2010.

Basic separative power of multi-component isotopes separation in a gas centrifuge

International Nuclear Information System (INIS)

Jiang, Hongmin; Lei, Zengguang; Zhuge, Fu

2008-01-01

On condition that the overall separation factor per unit exists in centrifuge for multi-component isotopes separation, the relations between separative power of each component and molecular weight have been investigated in the paper while the value function and the separative power of binary-component separation are adopted. The separative power of each component is proportional to the square of the molecular weight difference between its molecular weight and the average molecular weight of other remnant components. In addition, these relations are independent on the number of the components and feed concentrations. The basic separative power and related expressions, suggested in the paper, can be used for estimating the separative power of each component and analyzing the separation characteristics. The most valuable application of the basic separative power is to evaluate the separative capacity of centrifuge for multi-component isotopes. (author)

Low-level profiling and MARTE-compatible modeling of software components for real-time systems

NARCIS (Netherlands)

Triantafyllidis, K.; Bondarev, E.; With, de P.H.N.

2012-01-01

In this paper, we present a method for (a) profiling of individual components at high accuracy level, (b) modeling of the components with the accurate data obtained from profiling, and (c) model conversion to the MARTE profile. The resulting performance models of individual components are used at

Efficacy of a "small-changes" workplace weight loss initiative on weight and productivity outcomes.

Science.gov (United States)

Zinn, Caryn; Schofield, Grant M; Hopkins, Will G

2012-10-01

The effect of weight reduction on workplace productivity is unknown. We have investigated a "small-changes" workplace weight loss intervention on weight and productivity outcomes. Overweight/obese employees at two New Zealand worksites (n = 102) received the 12-week intervention. One site received an extra 9-month weight-maintenance component. Magnitudes of effects on weight and productivity were assessed via standardization. Both groups reduced weight at 12 weeks and maintained lost weight at 12 months. There were small possible improvements in productivity at one worksite and trivial reductions at the other by 12 weeks, with little subsequent change during maintenance in either group. At an individual level, weight change was associated with at most only small improvements or small reductions in productivity. Workplace weight loss initiatives may need to be more intensive or multidimensional to enhance productivity.

Component Degradation Susceptibilities As The Bases For Modeling Reactor Aging Risk

International Nuclear Information System (INIS)

Unwin, Stephen D.; Lowry, Peter P.; Toyooka, Michael Y.

2010-01-01

The extension of nuclear power plant operating licenses beyond 60 years in the United States will be necessary if we are to meet national energy needs while addressing the issues of carbon and climate. Characterizing the operating risks associated with aging reactors is problematic because the principal tool for risk-informed decision-making, Probabilistic Risk Assessment (PRA), is not ideally-suited to addressing aging systems. The components most likely to drive risk in an aging reactor - the passives - receive limited treatment in PRA, and furthermore, standard PRA methods are based on the assumption of stationary failure rates: a condition unlikely to be met in an aging system. A critical barrier to modeling passives aging on the wide scale required for a PRA is that there is seldom sufficient field data to populate parametric failure models, and nor is there the availability of practical physics models to predict out-year component reliability. The methodology described here circumvents some of these data and modeling needs by using materials degradation metrics, integrated with conventional PRA models, to produce risk importance measures for specific aging mechanisms and component types. We suggest that these measures have multiple applications, from the risk-screening of components to the prioritization of materials research.

The attention-weighted sample-size model of visual short-term memory

DEFF Research Database (Denmark)

Smith, Philip L.; Lilburn, Simon D.; Corbett, Elaine A.

2016-01-01

exceeded that predicted by the sample-size model for both simultaneously and sequentially presented stimuli. Instead, the set-size effect and the serial position curves with sequential presentation were predicted by an attention-weighted version of the sample-size model, which assumes that one of the items...

Sparse Principal Component Analysis in Medical Shape Modeling

DEFF Research Database (Denmark)

Sjöstrand, Karl; Stegmann, Mikkel Bille; Larsen, Rasmus

2006-01-01

Principal component analysis (PCA) is a widely used tool in medical image analysis for data reduction, model building, and data understanding and exploration. While PCA is a holistic approach where each new variable is a linear combination of all original variables, sparse PCA (SPCA) aims...... analysis in medicine. Results for three different data sets are given in relation to standard PCA and sparse PCA by simple thresholding of sufficiently small loadings. Focus is on a recent algorithm for computing sparse principal components, but a review of other approaches is supplied as well. The SPCA...

Quantifying the weight of fingerprint evidence through the spatial relationship, directions and types of minutiae observed on fingermarks.

Science.gov (United States)

Neumann, Cedric; Champod, Christophe; Yoo, Mina; Genessay, Thibault; Langenburg, Glenn

2015-03-01

This paper presents a statistical model for the quantification of the weight of fingerprint evidence. Contrarily to previous models (generative and score-based models), our model proposes to estimate the probability distributions of spatial relationships, directions and types of minutiae observed on fingerprints for any given fingermark. Our model is relying on an AFIS algorithm provided by 3M Cogent and on a dataset of more than 4,000,000 fingerprints to represent a sample from a relevant population of potential sources. The performance of our model was tested using several hundreds of minutiae configurations observed on a set of 565 fingermarks. In particular, the effects of various sub-populations of fingers (i.e., finger number, finger general pattern) on the expected evidential value of our test configurations were investigated. The performance of our model indicates that the spatial relationship between minutiae carries more evidential weight than their type or direction. Our results also indicate that the AFIS component of our model directly enables us to assign weight to fingerprint evidence without the need for the additional layer of complex statistical modeling involved by the estimation of the probability distributions of fingerprint features. In fact, it seems that the AFIS component is more sensitive to the sub-population effects than the other components of the model. Overall, the data generated during this research project contributes to support the idea that fingerprint evidence is a valuable forensic tool for the identification of individuals. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Photonic Beamformer Model Based on Analog Fiber-Optic Links’ Components

International Nuclear Information System (INIS)

Volkov, V A; Gordeev, D A; Ivanov, S I; Lavrov, A P; Saenko, I I

2016-01-01

The model of photonic beamformer for wideband microwave phased array antenna is investigated. The main features of the photonic beamformer model based on true-time-delay technique, DWDM technology and fiber chromatic dispersion are briefly analyzed. The performance characteristics of the key components of photonic beamformer for phased array antenna in the receive mode are examined. The beamformer model composed of the components available on the market of fiber-optic analog communication links is designed and tentatively investigated. Experimental demonstration of the designed model beamforming features includes actual measurement of 5-element microwave linear array antenna far-field patterns in 6-16 GHz frequency range for antenna pattern steering up to 40°. The results of experimental testing show good accordance with the calculation estimates. (paper)

Relative Error Model Reduction via Time-Weighted Balanced Stochastic Singular Perturbation

DEFF Research Database (Denmark)

Tahavori, Maryamsadat; Shaker, Hamid Reza

2012-01-01

A new mixed method for relative error model reduction of linear time invariant (LTI) systems is proposed in this paper. This order reduction technique is mainly based upon time-weighted balanced stochastic model reduction method and singular perturbation model reduction technique. Compared...... by using the concept and properties of the reciprocal systems. The results are further illustrated by two practical numerical examples: a model of CD player and a model of the atmospheric storm track....

Research on development model of nuclear component based on life cycle management

International Nuclear Information System (INIS)

Bao Shiyi; Zhou Yu; He Shuyan

2005-01-01

At present the development process of nuclear component, even nuclear component itself, is more and more supported by computer technology. This increasing utilization of the computer and software has led to the faster development of nuclear technology on one hand and also brought new problems on the other hand. Especially, the combination of hardware, software and humans has increased nuclear component system complexities to an unprecedented level. To solve this problem, Life Cycle Management technology is adopted in nuclear component system. Hence, an intensive discussion on the development process of a nuclear component is proposed. According to the characteristics of the nuclear component development, such as the complexities and strict safety requirements of the nuclear components, long-term design period, changeable design specifications and requirements, high capital investment, and satisfaction for engineering codes/standards, the development life-cycle model of nuclear component is presented. The development life-cycle model is classified at three levels, namely, component level development life-cycle, sub-component development life-cycle and component level verification/certification life-cycle. The purposes and outcomes of development processes are stated in detailed. A process framework for nuclear component based on system engineering and development environment of nuclear component is discussed for future research work. (authors)

GTX Reference Vehicle Structural Verification Methods and Weight Summary

Science.gov (United States)

Hunter, J. E.; McCurdy, D. R.; Dunn, P. W.

2002-01-01

The design of a single-stage-to-orbit air breathing propulsion system requires the simultaneous development of a reference launch vehicle in order to achieve the optimal mission performance. Accordingly, for the GTX study a 300-lb payload reference vehicle was preliminarily sized to a gross liftoff weight (GLOW) of 238,000 lb. A finite element model of the integrated vehicle/propulsion system was subjected to the trajectory environment and subsequently optimized for structural efficiency. This study involved the development of aerodynamic loads mapped to finite element models of the integrated system in order to assess vehicle margins of safety. Commercially available analysis codes were used in the process along with some internally developed spreadsheets and FORTRAN codes specific to the GTX geometry for mapping of thermal and pressure loads. A mass fraction of 0.20 for the integrated system dry weight has been the driver for a vehicle design consisting of state-of-the-art composite materials in order to meet the rigid weight requirements. This paper summarizes the methodology used for preliminary analyses and presents the current status of the weight optimization for the structural components of the integrated system.

Combined Effects of Prenatal Exposures to Environmental Chemicals on Birth Weight

Directory of Open Access Journals (Sweden)

Eva Govarts

2016-05-01

Full Text Available Prenatal chemical exposure has been frequently associated with reduced fetal growth by single pollutant regression models although inconsistent results have been obtained. Our study estimated the effects of exposure to single pollutants and mixtures on birth weight in 248 mother-child pairs. Arsenic, copper, lead, manganese and thallium were measured in cord blood, cadmium in maternal blood, methylmercury in maternal hair, and five organochlorines, two perfluorinated compounds and diethylhexyl phthalate metabolites in cord plasma. Daily exposure to particulate matter was modeled and averaged over the duration of gestation. In single pollutant models, arsenic was significantly associated with reduced birth weight. The effect estimate increased when including cadmium, and mono-(2-ethyl-5-carboxypentyl phthalate (MECPP co-exposure. Combining exposures by principal component analysis generated an exposure factor loaded by cadmium and arsenic that was associated with reduced birth weight. MECPP induced gender specific effects. In girls, the effect estimate was doubled with co-exposure of thallium, PFOS, lead, cadmium, manganese, and mercury, while in boys, the mixture of MECPP with cadmium showed the strongest association with birth weight. In conclusion, birth weight was consistently inversely associated with exposure to pollutant mixtures. Chemicals not showing significant associations at single pollutant level contributed to stronger effects when analyzed as mixtures.

Combined Effects of Prenatal Exposures to Environmental Chemicals on Birth Weight

Science.gov (United States)

Govarts, Eva; Remy, Sylvie; Bruckers, Liesbeth; Den Hond, Elly; Sioen, Isabelle; Nelen, Vera; Baeyens, Willy; Nawrot, Tim S; Loots, Ilse; Van Larebeke, Nick; Schoeters, Greet

2016-01-01

Prenatal chemical exposure has been frequently associated with reduced fetal growth by single pollutant regression models although inconsistent results have been obtained. Our study estimated the effects of exposure to single pollutants and mixtures on birth weight in 248 mother-child pairs. Arsenic, copper, lead, manganese and thallium were measured in cord blood, cadmium in maternal blood, methylmercury in maternal hair, and five organochlorines, two perfluorinated compounds and diethylhexyl phthalate metabolites in cord plasma. Daily exposure to particulate matter was modeled and averaged over the duration of gestation. In single pollutant models, arsenic was significantly associated with reduced birth weight. The effect estimate increased when including cadmium, and mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP) co-exposure. Combining exposures by principal component analysis generated an exposure factor loaded by cadmium and arsenic that was associated with reduced birth weight. MECPP induced gender specific effects. In girls, the effect estimate was doubled with co-exposure of thallium, PFOS, lead, cadmium, manganese, and mercury, while in boys, the mixture of MECPP with cadmium showed the strongest association with birth weight. In conclusion, birth weight was consistently inversely associated with exposure to pollutant mixtures. Chemicals not showing significant associations at single pollutant level contributed to stronger effects when analyzed as mixtures. PMID:27187434

Electrophoretic analysis of different human growth hormone preparations:characterization and molecular weight estimation of isohormones and other proteic components

International Nuclear Information System (INIS)

Schwarz, I.

1979-01-01

Twelve human growth hormone (hGH) preparations were studied on analytical polyacrilamide gel electrophoresis with the purpose of evaluating degree of homogeneity of the extracts, the geometric mean radius (R) sup(-) and the molecular weight (MW) of the protein hormone. A standard curve was used for ten proteins of known molecular weight, where the square root of the retardation coefficient (K sub(R)) was plotted against R sup(-). Five isohormones were identified and defined as charge isomers, based on their different relative free mobility and on their similar R sup(-)(1.81-1.97 nm) and MW (20300-26000 d) values. The heterogeneity of all preparations was due to the presence in general of three isohormones. In five preparations, isohormones B, C 1 and C 2 , were predominant. In recent hGH (IEA) preparations by the method of ROOS, the isohormones C 2 , D and E were identified while in an older one, isohormones E and E 1 were detected. From two to five minor components were found in all samples. Moreover the same type of analysis was carried out on several fractions from protein peaks II and III eluting from Sephadex G 100 purification of three hGH (IEA) extracts. The isohormones start to appear in peak II and their relative concentration is in agreement with the peak III profile read at 280 nm. Practically all secondary components were present in peak II and in most of peak III, showing a type of heterogeneity due to hGH polymeric forms and a relatively small presence of contaminants. (Author) [pt

The n-component cubic model and flows: subgraph break-collapse method

International Nuclear Information System (INIS)

Essam, J.W.; Magalhaes, A.C.N. de.

1988-01-01

We generalise to the n-component cubic model the subgraph break-collapse method which we previously developed for the Potts model. The relations used are based on expressions which we recently derived for the Z(λ) model in terms of mod-λ flows. Our recursive algorithm is similar, for n = 2, to the break-collapse method for the Z(4) model proposed by Mariz and coworkers. It allows the exact calculation for the partition function and correlation functions for n-component cubic clusters with n as a variable, without the need to examine all of the spin configurations. (author) [pt

Cessation-related weight concern among homeless male and female smokers.

Science.gov (United States)

Pinsker, Erika Ashley; Hennrikus, Deborah Jane; Erickson, Darin J; Call, Kathleen Thiede; Forster, Jean Lois; Okuyemi, Kolawole Stephen

2017-09-01

Concern about post-cessation weight gain is a barrier to making attempts to quit smoking; however, its effect on smoking cessation is unclear. In this study we examine cessation-related weight concern among the homeless, which hasn't been studied. Homeless males (n = 320) and females (n = 110) participating in a smoking cessation RCT in the Twin Cities, Minnesota from 2009 to 2011 completed surveys on cessation-related weight concern, smoking status, and components from the Behavioral Model for Vulnerable Populations. Generalized estimating equations were used to examine baseline predictors of cessation-related weight concern at baseline, the end of treatment, and 26-weeks follow-up. Logistic regression models were used to examine the relationship between cessation-related weight concern and smoking status at the end of treatment and follow-up. Females had higher cessation-related weight concern than males. Among males, older age, Black race, higher BMI, depression, and having health insurance were associated with higher cessation-related weight concern. Among females, nicotine dependence, greater cigarette consumption, indicating quitting is more important, older age of smoking initiation, and less support to quit from family were associated with higher cessation-related weight concern. In multivariate analyses, cessation-related weight concern decreased over time among females. Cessation-related weight concern wasn't associated with smoking cessation. Although several types of characteristics predicted cessation-related weight concern among males, only smoking characteristics predicted cessation-related weight concern among females. Given the small proportion of quitters in this study (8% of males and 5% of females), further research on the impact of cessation-related weight concern on smoking cessation among the homeless is warranted.

A conceptual model of psychosocial risk and protective factors for excessive gestational weight gain.

Science.gov (United States)

Hill, Briony; Skouteris, Helen; McCabe, Marita; Milgrom, Jeannette; Kent, Bridie; Herring, Sharon J; Hartley-Clark, Linda; Gale, Janette

2013-02-01

nearly half of all women exceed the guideline recommended pregnancy weight gain for their Body Mass Index (BMI) category. Excessive gestational weight gain (GWG) is correlated positively with postpartum weight retention and is a predictor of long-term, higher BMI in mothers and their children. Psychosocial factors are generally not targeted in GWG behaviour change interventions, however, multifactorial, conceptual models that include these factors, may be useful in determining the pathways that contribute to excessive GWG. We propose a conceptual model, underpinned by health behaviour change theory, which outlines the psychosocial determinants of GWG, including the role of motivation and self-efficacy towards healthy behaviours. This model is based on a review of the existing literature in this area. there is increasing evidence to show that psychosocial factors, such as increased depressive symptoms, anxiety, lower self-esteem and body image dissatisfaction, are associated with excessive GWG. What is less known is how these factors might lead to excessive GWG. Our conceptual model proposes a pathway of factors that affect GWG, and may be useful for understanding the mechanisms by which interventions impact on weight management during pregnancy. This involves tracking the relationships among maternal psychosocial factors, including body image concerns, motivation to adopt healthy lifestyle behaviours, confidence in adopting healthy lifestyle behaviours for the purposes of weight management, and actual behaviour changes. health-care providers may improve weight gain outcomes in pregnancy if they assess and address psychosocial factors in pregnancy. Copyright © 2011 Elsevier Ltd. All rights reserved.

A Four–Component Model of Age–Related Memory Change

Science.gov (United States)

Healey, M. Karl; Kahana, Michael J.

2015-01-01

We develop a novel, computationally explicit, theory of age–related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that includes aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates four components: 1) the ability to sustain attention across an encoding episode, 2) the ability to retrieve contextual representations for use as retrieval cues, 3) the ability to monitor retrievals and reject intrusions, and 4) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the four–component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus we provide a four–component theory of a complex pattern of age differences across two key laboratory tasks. PMID:26501233

a Quadtree Organization Construction and Scheduling Method for Urban 3d Model Based on Weight

Science.gov (United States)

Yao, C.; Peng, G.; Song, Y.; Duan, M.

2017-09-01

The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

A QUADTREE ORGANIZATION CONSTRUCTION AND SCHEDULING METHOD FOR URBAN 3D MODEL BASED ON WEIGHT

Directory of Open Access Journals (Sweden)

C. Yao

2017-09-01

Full Text Available The increasement of Urban 3D model precision and data quantity puts forward higher requirements for real-time rendering of digital city model. Improving the organization, management and scheduling of 3D model data in 3D digital city can improve the rendering effect and efficiency. This paper takes the complexity of urban models into account, proposes a Quadtree construction and scheduling rendering method for Urban 3D model based on weight. Divide Urban 3D model into different rendering weights according to certain rules, perform Quadtree construction and schedule rendering according to different rendering weights. Also proposed an algorithm for extracting bounding box extraction based on model drawing primitives to generate LOD model automatically. Using the algorithm proposed in this paper, developed a 3D urban planning&management software, the practice has showed the algorithm is efficient and feasible, the render frame rate of big scene and small scene are both stable at around 25 frames.

Softened food reduces weight loss in the streptozotocin-induced male mouse model of diabetic nephropathy

DEFF Research Database (Denmark)

Nørgaard, Sisse A; Sand, Fredrik W; Sørensen, Dorte B

2018-01-01

The streptozotocin (STZ)-induced diabetic mouse is a widely used model of diabetes and diabetic nephropathy (DN). However, it is a well-known issue that this model is challenged by high weight loss, which despite supportive measures often results in high euthanization rates. To overcome...... these issues, we hypothesized that supplementing STZ-induced diabetic mice with water-softened chow in addition to normal chow would reduce weight loss, lower the need for supportive treatment, and reduce the number of mice reaching the humane endpoint of 20% weight loss. In a 15 week STZ-induced DN study we...... demonstrated that diabetic male mice receiving softened chow had reduced acute weight loss following STZ treatment ( p = 0.045) and additionally fewer mice were euthanized due to weight loss. By supplementing the diabetic mice with softened chow, no mice reached 20% weight loss whereas 37.5% of the mice...

Three-Component Forward Modeling for Transient Electromagnetic Method

Directory of Open Access Journals (Sweden)

Bin Xiong

2010-01-01

Full Text Available In general, the time derivative of vertical magnetic field is considered only in the data interpretation of transient electromagnetic (TEM method. However, to survey in the complex geology structures, this conventional technique has begun gradually to be unsatisfied with the demand of field exploration. To improve the integrated interpretation precision of TEM, it is necessary to study the three-component forward modeling and inversion. In this paper, a three-component forward algorithm for 2.5D TEM based on the independent electric and magnetic field has been developed. The main advantage of the new scheme is that it can reduce the size of the global system matrix to the utmost extent, that is to say, the present is only one fourth of the conventional algorithm. In order to illustrate the feasibility and usefulness of the present algorithm, several typical geoelectric models of the TEM responses produced by loop sources at air-earth interface are presented. The results of the numerical experiments show that the computation speed of the present scheme is increased obviously and three-component interpretation can get the most out of the collected data, from which we can easily analyze or interpret the space characteristic of the abnormity object more comprehensively.

Statistical models for prediction of dry weight and nitrogen accumulation based on visible and near-infrared hyper-spectral reflectance of rice canopies

International Nuclear Information System (INIS)

Takahashi, W.; Nguyen-Cong, V.; Kawaguchi, S.; Minamiyama, M.; Ninomiya, S.

2000-01-01

Various multivariate regression models were examined with ten-fold cross-validation to develop efficient, accurate models to predict dry weight and nitrogen accumulation of rice crops (cultivars Koshihikari, Hanaechizen, Nipponbare, and IR-36) from the maximum tiller number stage to the meiosis stage, using plant-canopy reflectance of hyper-spectra within the 400-1100 nm domain without any variable selection. The results showed that the principal component regression using hyper-spectra gave better fits and predictability than that using specific wavelengths. On the other hand, partial least squares regression was the most useful among the models tested; this method avoided overfitting and multicollinearity by using all wavelength information without variable selection and by inclusion of both x and y variations in its latent variables. (author)

Half-unit weighted bilinear algorithm for image contrast enhancement in capsule endoscopy

Science.gov (United States)

Rukundo, Olivier

2018-04-01

This paper proposes a novel enhancement method based exclusively on the bilinear interpolation algorithm for capsule endoscopy images. The proposed method does not convert the original RBG image components to HSV or any other color space or model; instead, it processes directly RGB components. In each component, a group of four adjacent pixels and half-unit weight in the bilinear weighting function are used to calculate the average pixel value, identical for each pixel in that particular group. After calculations, groups of identical pixels are overlapped successively in horizontal and vertical directions to achieve a preliminary-enhanced image. The final-enhanced image is achieved by halving the sum of the original and preliminary-enhanced image pixels. Quantitative and qualitative experiments were conducted focusing on pairwise comparisons between original and enhanced images. Final-enhanced images have generally the best diagnostic quality and gave more details about the visibility of vessels and structures in capsule endoscopy images.

Parameter estimation and statistical test of geographically weighted bivariate Poisson inverse Gaussian regression models

Science.gov (United States)

Amalia, Junita; Purhadi, Otok, Bambang Widjanarko

2017-11-01

Poisson distribution is a discrete distribution with count data as the random variables and it has one parameter defines both mean and variance. Poisson regression assumes mean and variance should be same (equidispersion). Nonetheless, some case of the count data unsatisfied this assumption because variance exceeds mean (over-dispersion). The ignorance of over-dispersion causes underestimates in standard error. Furthermore, it causes incorrect decision in the statistical test. Previously, paired count data has a correlation and it has bivariate Poisson distribution. If there is over-dispersion, modeling paired count data is not sufficient with simple bivariate Poisson regression. Bivariate Poisson Inverse Gaussian Regression (BPIGR) model is mix Poisson regression for modeling paired count data within over-dispersion. BPIGR model produces a global model for all locations. In another hand, each location has different geographic conditions, social, cultural and economic so that Geographically Weighted Regression (GWR) is needed. The weighting function of each location in GWR generates a different local model. Geographically Weighted Bivariate Poisson Inverse Gaussian Regression (GWBPIGR) model is used to solve over-dispersion and to generate local models. Parameter estimation of GWBPIGR model obtained by Maximum Likelihood Estimation (MLE) method. Meanwhile, hypothesis testing of GWBPIGR model acquired by Maximum Likelihood Ratio Test (MLRT) method.

Virtual enterprise model for the electronic components business in the Nuclear Weapons Complex

Energy Technology Data Exchange (ETDEWEB)

Ferguson, T.J.; Long, K.S.; Sayre, J.A. [Sandia National Labs., Albuquerque, NM (United States); Hull, A.L. [Sandia National Labs., Livermore, CA (United States); Carey, D.A.; Sim, J.R.; Smith, M.G. [Allied-Signal Aerospace Co., Kansas City, MO (United States). Kansas City Div.

1994-08-01

The electronic components business within the Nuclear Weapons Complex spans organizational and Department of Energy contractor boundaries. An assessment of the current processes indicates a need for fundamentally changing the way electronic components are developed, procured, and manufactured. A model is provided based on a virtual enterprise that recognizes distinctive competencies within the Nuclear Weapons Complex and at the vendors. The model incorporates changes that reduce component delivery cycle time and improve cost effectiveness while delivering components of the appropriate quality.

SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

International Nuclear Information System (INIS)

Boutilier, J; Chan, T; Lee, T; Craig, T; Sharpe, M

2014-01-01

Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time

SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT

Energy Technology Data Exchange (ETDEWEB)

Boutilier, J; Chan, T; Lee, T [University of Toronto, Toronto, Ontario (Canada); Craig, T; Sharpe, M [University of Toronto, Toronto, Ontario (Canada); The Princess Margaret Cancer Centre - UHN, Toronto, ON (Canada)

2014-06-15

Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.

Modeling the evaporation of sessile multi-component droplets

NARCIS (Netherlands)

Diddens, C.; Kuerten, Johannes G.M.; van der Geld, C.W.M.; Wijshoff, H.M.A.

2017-01-01

We extended a mathematical model for the drying of sessile droplets, based on the lubrication approximation, to binary mixture droplets. This extension is relevant for e.g. inkjet printing applications, where ink consisting of several components are used. The extension involves the generalization of

Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)

Science.gov (United States)

Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul

2018-05-01

The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.

The Impact of Weights on the Quality of Agricultural Producers' Multicriteria Decision Models

Directory of Open Access Journals (Sweden)

Agata Sielska

2015-01-01

Full Text Available Decisions regarding agricultural production involve multiple goals. A multicriteria approach allows decision makers to consider more aspects of the decision scenario, although it also leads to other problems, such as difficulties with the selection of goals or criteria, as well as assigning them appropriate weights. It is argued that not only do goals vary depending on the decision-makers' socioeconomic features, but their relative importance changes as well. A simulation study has been conducted based on the Farm Accountancy Data Network (FADN database. We use the distance-to-the-negative-solution maximization model. Seven sets of criteria and different sets of weights are considered. The main purpose of the study is to determine the impact of weights on the quality of the model. Quality is assessed by comparing the optimal and observed values of the decision variables. The results lead to the conclusion that the differences between the quality of various models are small. (original abstract

Blood profile of proteins and steroid hormones predicts weight change after weight loss with interactions of dietary protein level and glycemic index.

Directory of Open Access Journals (Sweden)

Ping Wang

2011-02-01

Full Text Available Weight regain after weight loss is common. In the Diogenes dietary intervention study, high protein and low glycemic index (GI diet improved weight maintenance.To identify blood predictors for weight change after weight loss following the dietary intervention within the Diogenes study.Blood samples were collected at baseline and after 8-week low caloric diet-induced weight loss from 48 women who continued to lose weight and 48 women who regained weight during subsequent 6-month dietary intervention period with 4 diets varying in protein and GI levels. Thirty-one proteins and 3 steroid hormones were measured.Angiotensin I converting enzyme (ACE was the most important predictor. Its greater reduction during the 8-week weight loss was related to continued weight loss during the subsequent 6 months, identified by both Logistic Regression and Random Forests analyses. The prediction power of ACE was influenced by immunoproteins, particularly fibrinogen. Leptin, luteinizing hormone and some immunoproteins showed interactions with dietary protein level, while interleukin 8 showed interaction with GI level on the prediction of weight maintenance. A predictor panel of 15 variables enabled an optimal classification by Random Forests with an error rate of 24±1%. A logistic regression model with independent variables from 9 blood analytes had a prediction accuracy of 92%.A selected panel of blood proteins/steroids can predict the weight change after weight loss. ACE may play an important role in weight maintenance. The interactions of blood factors with dietary components are important for personalized dietary advice after weight loss.ClinicalTrials.gov NCT00390637.

Modelling Creativity: Identifying Key Components through a Corpus-Based Approach.

Science.gov (United States)

Jordanous, Anna; Keller, Bill

2016-01-01

Creativity is a complex, multi-faceted concept encompassing a variety of related aspects, abilities, properties and behaviours. If we wish to study creativity scientifically, then a tractable and well-articulated model of creativity is required. Such a model would be of great value to researchers investigating the nature of creativity and in particular, those concerned with the evaluation of creative practice. This paper describes a unique approach to developing a suitable model of how creative behaviour emerges that is based on the words people use to describe the concept. Using techniques from the field of statistical natural language processing, we identify a collection of fourteen key components of creativity through an analysis of a corpus of academic papers on the topic. Words are identified which appear significantly often in connection with discussions of the concept. Using a measure of lexical similarity to help cluster these words, a number of distinct themes emerge, which collectively contribute to a comprehensive and multi-perspective model of creativity. The components provide an ontology of creativity: a set of building blocks which can be used to model creative practice in a variety of domains. The components have been employed in two case studies to evaluate the creativity of computational systems and have proven useful in articulating achievements of this work and directions for further research.

Least-squares variance component estimation

NARCIS (Netherlands)

Teunissen, P.J.G.; Amiri-Simkooei, A.R.

2007-01-01

Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a user-defined weight

Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan; Krebs-Smith, Susan M.; Midthune, Douglas; Perez, Adriana; Buckman, Dennis W.; Kipnis, Victor; Freedman, Laurence S.; Dodd, Kevin W.; Carroll, Raymond J

2011-01-01

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

Fitting a Bivariate Measurement Error Model for Episodically Consumed Dietary Components

KAUST Repository

Zhang, Saijuan

2011-01-06

There has been great public health interest in estimating usual, i.e., long-term average, intake of episodically consumed dietary components that are not consumed daily by everyone, e.g., fish, red meat and whole grains. Short-term measurements of episodically consumed dietary components have zero-inflated skewed distributions. So-called two-part models have been developed for such data in order to correct for measurement error due to within-person variation and to estimate the distribution of usual intake of the dietary component in the univariate case. However, there is arguably much greater public health interest in the usual intake of an episodically consumed dietary component adjusted for energy (caloric) intake, e.g., ounces of whole grains per 1000 kilo-calories, which reflects usual dietary composition and adjusts for different total amounts of caloric intake. Because of this public health interest, it is important to have models to fit such data, and it is important that the model-fitting methods can be applied to all episodically consumed dietary components.We have recently developed a nonlinear mixed effects model (Kipnis, et al., 2010), and have fit it by maximum likelihood using nonlinear mixed effects programs and methodology (the SAS NLMIXED procedure). Maximum likelihood fitting of such a nonlinear mixed model is generally slow because of 3-dimensional adaptive Gaussian quadrature, and there are times when the programs either fail to converge or converge to models with a singular covariance matrix. For these reasons, we develop a Monte-Carlo (MCMC) computation of fitting this model, which allows for both frequentist and Bayesian inference. There are technical challenges to developing this solution because one of the covariance matrices in the model is patterned. Our main application is to the National Institutes of Health (NIH)-AARP Diet and Health Study, where we illustrate our methods for modeling the energy-adjusted usual intake of fish and whole

A four-component model of age-related memory change.

Science.gov (United States)

Healey, M Karl; Kahana, Michael J

2016-01-01

We develop a novel, computationally explicit, theory of age-related memory change within the framework of the context maintenance and retrieval (CMR2) model of memory search. We introduce a set of benchmark findings from the free recall and recognition tasks that include aspects of memory performance that show both age-related stability and decline. We test aging theories by lesioning the corresponding mechanisms in a model fit to younger adult free recall data. When effects are considered in isolation, many theories provide an adequate account, but when all effects are considered simultaneously, the existing theories fail. We develop a novel theory by fitting the full model (i.e., allowing all parameters to vary) to individual participants and comparing the distributions of parameter values for older and younger adults. This theory implicates 4 components: (a) the ability to sustain attention across an encoding episode, (b) the ability to retrieve contextual representations for use as retrieval cues, (c) the ability to monitor retrievals and reject intrusions, and (d) the level of noise in retrieval competitions. We extend CMR2 to simulate a recognition memory task using the same mechanisms the free recall model uses to reject intrusions. Without fitting any additional parameters, the 4-component theory that accounts for age differences in free recall predicts the magnitude of age differences in recognition memory accuracy. Confirming a prediction of the model, free recall intrusion rates correlate positively with recognition false alarm rates. Thus, we provide a 4-component theory of a complex pattern of age differences across 2 key laboratory tasks. (c) 2015 APA, all rights reserved).

Using the weighted keyword model to improve information retrieval for answering biomedical questions.

Science.gov (United States)

Yu, Hong; Cao, Yong-Gang

2009-03-01

Physicians ask many complex questions during the patient encounter. Information retrieval systems that can provide immediate and relevant answers to these questions can be invaluable aids to the practice of evidence-based medicine. In this study, we first automatically identify topic keywords from ad hoc clinical questions with a Condition Random Field model that is trained over thousands of manually annotated clinical questions. We then report on a linear model that assigns query weights based on their automatically identified semantic roles: topic keywords, domain specific terms, and their synonyms. Our evaluation shows that this weighted keyword model improves information retrieval from the Text Retrieval Conference Genomics track data.

Hybrid time/frequency domain modeling of nonlinear components

DEFF Research Database (Denmark)

Wiechowski, Wojciech Tomasz; Lykkegaard, Jan; Bak, Claus Leth

2007-01-01

This paper presents a novel, three-phase hybrid time/frequency methodology for modelling of nonlinear components. The algorithm has been implemented in the DIgSILENT PowerFactory software using the DIgSILENT Programming Language (DPL), as a part of the work described in [1]. Modified HVDC benchmark...

Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights

NARCIS (Netherlands)

L.F. Hoogerheide (Lennart); R.H. Kleijn (Richard); H.K. van Dijk (Herman); M.J.C.M. Verbeek (Marno)

2009-01-01

textabstractSeveral Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time

Modeling and solving semiring constraint satisfaction problems by transformation to weighted semiring Max-SAT

CSIR Research Space (South Africa)

Leenen, L

2007-12-01

Full Text Available The authors present a variant of the Weighted Maximum Satisfiability Problem (Weighted Max-SAT), which is a modeling of the Semiring Constraint Satisfaction framework. They show how to encode a Semiring Constraint Satisfaction Problem (SCSP...

A new cellular automata model of traffic flow with negative exponential weighted look-ahead potential

Science.gov (United States)

Ma, Xiao; Zheng, Wei-Fan; Jiang, Bao-Shan; Zhang, Ji-Ye

2016-10-01

With the development of traffic systems, some issues such as traffic jams become more and more serious. Efficient traffic flow theory is needed to guide the overall controlling, organizing and management of traffic systems. On the basis of the cellular automata model and the traffic flow model with look-ahead potential, a new cellular automata traffic flow model with negative exponential weighted look-ahead potential is presented in this paper. By introducing the negative exponential weighting coefficient into the look-ahead potential and endowing the potential of vehicles closer to the driver with a greater coefficient, the modeling process is more suitable for the driver’s random decision-making process which is based on the traffic environment that the driver is facing. The fundamental diagrams for different weighting parameters are obtained by using numerical simulations which show that the negative exponential weighting coefficient has an obvious effect on high density traffic flux. The complex high density non-linear traffic behavior is also reproduced by numerical simulations. Project supported by the National Natural Science Foundation of China (Grant Nos. 11572264, 11172247, 11402214, and 61373009).

Layout Optimization Model for the Production Planning of Precast Concrete Building Components

Directory of Open Access Journals (Sweden)

Dong Wang

2018-05-01

Full Text Available Precast concrete comprises the basic components of modular buildings. The efficiency of precast concrete building component production directly impacts the construction time and cost. In the processes of precast component production, mold setting has a significant influence on the production efficiency and cost, as well as reducing the resource consumption. However, the development of mold setting plans is left to the experience of production staff, with outcomes dependent on the quality of human skill and experience available. This can result in sub-optimal production efficiencies and resource wastage. Accordingly, in order to improve the efficiency of precast component production, this paper proposes an optimization model able to maximize the average utilization rate of pallets used during the molding process. The constraints considered were the order demand, the size of the pallet, layout methods, and the positional relationship of components. A heuristic algorithm was used to identify optimization solutions provided by the model. Through empirical analysis, and as exemplified in the case study, this research is significant in offering a prefabrication production planning model which improves pallet utilization rates, shortens component production time, reduces production costs, and improves the resource utilization. The results clearly demonstrate that the proposed method can facilitate the precast production plan providing strong practical implications for production planners.

Characterizing long-term patterns of weight change in China using latent class trajectory modeling.

Directory of Open Access Journals (Sweden)

Lauren Paynter

Full Text Available Over the past three decades, obesity-related diseases have increased tremendously in China, and are now the leading causes of morbidity and mortality. Patterns of weight change can be used to predict risk of obesity-related diseases, increase understanding of etiology of disease risk, identify groups at particularly high risk, and shape prevention strategies.Latent class trajectory modeling was used to compute weight change trajectories for adults aged 18 to 66 using the China Health and Nutrition Survey (CHNS data (n = 12,611. Weight change trajectories were computed separately for males and females by age group at baseline due to differential age-related patterns of weight gain in China with urbanization. Generalized linear mixed effects models examined the association between weight change trajectories and baseline characteristics including urbanicity, BMI category, age, and year of study entry.Trajectory classes were identified for each of six age-sex subgroups corresponding to various degrees of weight loss, maintenance and weight gain. Baseline BMI status was a significant predictor of trajectory membership for all age-sex subgroups. Baseline overweight/obesity increased odds of following 'initial loss with maintenance' trajectories. We found no significant association between baseline urbanization and trajectory membership after controlling for other covariates.Trajectory analysis identified patterns of weight change for age by gender groups. Lack of association between baseline urbanization status and trajectory membership suggests that living in a rural environment at baseline was not protective. Analyses identified age-specific nuances in weight change patterns, pointing to the importance of subgroup analyses in future research.

Link prediction in weighted networks

DEFF Research Database (Denmark)

Wind, David Kofoed; Mørup, Morten

2012-01-01

Many complex networks feature relations with weight information. Some models utilize this information while other ignore the weight information when inferring the structure. In this paper we investigate if edge-weights when modeling real networks, carry important information about the network...... is to infer presence of edges, but that simpler models are better at inferring the actual weights....

A global weighted mean temperature model based on empirical orthogonal function analysis

Science.gov (United States)

Li, Qinzheng; Chen, Peng; Sun, Langlang; Ma, Xiaping

2018-03-01

A global empirical orthogonal function (EOF) model of the tropospheric weighted mean temperature called GEOFM_Tm was developed using high-precision Global Geodetic Observing System (GGOS) Atmosphere Tm data during the years 2008-2014. Due to the quick convergence of EOF decomposition, it is possible to use the first four EOF series, which consists base functions Uk and associated coefficients Pk, to represent 99.99% of the overall variance of the original data sets and its spatial-temporal variations. Results show that U1 displays a prominent latitude distribution profile with positive peaks located at low latitude region. U2 manifests an asymmetric pattern that positive values occurred over 30° in the Northern Hemisphere, and negative values were observed at other regions. U3 and U4 displayed significant anomalies in Tibet and North America, respectively. Annual variation is the major component of the first and second associated coefficients P1 and P2, whereas P3 and P4 mainly reflects both annual and semi-annual variation components. Furthermore, the performance of constructed GEOFM_Tm was validated by comparison with GTm_III and GTm_N with different kinds of data including GGOS Atmosphere Tm data in 2015 and radiosonde data from Integrated Global Radiosonde Archive (IGRA) in 2014. Generally speaking, GEOFM_Tm can achieve the same accuracy and reliability as GTm_III and GTm_N models in a global scale, even has improved in the Antarctic and Greenland regions. The MAE and RMS of GEOFM_Tm tend to be 2.49 K and 3.14 K with respect to GGOS Tm data, respectively; and 3.38 K and 4.23 K with respect to IGRA sounding data, respectively. In addition, those three models have higher precision at low latitude than middle and high latitude regions. The magnitude of Tm remains at the range of 220-300 K, presented a high correlation with geographic latitude. In the Northern Hemisphere, there was a significant enhancement at high latitude region reaching 270 K during summer

Cognitive and weight-related correlates of flexible and rigid restrained eating behaviour

DEFF Research Database (Denmark)

Westenhoefer, Joachim; Engel, Daniel; Holst, Claus

2013-01-01

Examine the association between components of restrained eating, cognitive performance and weight loss maintenance.......Examine the association between components of restrained eating, cognitive performance and weight loss maintenance....

Validation of anthropometry and foot-to-foot bioelectrical resistance against a three-component model to assess total body fat in children: the IDEFICS study.

Science.gov (United States)

Bammann, K; Huybrechts, I; Vicente-Rodriguez, G; Easton, C; De Vriendt, T; Marild, S; Mesana, M I; Peeters, M W; Reilly, J J; Sioen, I; Tubic, B; Wawro, N; Wells, J C; Westerterp, K; Pitsiladis, Y; Moreno, L A

2013-04-01

To compare different field methods for estimating body fat mass with a reference value derived by a three-component (3C) model in pre-school and school children across Europe. Multicentre validation study. Seventy-eight preschool/school children aged 4-10 years from four different European countries. A standard measurement protocol was carried out in all children by trained field workers. A 3C model was used as the reference method. The field methods included height and weight measurement, circumferences measured at four sites, skinfold measured at two-six sites and foot-to-foot bioelectrical resistance (BIA) via TANITA scales. With the exception of height and neck circumference, all single measurements were able to explain at least 74% of the fat-mass variance in the sample. In combination, circumference models were superior to skinfold models and height-weight models. The best predictions were given by trunk models (combining skinfold and circumference measurements) that explained 91% of the observed fat-mass variance. The optimal data-driven model for our sample includes hip circumference, triceps skinfold and total body mass minus resistance index, and explains 94% of the fat-mass variance with 2.44 kg fat mass limits of agreement. In all investigated models, prediction errors were associated with fat mass, although to a lesser degree in the investigated skinfold models, arm models and the data-driven models. When studying total body fat in childhood populations, anthropometric measurements will give biased estimations as compared to gold standard measurements. Nevertheless, our study shows that when combining circumference and skinfold measurements, estimations of fat mass can be obtained with a limit of agreement of 1.91 kg in normal weight children and of 2.94 kg in overweight or obese children.

Incremental principal component pursuit for video background modeling

Science.gov (United States)

Rodriquez-Valderrama, Paul A.; Wohlberg, Brendt

2017-03-14

An incremental Principal Component Pursuit (PCP) algorithm for video background modeling that is able to process one frame at a time while adapting to changes in background, with a computational complexity that allows for real-time processing, having a low memory footprint and is robust to translational and rotational jitter.

Two-component mixture cure rate model with spline estimated nonparametric components.

Science.gov (United States)

Wang, Lu; Du, Pang; Liang, Hua

2012-09-01

In some survival analysis of medical studies, there are often long-term survivors who can be considered as permanently cured. The goals in these studies are to estimate the noncured probability of the whole population and the hazard rate of the susceptible subpopulation. When covariates are present as often happens in practice, to understand covariate effects on the noncured probability and hazard rate is of equal importance. The existing methods are limited to parametric and semiparametric models. We propose a two-component mixture cure rate model with nonparametric forms for both the cure probability and the hazard rate function. Identifiability of the model is guaranteed by an additive assumption that allows no time-covariate interactions in the logarithm of hazard rate. Estimation is carried out by an expectation-maximization algorithm on maximizing a penalized likelihood. For inferential purpose, we apply the Louis formula to obtain point-wise confidence intervals for noncured probability and hazard rate. Asymptotic convergence rates of our function estimates are established. We then evaluate the proposed method by extensive simulations. We analyze the survival data from a melanoma study and find interesting patterns for this study. © 2011, The International Biometric Society.

A mesoscopic reaction rate model for shock initiation of multi-component PBX explosives.

Science.gov (United States)

Liu, Y R; Duan, Z P; Zhang, Z Y; Ou, Z C; Huang, F L

2016-11-05

The primary goal of this research is to develop a three-term mesoscopic reaction rate model that consists of a hot-spot ignition, a low-pressure slow burning and a high-pressure fast reaction terms for shock initiation of multi-component Plastic Bonded Explosives (PBX). Thereinto, based on the DZK hot-spot model for a single-component PBX explosive, the hot-spot ignition term as well as its reaction rate is obtained through a "mixing rule" of the explosive components; new expressions for both the low-pressure slow burning term and the high-pressure fast reaction term are also obtained by establishing the relationships between the reaction rate of the multi-component PBX explosive and that of its explosive components, based on the low-pressure slow burning term and the high-pressure fast reaction term of a mesoscopic reaction rate model. Furthermore, for verification, the new reaction rate model is incorporated into the DYNA2D code to simulate numerically the shock initiation process of the PBXC03 and the PBXC10 multi-component PBX explosives, and the numerical results of the pressure histories at different Lagrange locations in explosive are found to be in good agreements with previous experimental data. Copyright © 2016 Elsevier B.V. All rights reserved.

The Association of Unintentional Changes in Weight, Body Composition, and Homeostasis Model Assessment Index with Glycemic Progression in Non-Diabetic Healthy Subjects

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Eun-Jung Rhee

2011-04-01

Full Text Available BackgroundWe performed a retrospective longitudinal study on the effects of changes in weight, body composition, and homeostasis model assessment (HOMA indices on glycemic progression in subjects without diabetes during a four-year follow-up period in a community cohort without intentional intervention.MethodsFrom 28,440 non-diabetic subjects who participated in a medical check-up program in 2004, data on anthropometric and metabolic parameters were obtained after four years in 2008. Body composition analyses were performed with a bioelectrical impedance analyzer. Skeletal muscle index (SMI, % was calculated with lean mass/weight×100. Subjects were divided into three groups according to weight change status in four years: weight loss (≤-5.0%, stable weight (-5.0 to 5.0%, weight gain (≥5.0%. Progressors were defined as the subjects who progressed to impaired fasting glucose or diabetes.ResultsProgressors showed worse baseline metabolic profiles compared with non-progressors. In logistic regression analyses, the increase in changes of HOMA-insulin resistance (HOMA-IR in four years presented higher odds ratios for glycemic progression compared with other changes during that period. Among the components of body composition, a change in waist-hip ratio was the strongest predictor, and SMI change in four years was a significant negative predictor for glycemic progression. Changes in HOMA β-cell function in four years was a negative predictor for glycemic progression.ConclusionIncreased interval changes in HOMA-IR, weight gain and waist-hip ratio was associated with glycemic progression during a four-year period without intentional intervention in non-diabetic Korean subjects.

A new model for reliability optimization of series-parallel systems with non-homogeneous components

International Nuclear Information System (INIS)

Feizabadi, Mohammad; Jahromi, Abdolhamid Eshraghniaye

2017-01-01

In discussions related to reliability optimization using redundancy allocation, one of the structures that has attracted the attention of many researchers, is series-parallel structure. In models previously presented for reliability optimization of series-parallel systems, there is a restricting assumption based on which all components of a subsystem must be homogeneous. This constraint limits system designers in selecting components and prevents achieving higher levels of reliability. In this paper, a new model is proposed for reliability optimization of series-parallel systems, which makes possible the use of non-homogeneous components in each subsystem. As a result of this flexibility, the process of supplying system components will be easier. To solve the proposed model, since the redundancy allocation problem (RAP) belongs to the NP-hard class of optimization problems, a genetic algorithm (GA) is developed. The computational results of the designed GA are indicative of high performance of the proposed model in increasing system reliability and decreasing costs. - Highlights: • In this paper, a new model is proposed for reliability optimization of series-parallel systems. • In the previous models, there is a restricting assumption based on which all components of a subsystem must be homogeneous. • The presented model provides a possibility for the subsystems’ components to be non- homogeneous in the required conditions. • The computational results demonstrate the high performance of the proposed model in improving reliability and reducing costs.

Comprehensive maternal characteristics associated with birth weight: Bayesian modeling in a prospective cohort study from Iran

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Marjan Mansourian

2017-01-01

Full Text Available Background: In this study, we aimed to determine comprehensive maternal characteristics associated with birth weight using Bayesian modeling. Materials and Methods: A total of 526 participants were included in this prospective study. Nutritional status, supplement consumption during the pregnancy, demographic and socioeconomic characteristics, anthropometric measures, physical activity, and pregnancy outcomes were considered as effective variables on the birth weight. Bayesian approach of complex statistical models using Markov chain Monte Carlo approach was used for modeling the data considering the real distribution of the response variable. Results: There was strong positive correlation between infant birth weight and the maternal intake of Vitamin C, folic acid, Vitamin B3, Vitamin A, selenium, calcium, iron, phosphorus, potassium, magnesium as micronutrients, and fiber and protein as macronutrients based on the 95% high posterior density regions for parameters in the Bayesian model. None of the maternal characteristics had statistical association with birth weight. Conclusion: Higher maternal macro- and micro-nutrient intake during pregnancy was associated with a lower risk of delivering low birth weight infants. These findings support recommendations to expand intake of nutrients during pregnancy to high level.

A "small-changes" workplace weight loss and maintenance program: examination of weight and health outcomes.

Science.gov (United States)

Zinn, Caryn; Schofield, Grant M; Hopkins, Will G

2012-10-01

To compare the effect of "small-changes" and "usual care" workplace interventions on weight loss and to investigate the effect of small changes with or without maintenance on weight and health outcomes. Overweight/obese employees at two New Zealand worksites received a 12-month usual-care intervention (n = 53), followed by a 12-month small-changes intervention (n = 102). Small changes comprised a 12-week component, followed by 9 months of maintenance, implemented at only one worksite. Magnitudes of effects were assessed via a threshold of -5% (weight loss) and standardization (health outcomes). Small changes showed beneficial weight loss relative to usual care in both worksites. For small-changes interventions, worksites reduced weight (12 weeks) and maintained lost weight (12 months). One in every three participants lost 5% or more weight. Some improvements in health outcomes were shown. Regardless of maintenance, the small-changes intervention was successful in sustaining weight loss.

Focused information criterion and model averaging based on weighted composite quantile regression

KAUST Repository

Xu, Ganggang

2013-08-13

We study the focused information criterion and frequentist model averaging and their application to post-model-selection inference for weighted composite quantile regression (WCQR) in the context of the additive partial linear models. With the non-parametric functions approximated by polynomial splines, we show that, under certain conditions, the asymptotic distribution of the frequentist model averaging WCQR-estimator of a focused parameter is a non-linear mixture of normal distributions. This asymptotic distribution is used to construct confidence intervals that achieve the nominal coverage probability. With properly chosen weights, the focused information criterion based WCQR estimators are not only robust to outliers and non-normal residuals but also can achieve efficiency close to the maximum likelihood estimator, without assuming the true error distribution. Simulation studies and a real data analysis are used to illustrate the effectiveness of the proposed procedure. © 2013 Board of the Foundation of the Scandinavian Journal of Statistics..

A mouse model of weight-drop closed head injury: emphasis on cognitive and neurological deficiency

Directory of Open Access Journals (Sweden)

Igor Khalin

2016-01-01

Full Text Available Traumatic brain injury (TBI is a leading cause of death and disability in individuals worldwide. Producing a clinically relevant TBI model in small-sized animals remains fairly challenging. For good screening of potential therapeutics, which are effective in the treatment of TBI, animal models of TBI should be established and standardized. In this study, we established mouse models of closed head injury using the Shohami weight-drop method with some modifications concerning cognitive deficiency assessment and provided a detailed description of the severe TBI animal model. We found that 250 g falling weight from 2 cm height produced severe closed head injury in C57BL/6 male mice. Cognitive disorders in mice with severe closed head injury could be detected using passive avoidance test on day 7 after injury. Findings from this study indicate that weight-drop injury animal models are suitable for further screening of brain neuroprotectants and potentially are similar to those seen in human TBI.

Weight Gain, Schizophrenia and Antipsychotics: New Findings from Animal Model and Pharmacogenomic Studies

Directory of Open Access Journals (Sweden)

Fabio Panariello

2011-01-01

Full Text Available Excess body weight is one of the most common physical health problems among patients with schizophrenia that increases the risk for many medical problems, including type 2 diabetes mellitus, coronary heart disease, osteoarthritis, and hypertension, and accounts in part for 20% shorter life expectancy than in general population. Among patients with severe mental illness, obesity can be attributed to an unhealthy lifestyle, personal genetic profile, as well as the effects of psychotropic medications, above all antipsychotic drugs. Novel “atypical” antipsychotic drugs represent a substantial improvement on older “typical” drugs. However, clinical experience has shown that some, but not all, of these drugs can induce substantial weight gain. Animal models of antipsychotic-related weight gain and animal transgenic models of knockout or overexpressed genes of antipsychotic receptors have been largely evaluated by scientific community for changes in obesity-related gene expression or phenotypes. Moreover, pharmacogenomic approaches have allowed to detect more than 300 possible candidate genes for antipsychotics-induced body weight gain. In this paper, we summarize current thinking on: (1 the role of polymorphisms in several candidate genes, (2 the possible roles of various neurotransmitters and neuropeptides in this adverse drug reaction, and (3 the state of development of animal models in this matter. We also outline major areas for future research.

Use of weighted characteristic analysis as a tool in resource assessment

International Nuclear Information System (INIS)

Sinding-Larsen, R.

1979-01-01

The paper describes a method which permits the integration of information from multiple domains in the assessment of resources. Maps displaying different attributes from multiple domains (e.g. geology, geophysics, geochemistry, remote sensing) are evaluated individually and partitioned in terms of the objective into favourable regions (aggregate of areal units) which are coded '1'; the remaining regions of uncertain significance are coded '0'. For some variables (e.g. geochemical and remote sensing) the spatial concept of 'anomalous' region, defined as any area 'higher' than its surrounding areas, can be used to delineate favourable regions. Binary surfaces generated for each of the geochemical, geological and geophysical variables available within a province of interest are evaluated within a model area and relative weights are calculated for each variable. The computed weights assign levels of importance to the component variables or characteristics of the model. Binary maps for the different domains are then combined into one map which expresses the degree of association between a given areal unit and the model, taking into account the relative weights or importance of the respective variables which characterize the model. An example of the use of weighted characteristic analysis with geological, geophysical and remote sensing variables showed the ability of the method to delineate areas with known mineralization when it was tested in a well-explored area in Norway. (author)

A model-based software development methodology for high-end automotive components

NARCIS (Netherlands)

Ravanan, Mahmoud

2014-01-01

This report provides a model-based software development methodology for high-end automotive components. The V-model is used as a process model throughout the development of the software platform. It offers a framework that simplifies the relation between requirements, design, implementation,

Energy Deficit Required for Rapid Weight Loss in Elite Collegiate Wrestlers.

Science.gov (United States)

Kondo, Emi; Sagayama, Hiroyuki; Yamada, Yosuke; Shiose, Keisuke; Osawa, Takuya; Motonaga, Keiko; Ouchi, Shiori; Kamei, Akiko; Nakajima, Kohei; Higaki, Yasuki; Tanaka, Hiroaki; Takahashi, Hideyuki; Okamura, Koji

2018-04-26

To determine energy density for rapid weight loss (RWL) of weight-classified sports, eight male elite wrestlers were instructed to lose 6% of body mass (BM) within 53 h. Energy deficit during the RWL was calculated by subtracting total energy expenditure (TEE) determined using the doubly labeled water method (DLW) from energy intake (EI) assessed with diet records. It was also estimated from body composition change estimated with the four-component model (4C) and other conventional methods. BM decreased significantly by 4.7 ± 0.5 kg (6.4 ± 0.5%). Total body water loss was the major component of the BM loss (71.0 ± 7.6%). TEE was 9446 ± 1422 kcal, and EI was 2366 ± 1184 kcal during the RWL of 53-h; therefore, the energy deficit was 7080 ± 1525 kcal. Thus, energy density was 1507 ± 279 kcal/kg ∆BM during the RWL, comparable with values obtained using the 4C, three-component model, dual energy X-ray absorptiometry, and stable isotope dilution. Energy density for RWL of wrestlers is lower than that commonly used (7400 or 7700 kcal/kg ΔBM). Although RWL is not recommended, we propose that commonly practiced extreme energy restriction such as 7400 or 7700 kcal/kg ΔBM during RWL appears to be meaningless.

Energy Deficit Required for Rapid Weight Loss in Elite Collegiate Wrestlers

Directory of Open Access Journals (Sweden)

Emi Kondo

2018-04-01

Full Text Available To determine energy density for rapid weight loss (RWL of weight-classified sports, eight male elite wrestlers were instructed to lose 6% of body mass (BM within 53 h. Energy deficit during the RWL was calculated by subtracting total energy expenditure (TEE determined using the doubly labeled water method (DLW from energy intake (EI assessed with diet records. It was also estimated from body composition change estimated with the four-component model (4C and other conventional methods. BM decreased significantly by 4.7 ± 0.5 kg (6.4 ± 0.5%. Total body water loss was the major component of the BM loss (71.0 ± 7.6%. TEE was 9446 ± 1422 kcal, and EI was 2366 ± 1184 kcal during the RWL of 53-h; therefore, the energy deficit was 7080 ± 1525 kcal. Thus, energy density was 1507 ± 279 kcal/kg ∆BM during the RWL, comparable with values obtained using the 4C, three-component model, dual energy X-ray absorptiometry, and stable isotope dilution. Energy density for RWL of wrestlers is lower than that commonly used (7400 or 7700 kcal/kg ΔBM. Although RWL is not recommended, we propose that commonly practiced extreme energy restriction such as 7400 or 7700 kcal/kg ΔBM during RWL appears to be meaningless.

Application of fuzzy-MOORA method: Ranking of components for reliability estimation of component-based software systems

Directory of Open Access Journals (Sweden)

Zeeshan Ali Siddiqui

2016-01-01

Full Text Available Component-based software system (CBSS development technique is an emerging discipline that promises to take software development into a new era. As hardware systems are presently being constructed from kits of parts, software systems may also be assembled from components. It is more reliable to reuse software than to create. It is the glue code and individual components reliability that contribute to the reliability of the overall system. Every component contributes to overall system reliability according to the number of times it is being used, some components are of critical usage, known as usage frequency of component. The usage frequency decides the weight of each component. According to their weights, each component contributes to the overall reliability of the system. Therefore, ranking of components may be obtained by analyzing their reliability impacts on overall application. In this paper, we propose the application of fuzzy multi-objective optimization on the basis of ratio analysis, Fuzzy-MOORA. The method helps us find the best suitable alternative, software component, from a set of available feasible alternatives named software components. It is an accurate and easy to understand tool for solving multi-criteria decision making problems that have imprecise and vague evaluation data. By the use of ratio analysis, the proposed method determines the most suitable alternative among all possible alternatives, and dimensionless measurement will realize the job of ranking of components for estimating CBSS reliability in a non-subjective way. Finally, three case studies are shown to illustrate the use of the proposed technique.

Development of commercial hybrid electric vehicle with native key components

Directory of Open Access Journals (Sweden)

S. V. Bakhmutov

2014-01-01

Full Text Available The perspectives of development of medium weight cargo vehicles with hybrid powertrain including Russian native key components are considered in this article. Series-parallel scheme of HEV is more relevant owing to limitations of series and parallel schemes. An example of this technology is described. This technical solution has good facilities for variation of HEV and AWD type. The authors have patented it. In addition, another main issue is to choose the types of key components with good correlation for parameters of ICE, electric motors, batteries, and inverter. Using mathematical model of the vehicle a selection and correlation of technical characteristics were carried out to meet ecological and economical requirements. After computing calculation two control strategies were accepted. The first strategy contributes to good fuel consumption, while the other one is aimed at ecology. Researchers use test benches to confirm the results of calculation, and this one was built by the authors applying native components. The result of experiment on the test bench is the growth of fuel consumption of the medium weight cargo vehicle by 25% and compliance with ecological class Euro-4.

Computational needs for modelling accelerator components

International Nuclear Information System (INIS)

Hanerfeld, H.

1985-06-01

The particle-in-cell MASK is being used to model several different electron accelerator components. These studies are being used both to design new devices and to understand particle behavior within existing structures. Studies include the injector for the Stanford Linear Collider and the 50 megawatt klystron currently being built at SLAC. MASK is a 2D electromagnetic code which is being used by SLAC both on our own IBM 3081 and on the CRAY X-MP at the NMFECC. Our experience with running MASK illustrates the need for supercomputers to continue work of the kind described. 3 refs., 2 figs

Softened food reduces weight loss in the streptozotocin-induced male mouse model of diabetic nephropathy.

Science.gov (United States)

Nørgaard, Sisse A; Sand, Fredrik W; Sørensen, Dorte B; Abelson, Klas Sp; Søndergaard, Henrik

2018-01-01

The streptozotocin (STZ)-induced diabetic mouse is a widely used model of diabetes and diabetic nephropathy (DN). However, it is a well-known issue that this model is challenged by high weight loss, which despite supportive measures often results in high euthanization rates. To overcome these issues, we hypothesized that supplementing STZ-induced diabetic mice with water-softened chow in addition to normal chow would reduce weight loss, lower the need for supportive treatment, and reduce the number of mice reaching the humane endpoint of 20% weight loss. In a 15 week STZ-induced DN study we demonstrated that diabetic male mice receiving softened chow had reduced acute weight loss following STZ treatment ( p = 0.045) and additionally fewer mice were euthanized due to weight loss. By supplementing the diabetic mice with softened chow, no mice reached 20% weight loss whereas 37.5% of the mice without this supplement reached this humane endpoint ( p = 0.0027). Excretion of corticosterone metabolites in faeces was reduced in diabetic mice on softened chow ( p = 0.0007), suggesting lower levels of general stress. Finally, it was demonstrated that the water-softened chow supplement did not significantly affect the induction of key disease parameters, i.e. %HbA1C and albuminuria nor result in abnormal teeth wear. In conclusion, supplementation of softened food is refining the STZ-induced diabetic mouse model significantly by reducing stress, weight loss and the number of animals sacrificed due to humane endpoints, while maintaining the key phenotypes of diabetes and nephropathy.

Model ZD-I paper base weight measuring and controlling system

International Nuclear Information System (INIS)

Li Nianzu; Song Debin; Wu Guoliang; Hou Yaoxin; Li Dazhen

1988-01-01

Model ZD-I Base Weight Measuring and Controlling System has been developed for the automation process in paper-making industry. A single-board microprocessor is installed in the system. The mass thickness can be controlled within 1 g/m 2 if the changing range of concentration and water content is less than 10%

Traceable components of terrestrial carbon storage capacity in biogeochemical models.

Science.gov (United States)

Xia, Jianyang; Luo, Yiqi; Wang, Ying-Ping; Hararuk, Oleksandra

2013-07-01

Biogeochemical models have been developed to account for more and more processes, making their complex structures difficult to be understood and evaluated. Here, we introduce a framework to decompose a complex land model into traceable components based on mutually independent properties of modeled biogeochemical processes. The framework traces modeled ecosystem carbon storage capacity (Xss ) to (i) a product of net primary productivity (NPP) and ecosystem residence time (τE ). The latter τE can be further traced to (ii) baseline carbon residence times (τ'E ), which are usually preset in a model according to vegetation characteristics and soil types, (iii) environmental scalars (ξ), including temperature and water scalars, and (iv) environmental forcings. We applied the framework to the Australian Community Atmosphere Biosphere Land Exchange (CABLE) model to help understand differences in modeled carbon processes among biomes and as influenced by nitrogen processes. With the climate forcings of 1990, modeled evergreen broadleaf forest had the highest NPP among the nine biomes and moderate residence times, leading to a relatively high carbon storage capacity (31.5 kg cm(-2) ). Deciduous needle leaf forest had the longest residence time (163.3 years) and low NPP, leading to moderate carbon storage (18.3 kg cm(-2) ). The longest τE in deciduous needle leaf forest was ascribed to its longest τ'E (43.6 years) and small ξ (0.14 on litter/soil carbon decay rates). Incorporation of nitrogen processes into the CABLE model decreased Xss in all biomes via reduced NPP (e.g., -12.1% in shrub land) or decreased τE or both. The decreases in τE resulted from nitrogen-induced changes in τ'E (e.g., -26.7% in C3 grassland) through carbon allocation among plant pools and transfers from plant to litter and soil pools. Our framework can be used to facilitate data model comparisons and model intercomparisons via tracking a few traceable components for all terrestrial carbon

Machine learning of frustrated classical spin models. I. Principal component analysis

Science.gov (United States)

Wang, Ce; Zhai, Hui

2017-10-01

This work aims at determining whether artificial intelligence can recognize a phase transition without prior human knowledge. If this were successful, it could be applied to, for instance, analyzing data from the quantum simulation of unsolved physical models. Toward this goal, we first need to apply the machine learning algorithm to well-understood models and see whether the outputs are consistent with our prior knowledge, which serves as the benchmark for this approach. In this work, we feed the computer data generated by the classical Monte Carlo simulation for the X Y model in frustrated triangular and union jack lattices, which has two order parameters and exhibits two phase transitions. We show that the outputs of the principal component analysis agree very well with our understanding of different orders in different phases, and the temperature dependences of the major components detect the nature and the locations of the phase transitions. Our work offers promise for using machine learning techniques to study sophisticated statistical models, and our results can be further improved by using principal component analysis with kernel tricks and the neural network method.

Volume-weighted particle-tracking method for solute-transport modeling; Implementation in MODFLOW–GWT

Science.gov (United States)

Winston, Richard B.; Konikow, Leonard F.; Hornberger, George Z.

2018-02-16

In the traditional method of characteristics for groundwater solute-transport models, advective transport is represented by moving particles that track concentration. This approach can lead to global mass-balance problems because in models of aquifers having complex boundary conditions and heterogeneous properties, particles can originate in cells having different pore volumes and (or) be introduced (or removed) at cells representing fluid sources (or sinks) of varying strengths. Use of volume-weighted particles means that each particle tracks solute mass. In source or sink cells, the changes in particle weights will match the volume of water added or removed through external fluxes. This enables the new method to conserve mass in source or sink cells as well as globally. This approach also leads to potential efficiencies by allowing the number of particles per cell to vary spatially—using more particles where concentration gradients are high and fewer where gradients are low. The approach also eliminates the need for the model user to have to distinguish between “weak” and “strong” fluid source (or sink) cells. The new model determines whether solute mass added by fluid sources in a cell should be represented by (1) new particles having weights representing appropriate fractions of the volume of water added by the source, or (2) distributing the solute mass added over all particles already in the source cell. The first option is more appropriate for the condition of a strong source; the latter option is more appropriate for a weak source. At sinks, decisions whether or not to remove a particle are replaced by a reduction in particle weight in proportion to the volume of water removed. A number of test cases demonstrate that the new method works well and conserves mass. The method is incorporated into a new version of the U.S. Geological Survey’s MODFLOW–GWT solute-transport model.

On the Likely Utility of Hybrid Weights Optimized for Variances in Hybrid Error Covariance Models

Science.gov (United States)

Satterfield, E.; Hodyss, D.; Kuhl, D.; Bishop, C. H.

2017-12-01

Because of imperfections in ensemble data assimilation schemes, one cannot assume that the ensemble covariance is equal to the true error covariance of a forecast. Previous work demonstrated how information about the distribution of true error variances given an ensemble sample variance can be revealed from an archive of (observation-minus-forecast, ensemble-variance) data pairs. Here, we derive a simple and intuitively compelling formula to obtain the mean of this distribution of true error variances given an ensemble sample variance from (observation-minus-forecast, ensemble-variance) data pairs produced by a single run of a data assimilation system. This formula takes the form of a Hybrid weighted average of the climatological forecast error variance and the ensemble sample variance. Here, we test the extent to which these readily obtainable weights can be used to rapidly optimize the covariance weights used in Hybrid data assimilation systems that employ weighted averages of static covariance models and flow-dependent ensemble based covariance models. Univariate data assimilation and multi-variate cycling ensemble data assimilation are considered. In both cases, it is found that our computationally efficient formula gives Hybrid weights that closely approximate the optimal weights found through the simple but computationally expensive process of testing every plausible combination of weights.

Component- and system-level degradation modeling of digital Instrumentation and Control systems based on a Multi-State Physics Modeling Approach

International Nuclear Information System (INIS)

Wang, Wei; Di Maio, Francesco; Zio, Enrico

2016-01-01

Highlights: • A Multi-State Physics Modeling (MSPM) framework for reliability assessment is proposed. • Monte Carlo (MC) simulation is utilized to estimate the degradation state probability. • Due account is given to stochastic uncertainty and deterministic degradation progression. • The MSPM framework is applied to the reliability assessment of a digital I&C system. • Results are compared with the results obtained with a Markov Chain Model (MCM). - Abstract: A system-level degradation modeling is proposed for the reliability assessment of digital Instrumentation and Control (I&C) systems in Nuclear Power Plants (NPPs). At the component level, we focus on the reliability assessment of a Resistance Temperature Detector (RTD), which is an important digital I&C component used to guarantee the safe operation of NPPs. A Multi-State Physics Model (MSPM) is built to describe this component degradation progression towards failure and Monte Carlo (MC) simulation is used to estimate the probability of sojourn in any of the previously defined degradation states, by accounting for both stochastic and deterministic processes that affect the degradation progression. The MC simulation relies on an integrated modeling of stochastic processes with deterministic aging of components that results to be fundamental for estimating the joint cumulative probability distribution of finding the component in any of the possible degradation states. The results of the application of the proposed degradation model to a digital I&C system of literature are compared with the results obtained by a Markov Chain Model (MCM). The integrated stochastic-deterministic process here proposed to drive the MC simulation is viable to integrate component-level models into a system-level model that would consider inter-system or/and inter-component dependencies and uncertainties.

Reliability Assessment of IGBT Modules Modeled as Systems with Correlated Components

DEFF Research Database (Denmark)

Kostandyan, Erik; Sørensen, John Dalsgaard

2013-01-01

configuration. The estimated system reliability by the proposed method is a conservative estimate. Application of the suggested method could be extended for reliability estimation of systems composing of welding joints, bolts, bearings, etc. The reliability model incorporates the correlation between...... was applied for the systems failure functions estimation. It is desired to compare the results with the true system failure function, which is possible to estimate using simulation techniques. Theoretical model development should be applied for the further research. One of the directions for it might...... be modeling the system based on the Sequential Order Statistics, by considering the failure of the minimum (weakest component) at each loading level. The proposed idea to represent the system by the independent components could also be used for modeling reliability by Sequential Order Statistics....

Connection between weighted LPC and higher-order statistics for AR model estimation

NARCIS (Netherlands)

Kamp, Y.; Ma, C.

1993-01-01

This paper establishes the relationship between a weighted linear prediction method used for robust analysis of voiced speech and the autoregressive modelling based on higher-order statistics, known as cumulants

Exposure–response model for sibutramine and placebo: suggestion for application to long-term weight-control drug development

Directory of Open Access Journals (Sweden)

Han S

2015-09-01

Full Text Available Seunghoon Han,1,2 Sangil Jeon,1,2 Taegon Hong,1,2 Jongtae Lee,1,2 Soo Hyeon Bae,1,2 Wan-su Park,1,2 Gab-jin Park,1,2 Sunil Youn,1,2 Doo Yeon Jang,1,2 Kyung-Soo Kim,3 Dong-Seok Yim1,2 1Department of Pharmacology, College of Medicine, The Catholic University of Korea, 2Pharmacometrics Institute for Practical Education and Training, 3Department of Family Medicine, Seoul St Mary’s Hospital, Seochogu, Seoul, Republic of KoreaAbstract: No wholly successful weight-control drugs have been developed to date, despite the tremendous demand. We present an exposure–response model of sibutramine mesylate that can be applied during clinical development of other weight-control drugs. Additionally, we provide a model-based evaluation of sibutramine efficacy. Data from a double-blind, randomized, placebo-controlled, multicenter study were used (N=120. Subjects in the treatment arm were initially given 8.37 mg sibutramine base daily, and those who lost <2 kg after 4 weeks’ treatment were escalated to 12.55 mg. The duration of treatment was 24 weeks. Drug concentration and body weight were measured predose and at 4 weeks, 8 weeks, and 24 weeks after treatment initiation. Exposure and response to sibutramine, including the placebo effect, were modeled using NONMEM 7.2. An asymptotic model approaching the final body weight was chosen to describe the time course of weight loss. Extent of weight loss was described successfully using a sigmoidal exposure–response relationship of the drug with a constant placebo effect in each individual. The placebo effect was influenced by subjects’ sex and baseline body mass index. Maximal weight loss was predicted to occur around 1 year after treatment initiation. The difference in mean weight loss between the sibutramine (daily 12.55 mg and placebo groups was predicted to be 4.5% in a simulation of 1 year of treatment, with considerable overlap of prediction intervals. Our exposure–response model, which

New component-based normalization method to correct PET system models

International Nuclear Information System (INIS)

Kinouchi, Shoko; Miyoshi, Yuji; Suga, Mikio; Yamaya, Taiga; Yoshida, Eiji; Nishikido, Fumihiko; Tashima, Hideaki

2011-01-01

Normalization correction is necessary to obtain high-quality reconstructed images in positron emission tomography (PET). There are two basic types of normalization methods: the direct method and component-based methods. The former method suffers from the problem that a huge count number in the blank scan data is required. Therefore, the latter methods have been proposed to obtain high statistical accuracy normalization coefficients with a small count number in the blank scan data. In iterative image reconstruction methods, on the other hand, the quality of the obtained reconstructed images depends on the system modeling accuracy. Therefore, the normalization weighing approach, in which normalization coefficients are directly applied to the system matrix instead of a sinogram, has been proposed. In this paper, we propose a new component-based normalization method to correct system model accuracy. In the proposed method, two components are defined and are calculated iteratively in such a way as to minimize errors of system modeling. To compare the proposed method and the direct method, we applied both methods to our small OpenPET prototype system. We achieved acceptable statistical accuracy of normalization coefficients while reducing the count number of the blank scan data to one-fortieth that required in the direct method. (author)

Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

Science.gov (United States)

Chaubert-Pereira, Florence; Guédon, Yann; Lavergne, Christian; Trottier, Catherine

2010-09-01

Tree growth is assumed to be mainly the result of three components: (i) an endogenous component assumed to be structured as a succession of roughly stationary phases separated by marked change points that are asynchronous among individuals, (ii) a time-varying environmental component assumed to take the form of synchronous fluctuations among individuals, and (iii) an individual component corresponding mainly to the local environment of each tree. To identify and characterize these three components, we propose to use semi-Markov switching linear mixed models, i.e., models that combine linear mixed models in a semi-Markovian manner. The underlying semi-Markov chain represents the succession of growth phases and their lengths (endogenous component) whereas the linear mixed models attached to each state of the underlying semi-Markov chain represent-in the corresponding growth phase-both the influence of time-varying climatic covariates (environmental component) as fixed effects, and interindividual heterogeneity (individual component) as random effects. In this article, we address the estimation of Markov and semi-Markov switching linear mixed models in a general framework. We propose a Monte Carlo expectation-maximization like algorithm whose iterations decompose into three steps: (i) sampling of state sequences given random effects, (ii) prediction of random effects given state sequences, and (iii) maximization. The proposed statistical modeling approach is illustrated by the analysis of successive annual shoots along Corsican pine trunks influenced by climatic covariates. © 2009, The International Biometric Society.

Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

KAUST Repository

Martinez, Josue G.

2010-06-01

The authors consider the analysis of hierarchical longitudinal functional data based upon a functional principal components approach. In contrast to standard frequentist approaches to selecting the number of principal components, the authors do model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order to overcome this, the authors show how to apply Stochastic Approximation Monte Carlo (SAMC) to this problem, a method that has the potential to explore the entire space and does not become trapped in local extrema. The combination of reversible jump methods and SAMC in hierarchical longitudinal functional data is simplified by a polar coordinate representation of the principal components. The approach is easy to implement and does well in simulated data in determining the distribution of the number of principal components, and in terms of its frequentist estimation properties. Empirical applications are also presented.

Entropy-optimal weight constraint elicitation with additive multi-attribute utility models

NARCIS (Netherlands)

Valkenhoef , van Gert; Tervonen, Tommi

2016-01-01

We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is

Modelling raster-based monthly water balance components for Europe

Energy Technology Data Exchange (ETDEWEB)

Ulmen, C.

2000-11-01

The terrestrial runoff component is a comparatively small but sensitive and thus significant quantity in the global energy and water cycle at the interface between landmass and atmosphere. As opposed to soil moisture and evapotranspiration which critically determine water vapour fluxes and thus water and energy transport, it can be measured as an integrated quantity over a large area, i.e. the river basin. This peculiarity makes terrestrial runoff ideally suited for the calibration, verification and validation of general circulation models (GCMs). Gauging stations are not homogeneously distributed in space. Moreover, time series are not necessarily continuously measured nor do they in general have overlapping time periods. To overcome this problems with regard to regular grid spacing used in GCMs, different methods can be applied to transform irregular data to regular so called gridded runoff fields. The present work aims to directly compute the gridded components of the monthly water balance (including gridded runoff fields) for Europe by application of the well-established raster-based macro-scale water balance model WABIMON used at the Federal Institute of Hydrology, Germany. Model calibration and validation is performed by separated examination of 29 representative European catchments. Results indicate a general applicability of the model delivering reliable overall patterns and integrated quantities on a monthly basis. For time steps less then too weeks further research and structural improvements of the model are suggested. (orig.)

76 FR 13580 - Bus Testing; Calculation of Average Passenger Weight and Test Vehicle Weight

Science.gov (United States)

2011-03-14

... averages (See, Advisory Circular 120-27E, ``Aircraft Weight and Balance Control,'' June 10, 2005) and the...' needs, or they may choose to upgrade individual components, such as chassis, wheels, tires, brakes, or...

Structural assessment of aerospace components using image processing algorithms and Finite Element models

DEFF Research Database (Denmark)

Stamatelos, Dimtrios; Kappatos, Vassilios

2017-01-01

Purpose – This paper presents the development of an advanced structural assessment approach for aerospace components (metallic and composites). This work focuses on developing an automatic image processing methodology based on Non Destructive Testing (NDT) data and numerical models, for predicting...... the residual strength of these components. Design/methodology/approach – An image processing algorithm, based on the threshold method, has been developed to process and quantify the geometric characteristics of damages. Then, a parametric Finite Element (FE) model of the damaged component is developed based...... on the inputs acquired from the image processing algorithm. The analysis of the metallic structures is employing the Extended FE Method (XFEM), while for the composite structures the Cohesive Zone Model (CZM) technique with Progressive Damage Modelling (PDM) is used. Findings – The numerical analyses...

A multi-component and multi-failure mode inspection model based on the delay time concept

International Nuclear Information System (INIS)

Wang Wenbin; Banjevic, Dragan; Pecht, Michael

2010-01-01

The delay time concept and the techniques developed for modelling and optimising plant inspection practices have been reported in many papers and case studies. For a system comprised of many components and subject to many different failure modes, one of the most convenient ways to model the inspection and failure processes is to use a stochastic point process for defect arrivals and a common delay time distribution for the duration between defect the arrival and failure of all defects. This is an approximation, but has been proven to be valid when the number of components is large. However, for a system with just a few key components and subject to few major failure modes, the approximation may be poor. In this paper, a model is developed to address this situation, where each component and failure mode is modelled individually and then pooled together to form the system inspection model. Since inspections are usually scheduled for the whole system rather than individual components, we then formulate the inspection model when the time to the next inspection from the point of a component failure renewal is random. This imposes some complication to the model, and an asymptotic solution was found. Simulation algorithms have also been proposed as a comparison to the analytical results. A numerical example is presented to demonstrate the model.

Evaluation of the RELAP5/MOD3 multidimensional component model

International Nuclear Information System (INIS)

Tomlinson, E.T.; Rens, T.E.; Coffield, R.D.

1994-01-01

Accurate plenum predictions, which are directly related to the mixing models used, are an important plant modeling consideration because of the consequential impact on basic transient performance calculations for the integrated system. The effect of plenum is a time shift between inlet and outlet temperature changes to the particular volume. Perfect mixing, where the total volume interacts instantaneously with the total inlet flow, does not occur because of effects such as inlet/outlet nozzle jetting, flow stratification, nested vortices within the volume and the general three-dimensional velocity distribution of the flow field. The time lag which exists between the inlet and outlet flows impacts the predicted rate of temperature change experienced by various plant system components and this impacts local component analyses which are affected by the rate of temperature change. This study includes a comparison of two-dimensional plenum mixing predictions using CFD-FLOW3D, RELAP5/MOD3 and perfect mixing models. Three different geometries (flat, square and tall) are assessed for scalar transport times using a wide range of inlet velocity and isothermal conditions. In addition, the three geometries were evaluated for low flow conditions with the inlet flow experiencing a large step temperature decrease. A major conclusion from this study is that the RELAP5/MOD3 multidimensional component model appears to be adequately predicting plenum mixing for a wide range of thermal-hydraulic conditions representative of plant transients

Modeling cellular networks in fading environments with dominant specular components

KAUST Repository

AlAmmouri, Ahmad

2016-07-26

Stochastic geometry (SG) has been widely accepted as a fundamental tool for modeling and analyzing cellular networks. However, the fading models used with SG analysis are mainly confined to the simplistic Rayleigh fading, which is extended to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks with generalized two-ray (GTR) fading channel. The GTR fading explicitly accounts for two DSCs in addition to the diffuse components and offers high flexibility to capture diverse fading channels that appear in realistic outdoor/indoor wireless communication scenarios. It also encompasses the famous Rayleigh and Rician fading as special cases. To this end, the prominent effect of DSCs is highlighted in terms of average spectral efficiency. © 2016 IEEE.

Finsler Geometry Modeling of Phase Separation in Multi-Component Membranes

Directory of Open Access Journals (Sweden)

Satoshi Usui

2016-08-01

Full Text Available A Finsler geometric surface model is studied as a coarse-grained model for membranes of three components, such as zwitterionic phospholipid (DOPC, lipid (DPPC and an organic molecule (cholesterol. To understand the phase separation of liquid-ordered (DPPC rich L o and liquid-disordered (DOPC rich L d , we introduce a binary variable σ ( = ± 1 into the triangulated surface model. We numerically determine that two circular and stripe domains appear on the surface. The dependence of the morphological change on the area fraction of L o is consistent with existing experimental results. This provides us with a clear understanding of the origin of the line tension energy, which has been used to understand these morphological changes in three-component membranes. In addition to these two circular and stripe domains, a raft-like domain and budding domain are also observed, and the several corresponding phase diagrams are obtained.

The Component Slope Linear Model for Calculating Intensive Partial Molar Properties: Application to Waste Glasses

International Nuclear Information System (INIS)

Reynolds, Jacob G.

2013-01-01

Partial molar properties are the changes occurring when the fraction of one component is varied while the fractions of all other component mole fractions change proportionally. They have many practical and theoretical applications in chemical thermodynamics. Partial molar properties of chemical mixtures are difficult to measure because the component mole fractions must sum to one, so a change in fraction of one component must be offset with a change in one or more other components. Given that more than one component fraction is changing at a time, it is difficult to assign a change in measured response to a change in a single component. In this study, the Component Slope Linear Model (CSLM), a model previously published in the statistics literature, is shown to have coefficients that correspond to the intensive partial molar properties. If a measured property is plotted against the mole fraction of a component while keeping the proportions of all other components constant, the slope at any given point on a graph of this curve is the partial molar property for that constituent. Actually plotting this graph has been used to determine partial molar properties for many years. The CSLM directly includes this slope in a model that predicts properties as a function of the component mole fractions. This model is demonstrated by applying it to the constant pressure heat capacity data from the NaOH-NaAl(OH 4 H 2 O system, a system that simplifies Hanford nuclear waste. The partial molar properties of H 2 O, NaOH, and NaAl(OH) 4 are determined. The equivalence of the CSLM and the graphical method is verified by comparing results detennined by the two methods. The CSLM model has been previously used to predict the liquidus temperature of spinel crystals precipitated from Hanford waste glass. Those model coefficients are re-interpreted here as the partial molar spinel liquidus temperature of the glass components

Building Component Library: An Online Repository to Facilitate Building Energy Model Creation; Preprint

Energy Technology Data Exchange (ETDEWEB)

Fleming, K.; Long, N.; Swindler, A.

2012-05-01

This paper describes the Building Component Library (BCL), the U.S. Department of Energy's (DOE) online repository of building components that can be directly used to create energy models. This comprehensive, searchable library consists of components and measures as well as the metadata which describes them. The library is also designed to allow contributors to easily add new components, providing a continuously growing, standardized list of components for users to draw upon.

Bayesian model averaging and weighted average least squares : Equivariance, stability, and numerical issues

NARCIS (Netherlands)

De Luca, G.; Magnus, J.R.

2011-01-01

In this article, we describe the estimation of linear regression models with uncertainty about the choice of the explanatory variables. We introduce the Stata commands bma and wals, which implement, respectively, the exact Bayesian model-averaging estimator and the weighted-average least-squares

Association of the components of the metabolic syndrome with non- alcoholic fatty liver disease among normal-weight, overweight and obese children and adolescents

Directory of Open Access Journals (Sweden)

Kelishadi Roya

2009-12-01

Full Text Available Abstract Objectives This study aimed to determine the prevalence of the metabolic syndrome, abnormalities of liver enzymes and sonographic fatty liver, as well as the inter-related associations in normal weight, overweight and obese children and adolescents. Methods This cross-sectional study was conducted among a sample of 1107 students (56.1% girls, aged 6-18 years in Isfahan, Iran. In addition to physical examination, fasting blood glucose, serum lipid profile and liver enzymes were determined. Liver sonography was performed among 931 participants. These variables were compared among participants with different body mass index (BMI categories. Results From lower to higher BMI category, alanine aminotransferase (ALT, total cholesterol, LDL-cholesterol, triglycerides and systolic blood pressure increased, and HDL-cholesterol decreased significantly. Elevated ALT, aspartate aminotransferase (AST and alkaline phosphatase (ALP were documented in respectively 4.1%, 6.6% and 9.8% of normal weight group. The corresponding figure was 9.5%, 9.8% and 9.1% in overweight group, and 16.9%, 14.9% and 10.8% in obese group, respectively. In all BMI categories, ALT increased significantly by increasing the number of the components of the metabolic syndrome. Odds ratio for elevated liver enzymes and sonographic fatty liver increased significantly with higher number of the components of the metabolic syndrome and higher BMI categories before and after adjustment for age. Conclusions Because of the interrelationship of biochemical and sonographic indexes of fatty liver with the components of the metabolic syndrome, and with increase in their number, it is suggested to determine the clinical impact of such association in future longitudinal studies.

Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components

Energy Technology Data Exchange (ETDEWEB)

Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc

2017-06-27

The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.

Optimality criteria for the components of anisotropic constitutive matrix

DEFF Research Database (Denmark)

Pedersen, Pauli; Pedersen, Niels Leergaard

2014-01-01

densities is equal value for the weighted elastic energy densities, as a natural extension of the optimality criterion for a single load case. The second optimality criterion for the components of a constitutive matrix (of unit norm) is proportionality to corresponding weighted strain components...... with the same proportionality factor $widehat lambda $ for all the components, as shortly specified by $C_{i j k l} = widehat lambda sum _{n} eta _{n} (epsilon _{i j})_{n} (epsilon _{k l})_{n}$, in traditional notation (n indicate load case). These simple analytical results should be communicated, in spite...

Model of community emergence in weighted social networks

Science.gov (United States)

Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.

2009-04-01

Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

Science.gov (United States)

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Mathematical Model for Multicomponent Adsorption Equilibria Using Only Pure Component Data

DEFF Research Database (Denmark)

Marcussen, Lis

2000-01-01

A mathematical model for nonideal adsorption equilibria in multicomponent mixtures is developed. It is applied with good results for pure substances and for prediction of strongly nonideal multicomponent equilibria using only pure component data. The model accounts for adsorbent...

A Three-Component Model for Magnetization Transfer. Solution by Projection-Operator Technique, and Application to Cartilage

Science.gov (United States)

Adler, Ronald S.; Swanson, Scott D.; Yeung, Hong N.

1996-01-01

A projection-operator technique is applied to a general three-component model for magnetization transfer, extending our previous two-component model [R. S. Adler and H. N. Yeung,J. Magn. Reson. A104,321 (1993), and H. N. Yeung, R. S. Adler, and S. D. Swanson,J. Magn. Reson. A106,37 (1994)]. The PO technique provides an elegant means of deriving a simple, effective rate equation in which there is natural separation of relaxation and source terms and allows incorporation of Redfield-Provotorov theory without any additional assumptions or restrictive conditions. The PO technique is extended to incorporate more general, multicomponent models. The three-component model is used to fit experimental data from samples of human hyaline cartilage and fibrocartilage. The fits of the three-component model are compared to the fits of the two-component model.

Towards a Complete Model for Software Component Deployment on Heterogeneous Platform

Directory of Open Access Journals (Sweden)

Švogor Ivan

2014-12-01

Full Text Available This report briefly describes an ongoing research related to optimization of allocating software components to heterogeneous computing platform (which includes CPU, GPU and FPGA. Research goal is also presented, along with current hot topics of the research area, related research teams, and finally results and contribution of my research. It involves mathematical modelling which results in goal function, optimization method which finds a suboptimal solution to the goal function and a software modeling tool which enables graphical representation of the problem at hand and help developers determine component placement in the system design phase.

The ORC method. Effective modelling of thermal performance of multilayer building components

Energy Technology Data Exchange (ETDEWEB)

Akander, Jan

2000-02-01

The ORC Method (Optimised RC-networks) provides a means of modelling one- or multidimensional heat transfer in building components, in this context within building simulation environments. The methodology is shown, primarily applied to heat transfer in multilayer building components. For multilayer building components, the analytical thermal performance is known, given layer thickness and material properties. The aim of the ORC Method is to optimise the values of the thermal resistances and heat capacities of an RC-model such as to give model performance a good agreement with the analytical performance, for a wide range of frequencies. The optimisation procedure is made in the frequency domain, where the over-all deviation between model and analytical frequency response, in terms of admittance and dynamic transmittance, is minimised. It is shown that ORC's are effective in terms of accuracy and computational time in comparison to finite difference models when used in building simulations, in this case with IDA/ICE. An ORC configuration of five mass nodes has been found to model building components in Nordic countries well, within the application of thermal comfort and energy requirement simulations. Simple RC-networks, such as the surface heat capacity and the simple R-C-configuration are not appropriate for detailed building simulation. However, these can be used as basis for defining the effective heat capacity of a building component. An approximate method is suggested on how to determine the effective heat capacity without the use of complex numbers. This entity can be calculated on basis of layer thickness and material properties with the help of two time constants. The approximate method can give inaccuracies corresponding to 20%. In-situ measurements have been carried out in an experimental building with the purpose of establishing the effective heat capacity of external building components that are subjected to normal thermal conditions. The auxiliary

A new enhanced index tracking model in portfolio optimization with sum weighted approach

Science.gov (United States)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Effect of psychological distress on weight concern and weight control behaviors.

Science.gov (United States)

Roohafza, Hamidreza; Kabir, Ali; Sadeghi, Masoumeh; Shokouh, Pedram; Aalaei-Andabili, Seyed Hossein; Mehrabi, Yadollah; Sarrafzadegan, Nizal

2014-09-01

Obesity is associated with chronic disorders like coronary artery diseases, metabolic syndrome, cancers, and psychiatric disorders. Stress may contribute to weight gain by disrupting weight concern, and lead to uncontrolled eating behavior. This study aimed to investigate the effects of stress on weight concern and control behaviors in normal weight and obese adults. A total of 9544 subjects were selected by multi-stage random sampling from three provinces in central Iran. Information related to weight concern and control behavior was registered in normal weight and obese participants. Psychological distress was measured by a 12-item General Health Questionnaire (GHQ-12) and subjects were divided into high and low stress groups. Logistic regression was used for analysis. The mean age of participants was 38.7 ± 15.5 years and 50% (4772) of them were males. The adjusted odds ratio (OR) for age, sex and education of high stress to low stress level for weight concern, weight control behavior and acceptable physical activity behavior was more than 1; but the OR was less than 1 for waist circumference, obesity and healthy diet behavior. Among obese participants, higher levels of stress were associated with lower weight concern with OR, 95%CI: 0.821, (0.682 - 0.988), lower acceptable physical activity with OR = 0.833, 95%CI: (0.624 - 0.912), but higher rates of healthy diet behavior with OR = 1.360, 95% CI: (1.040 - 1.780). Individuals with high stress level have lower weight concern and lower physical activity; therefore, they are prone to weight gain and obesity. It could be concluded that stress management should be considered as a crucial component of obesity prevention and control programs.

A componential model of human interaction with graphs: 1. Linear regression modeling

Science.gov (United States)

Gillan, Douglas J.; Lewis, Robert

1994-01-01

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Flexible Multibody Systems Models Using Composite Materials Components

International Nuclear Information System (INIS)

Neto, Maria Augusta; Ambr'osio, Jorge A. C.; Leal, Rog'erio Pereira

2004-01-01

The use of a multibody methodology to describe the large motion of complex systems that experience structural deformations enables to represent the complete system motion, the relative kinematics between the components involved, the deformation of the structural members and the inertia coupling between the large rigid body motion and the system elastodynamics. In this work, the flexible multibody dynamics formulations of complex models are extended to include elastic components made of composite materials, which may be laminated and anisotropic. The deformation of any structural member must be elastic and linear, when described in a coordinate frame fixed to one or more material points of its domain, regardless of the complexity of its geometry. To achieve the proposed flexible multibody formulation, a finite element model for each flexible body is used. For the beam composite material elements, the sections properties are found using an asymptotic procedure that involves a two-dimensional finite element analysis of their cross-section. The equations of motion of the flexible multibody system are solved using an augmented Lagrangian formulation and the accelerations and velocities are integrated in time using a multi-step multi-order integration algorithm based on the Gear method

A Model of Yeast Cell-Cycle Regulation Based on a Standard Component Modeling Strategy for Protein Regulatory Networks.

Directory of Open Access Journals (Sweden)

Teeraphan Laomettachit

Full Text Available To understand the molecular mechanisms that regulate cell cycle progression in eukaryotes, a variety of mathematical modeling approaches have been employed, ranging from Boolean networks and differential equations to stochastic simulations. Each approach has its own characteristic strengths and weaknesses. In this paper, we propose a "standard component" modeling strategy that combines advantageous features of Boolean networks, differential equations and stochastic simulations in a framework that acknowledges the typical sorts of reactions found in protein regulatory networks. Applying this strategy to a comprehensive mechanism of the budding yeast cell cycle, we illustrate the potential value of standard component modeling. The deterministic version of our model reproduces the phenotypic properties of wild-type cells and of 125 mutant strains. The stochastic version of our model reproduces the cell-to-cell variability of wild-type cells and the partial viability of the CLB2-dbΔ clb5Δ mutant strain. Our simulations show that mathematical modeling with "standard components" can capture in quantitative detail many essential properties of cell cycle control in budding yeast.

Modelling temporal variance of component temperatures and directional anisotropy over vegetated canopy

Science.gov (United States)

Bian, Zunjian; du, yongming; li, hua

2016-04-01

Land surface temperature (LST) as a key variable plays an important role on hydrological, meteorology and climatological study. Thermal infrared directional anisotropy is one of essential factors to LST retrieval and application on longwave radiance estimation. Many approaches have been proposed to estimate directional brightness temperatures (DBT) over natural and urban surfaces. While less efforts focus on 3-D scene and the surface component temperatures used in DBT models are quiet difficult to acquire. Therefor a combined 3-D model of TRGM (Thermal-region Radiosity-Graphics combined Model) and energy balance method is proposed in the paper for the attempt of synchronously simulation of component temperatures and DBT in the row planted canopy. The surface thermodynamic equilibrium can be final determined by the iteration strategy of TRGM and energy balance method. The combined model was validated by the top-of-canopy DBTs using airborne observations. The results indicated that the proposed model performs well on the simulation of directional anisotropy, especially the hotspot effect. Though we find that the model overestimate the DBT with Bias of 1.2K, it can be an option as a data reference to study temporal variance of component temperatures and DBTs when field measurement is inaccessible

Preoccupation with shape or weight, fear of weight gain, feeling fat and treatment outcomes in patients with anorexia nervosa: A longitudinal study.

Science.gov (United States)

Calugi, Simona; El Ghoch, Marwan; Conti, Maddalena; Dalle Grave, Riccardo

2018-06-01

The study aimed to evaluate the trajectories of change over time in body-image concern components in patients with anorexia nervosa treated by means of intensive enhanced cognitive behavioural therapy. Moreover, it aimed to study the role of body-image concern components in changes in eating and general psychopathology as well as work and social functioning. Sixty-six adult patients with anorexia nervosa were recruited. Body mass index (BMI); Eating Disorder Examination 'Dietary Restraint' and 'Eating Concern' subscales; Brief Symptom Inventory (BSI); and Work and Social Adjustment Scale (WSAS) scores were recorded at admission, end of treatment, and at 6- and 12-month follow-ups. The trajectories of change of three components of body image concern, namely 'preoccupation with shape or weight', 'fear of weight gain' and 'feeling fat', were assessed. The treatment was associated with a significant improvement in outcome variables and body-image concern components. Baseline 'preoccupation with shape or weight' predicted improvement in Eating Concern, BSI and WSAS scores, while the change in 'fear of weight gain' was associated with improvement in dietary restraint. Baseline and end-of-therapy scores for all three measured body-image concern components predicted achievement of BMI ≥18.5 kg/m 2 at 6- and 12-month follow-ups. These findings highlight the importance of assessing and addressing body-image concern in the management of patients with anorexia nervosa. Copyright © 2018 Elsevier Ltd. All rights reserved.

A two-component dark matter model with real singlet scalars ...

Indian Academy of Sciences (India)

2016-01-05

component dark matter model with real singlet scalars confronting GeV -ray excess from galactic centre and Fermi bubble. Debasish Majumdar Kamakshya Prasad Modak Subhendu Rakshit. Special: Cosmology Volume 86 Issue ...

Hypothalamic deep brain stimulation reduces weight gain in an obesity-animal model.

Directory of Open Access Journals (Sweden)

William P Melega

Full Text Available Prior studies of appetite regulatory networks, primarily in rodents, have established that targeted electrical stimulation of ventromedial hypothalamus (VMH can alter food intake patterns and metabolic homeostasis. Consideration of this method for weight modulation in humans with severe overeating disorders and morbid obesity can be further advanced by modeling procedures and assessing endpoints that can provide preclinical data on efficacy and safety. In this study we adapted human deep brain stimulation (DBS stereotactic methods and instrumentation to demonstrate in a large animal model the modulation of weight gain with VMH-DBS. Female Göttingen minipigs were used because of their dietary habits, physiologic characteristics, and brain structures that resemble those of primates. Further, these animals become obese on extra-feeding regimens. DBS electrodes were first bilaterally implanted into the VMH of the animals (n = 8 which were then maintained on a restricted food regimen for 1 mo following the surgery. The daily amount of food was then doubled for the next 2 mo in all animals to produce obesity associated with extra calorie intake, with half of the animals (n = 4 concurrently receiving continuous low frequency (50 Hz VMH-DBS. Adverse motoric or behavioral effects were not observed subsequent to the surgical procedure or during the DBS period. Throughout this 2 mo DBS period, all animals consumed the doubled amount of daily food. However, the animals that had received VMH-DBS showed a cumulative weight gain (6.1±0.4 kg; mean ± SEM that was lower than the nonstimulated VMH-DBS animals (9.4±1.3 kg; p<0.05, suggestive of a DBS-associated increase in metabolic rate. These results in a porcine obesity model demonstrate the efficacy and behavioral safety of a low frequency VMH-DBS application as a potential clinical strategy for modulation of body weight.

Polycystic ovary syndrome and weight management.

Science.gov (United States)

Moran, Lisa J; Lombard, Catherine B; Lim, Siew; Noakes, Manny; Teede, Helena J

2010-03-01

Polycystic ovary syndrome (PCOS) is a common condition in women of reproductive age, and has reproductive, metabolic and psychological implications. Weight gain and obesity worsen the features of PCOS, while weight loss improves the features of PCOS. While there are potential barriers to successful weight management in young women who do not suffer from PCOS, women with PCOS may experience additional barriers. Weight management strategies in younger women with or without PCOS should encompass both the prevention of excess weight gain and achieving and maintaining a reduced weight through multidisciplinary lifestyle management, comprising dietary, exercise and behavioral therapy, as well as attention to psychosocial stress and practical and physiological barriers to weight management. Further research is warranted in the examination of specific barriers to weight management in women with PCOS, as well as in the determination of optimal components of lifestyle weight management interventions in young women in order to facilitate long-term compliance.

Component and system simulation models for High Flux Isotope Reactor

International Nuclear Information System (INIS)

Sozer, A.

1989-08-01

Component models for the High Flux Isotope Reactor (HFIR) have been developed. The models are HFIR core, heat exchangers, pressurizer pumps, circulation pumps, letdown valves, primary head tank, generic transport delay (pipes), system pressure, loop pressure-flow balance, and decay heat. The models were written in FORTRAN and can be run on different computers, including IBM PCs, as they do not use any specific simulation languages such as ACSL or CSMP. 14 refs., 13 figs

The International Trade Network: weighted network analysis and modelling

International Nuclear Information System (INIS)

Bhattacharya, K; Mukherjee, G; Manna, S S; Saramäki, J; Kaski, K

2008-01-01

Tools of the theory of critical phenomena, namely the scaling analysis and universality, are argued to be applicable to large complex web-like network structures. Using a detailed analysis of the real data of the International Trade Network we argue that the scaled link weight distribution has an approximate log-normal distribution which remains robust over a period of 53 years. Another universal feature is observed in the power-law growth of the trade strength with gross domestic product, the exponent being similar for all countries. Using the 'rich-club' coefficient measure of the weighted networks it has been shown that the size of the rich-club controlling half of the world's trade is actually shrinking. While the gravity law is known to describe well the social interactions in the static networks of population migration, international trade, etc, here for the first time we studied a non-conservative dynamical model based on the gravity law which excellently reproduced many empirical features of the ITN

Weight Loss and the Prevention of Weight Regain: Evaluation of a Treatment Model of Exercise Self-Regulation Generalizing to Controlled Eating.

Science.gov (United States)

Annesi, James J; Johnson, Ping H; Tennant, Gisèle A; Porter, Kandice J; Mcewen, Kristin L

2016-01-01

For decades, behavioral weight-loss treatments have been unsuccessful beyond the short term. Development and testing of innovative, theoretically based methods that depart from current failed practices is a priority for behavioral medicine. To evaluate a new, theory-based protocol in which exercise support methods are employed to facilitate improvements in psychosocial predictors of controlled eating and sustained weight loss. Women with obesity were randomized into either a comparison treatment that incorporated a print manual plus telephone follow-ups (n = 55) or an experimental treatment of The Coach Approach exercise-support protocol followed after 2 months by group nutrition sessions focused on generalizing self-regulatory skills from an exercise support to a controlled eating context (n = 55). Repeated-measures analysis of variance contrasted group changes in weight, physical activity, fruit and vegetable intake, mood, and exercise- and eating-related self-regulation and self-efficacy over 24 months. Regression analyses determined salient interrelations of change scores over both the weight-loss phase (baseline-month 6) and weight-loss maintenance phase (month 6-month 24). Improvements in all psychological measures, physical activity, and fruit and vegetable intake were significantly greater in the experimental group where a mean weight loss of 5.7 kg (6.1% of initial body weight) occurred at month 6, and was largely maintained at a loss of 5.1 kg (5.4%) through the full 24 months of the study. After establishing temporal intervals for changes in self-regulation, self-efficacy, and mood that best predicted improvements in physical activity and eating, a consolidated multiple mediation model suggested that change in self-regulation best predicted weight loss, whereas change in self-efficacy best predicted maintenance of lost weight. Because for most participants loss of weight remained greater than that required for health benefits, and costs for treatment

Three-Component Decomposition Based on Stokes Vector for Compact Polarimetric SAR

Directory of Open Access Journals (Sweden)

Hanning Wang

2015-09-01

Full Text Available In this paper, a three-component decomposition algorithm is proposed for processing compact polarimetric SAR images. By using the correspondence between the covariance matrix and the Stokes vector, three-component scattering models for CTLR and DCP modes are established. The explicit expression of decomposition results is then derived by setting the contribution of volume scattering as a free parameter. The degree of depolarization is taken as the upper bound of the free parameter, for the constraint that the weighting factor of each scattering component should be nonnegative. Several methods are investigated to estimate the free parameter suitable for decomposition. The feasibility of this algorithm is validated by AIRSAR data over San Francisco and RADARSAT-2 data over Flevoland.

Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

Science.gov (United States)

Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

2012-02-08

The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

Genotype x environment interactions for yield components of broomcorn [Sorghum bicolor (L. Moench

Directory of Open Access Journals (Sweden)

Sikora Vladimir

2000-01-01

Full Text Available The aim of this investigation was to study the ecological stability of yield components (weight of undressed and trashed panicle and seed weight per panicle in fourteen varieties of broomcorn. Our current varieties was compared with our old, Hungarian and American varieties. Investigations were carried out under field conditions in a micro trial set up in a randomized block design providing five replications in seven ecologically different years. Stability parameters were computed using the model of Eberhart and Russell (1966. The results of this investigation showed that the genotypes differed in stability parameters for the characters studied. Variety Sava show good stability in all growing conditions. Variety Neoplanta plus was adapted to favorable and variety Reform to unfavorable conditions. Varieties with best performances in regard to yield components did not also show best stability. .

An efficient rhythmic component expression and weighting synthesis strategy for classifying motor imagery EEG in a brain computer interface

Science.gov (United States)

Wang, Tao; He, Bin

2004-03-01

The recognition of mental states during motor imagery tasks is crucial for EEG-based brain computer interface research. We have developed a new algorithm by means of frequency decomposition and weighting synthesis strategy for recognizing imagined right- and left-hand movements. A frequency range from 5 to 25 Hz was divided into 20 band bins for each trial, and the corresponding envelopes of filtered EEG signals for each trial were extracted as a measure of instantaneous power at each frequency band. The dimensionality of the feature space was reduced from 200 (corresponding to 2 s) to 3 by down-sampling of envelopes of the feature signals, and subsequently applying principal component analysis. The linear discriminate analysis algorithm was then used to classify the features, due to its generalization capability. Each frequency band bin was weighted by a function determined according to the classification accuracy during the training process. The present classification algorithm was applied to a dataset of nine human subjects, and achieved a success rate of classification of 90% in training and 77% in testing. The present promising results suggest that the present classification algorithm can be used in initiating a general-purpose mental state recognition based on motor imagery tasks.

Do Knowledge-Component Models Need to Incorporate Representational Competencies?

Science.gov (United States)

Rau, Martina Angela

2017-01-01

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

Multi-Trait analysis of growth traits: fitting reduced rank models using principal components for Simmental beef cattle

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Rodrigo Reis Mota

2016-09-01

Full Text Available ABSTRACT: The aim of this research was to evaluate the dimensional reduction of additive direct genetic covariance matrices in genetic evaluations of growth traits (range 100-730 days in Simmental cattle using principal components, as well as to estimate (covariance components and genetic parameters. Principal component analyses were conducted for five different models-one full and four reduced-rank models. Models were compared using Akaike information (AIC and Bayesian information (BIC criteria. Variance components and genetic parameters were estimated by restricted maximum likelihood (REML. The AIC and BIC values were similar among models. This indicated that parsimonious models could be used in genetic evaluations in Simmental cattle. The first principal component explained more than 96% of total variance in both models. Heritability estimates were higher for advanced ages and varied from 0.05 (100 days to 0.30 (730 days. Genetic correlation estimates were similar in both models regardless of magnitude and number of principal components. The first principal component was sufficient to explain almost all genetic variance. Furthermore, genetic parameter similarities and lower computational requirements allowed for parsimonious models in genetic evaluations of growth traits in Simmental cattle.

Reliability prediction system based on the failure rate model for electronic components

International Nuclear Information System (INIS)

Lee, Seung Woo; Lee, Hwa Ki

2008-01-01

Although many methodologies for predicting the reliability of electronic components have been developed, their reliability might be subjective according to a particular set of circumstances, and therefore it is not easy to quantify their reliability. Among the reliability prediction methods are the statistical analysis based method, the similarity analysis method based on an external failure rate database, and the method based on the physics-of-failure model. In this study, we developed a system by which the reliability of electronic components can be predicted by creating a system for the statistical analysis method of predicting reliability most easily. The failure rate models that were applied are MILHDBK- 217F N2, PRISM, and Telcordia (Bellcore), and these were compared with the general purpose system in order to validate the effectiveness of the developed system. Being able to predict the reliability of electronic components from the stage of design, the system that we have developed is expected to contribute to enhancing the reliability of electronic components

Component-oriented approach to the development and use of numerical models in high energy physics

International Nuclear Information System (INIS)

Amelin, N.S.; Komogorov, M.Eh.

2002-01-01

We discuss the main concepts of a component approach to the development and use of numerical models in high energy physics. This approach is realized as the NiMax software system. The discussed concepts are illustrated by numerous examples of the system user session. In appendix chapter we describe physics and numerical algorithms of the model components to perform simulation of hadronic and nuclear collisions at high energies. These components are members of hadronic application modules that have been developed with the help of the NiMax system. Given report is served as an early release of the NiMax manual mainly for model component users

Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

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Moritz eBoos

2016-05-01

Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Models for describing the thermal characteristics of building components

DEFF Research Database (Denmark)

Jimenez, M.J.; Madsen, Henrik

2008-01-01

, for example. For the analysis of these tests, dynamic analysis models and methods are required. However, a wide variety of models and methods exists, and the problem of choosing the most appropriate approach for each particular case is a non-trivial and interdisciplinary task. Knowledge of a large family....... The characteristics of each type of model are highlighted. Some available software tools for each of the methods described will be mentioned. A case study also demonstrating the difference between linear and nonlinear models is considered....... of these approaches may therefore be very useful for selecting a suitable approach for each particular case. This paper presents an overview of models that can be applied for modelling the thermal characteristics of buildings and building components using data from outdoor testing. The choice of approach depends...

A comparative study of the proposed models for the components of the national health information system.

Science.gov (United States)

Ahmadi, Maryam; Damanabi, Shahla; Sadoughi, Farahnaz

2014-04-01

National Health Information System plays an important role in ensuring timely and reliable access to Health information, which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system - for better planning and management influential factors of performanceseems necessary, therefore, in this study different attitudes towards components of this system are explored comparatively. This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process and output. In this context, search for information using library resources and internet search were conducted, and data analysis was expressed using comparative tables and qualitative data. The findings showed that there are three different perspectives presenting the components of national health information system Lippeveld and Sauerborn and Bodart model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008, and Gattini's 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities and equipment. Plus, in the "process" section from three models, we pointed up the actions ensuring the quality of health information system, and in output section, except for Lippeveld Model, two other models consider information products and use and distribution of information as components of the national health information system. the results showed that all the three models have had a brief discussion about the

Superfluid drag in the two-component Bose-Hubbard model

Science.gov (United States)

Sellin, Karl; Babaev, Egor

2018-03-01

In multicomponent superfluids and superconductors, co- and counterflows of components have, in general, different properties. A. F. Andreev and E. P. Bashkin [Sov. Phys. JETP 42, 164 (1975)] discussed, in the context of He3/He4 superfluid mixtures, that interparticle interactions produce a dissipationless drag. The drag can be understood as a superflow of one component induced by phase gradients of the other component. Importantly, the drag can be both positive (entrainment) and negative (counterflow). The effect is known to have crucial importance for many properties of diverse physical systems ranging from the dynamics of neutron stars and rotational responses of Bose mixtures of ultracold atoms to magnetic responses of multicomponent superconductors. Although substantial literature exists that includes the drag interaction phenomenologically, only a few regimes are covered by quantitative studies of the microscopic origin of the drag and its dependence on microscopic parameters. Here we study the microscopic origin and strength of the drag interaction in a quantum system of two-component bosons on a lattice with short-range interaction. By performing quantum Monte Carlo simulations of a two-component Bose-Hubbard model we obtain dependencies of the drag strength on the boson-boson interactions and properties of the optical lattice. Of particular interest are the strongly correlated regimes where the ratio of coflow and counterflow superfluid stiffnesses can diverge, corresponding to the case of saturated drag.

Weight Loss Self-Efficacy and Modelled Behaviour: Gaining Competence through Example

Science.gov (United States)

Schulz, Benjamin R.; McDonald, Marvin J.

2011-01-01

The Weight Efficacy Life-Style Questionnaire (WEL) and the International Physical Activity Questionnaire (IPAQ) assessed self-efficacy and physical activity for 124 volunteers aged 17-61. It was administered before and after participants attended a video modelling workshop. Half of the participants in the treatment and control groups were given…

Longitudinal functional principal component modelling via Stochastic Approximation Monte Carlo

KAUST Repository

Martinez, Josue G.; Liang, Faming; Zhou, Lan; Carroll, Raymond J.

2010-01-01

model averaging using a Bayesian formulation. A relatively straightforward reversible jump Markov Chain Monte Carlo formulation has poor mixing properties and in simulated data often becomes trapped at the wrong number of principal components. In order

Weight Rhythms: Weight Increases during Weekends and Decreases during Weekdays

Directory of Open Access Journals (Sweden)

Anna-Leena Orsama

2014-01-01

Full Text Available Background/Aims: The week's cycle influences sleep, exercise, and eating habits. An accurate description of weekly weight rhythms has not been reported yet - especially across people who lose weight versus those who maintain or gain weight. Methods: The daily weight in 80 adults (BMI 20.0-33.5 kg/m2; age, 25-62 years was recorded and analysed to determine if a group-level weekly weight fluctuation exists. This was a retrospective study of 4,657 measurements during 15-330 monitoring days. Semi-parametric regression was used to model the rhythm. Results: A pattern of daily weight changes was found (p Conclusion: Weight variations between weekends and weekdays should be considered as normal instead of signs of weight gain. Those who compensate the most are most likely to either lose or maintain weight over time. Long-term habits may make more of a difference than short-term splurges. People prone to weight gain could be counselled about the importance of weekday compensation.

New methods for the characterization of pyrocarbon; The two component model of pyrocarbon

Energy Technology Data Exchange (ETDEWEB)

Luhleich, H.; Sutterlin, L.; Hoven, H.; Nickel, H.

1972-04-19

In the first part, new experiments to clarify the origin of different pyrocarbon components are described. Three new methods (plasma-oxidation, wet-oxidation, ultrasonic method) are presented to expose the carbon black like component in the pyrocarbon deposited in fluidized beds. In the second part, a two component model of pyrocarbon is proposed and illustrated by examples.

Prepregnancy body mass index, gestational weight gain, and birth weight in the BRISA cohort.

Science.gov (United States)

Lima, Raina Jansen Cutrim Propp; Batista, Rosângela Fernandes Lucena; Ribeiro, Marizélia Rodrigues Costa; Ribeiro, Cecília Cláudia Costa; Simões, Vanda Maria Ferreira; Lima Neto, Pedro Martins; Silva, Antônio Augusto Moura da; Bettiol, Heloisa

2018-01-01

OBJECTIVE To analyze the effects of maternal pre-pregnancy body mass index and weight gain during pregnancy on the baby's birth weight. METHODS We conducted a cross-sectional study with 5,024 mothers and their newborns using a Brazilian birth cohort study. In the proposed model, estimated by structural equation modeling, we tested socioeconomic status, age, marital status, pre-pregnancy body mass index, smoking habit and alcohol consumption during pregnancy, hypertension and gestational diabetes, gestational weight gain, and type of delivery as determinants of the baby's birth weight. RESULTS For a gain of 4 kg/m2 (1 Standard Deviation [SD]) in pre-pregnancy body mass index, there was a 0.126 SD increase in birth weight, corresponding to 68 grams (p gestational weight gain represented a 0.280 SD increase in newborn weight, correponding to 151.2 grams (p weight was direct (standardized coefficient [SC] = 0.202; p weight gain during pregnancy (SC = -0.070, p weight gain during pregnany on birth weight was predominantly direct (SC = 0.269, p gained less weight during pregnancy (p gestational weight gain on the increase in birth weight was greater than that of pre-pregnancy body mass index.

A review of typical thermal fatigue failure models for solder joints of electronic components

Science.gov (United States)

Li, Xiaoyan; Sun, Ruifeng; Wang, Yongdong

2017-09-01

For electronic components, cyclic plastic strain makes it easier to accumulate fatigue damage than elastic strain. When the solder joints undertake thermal expansion or cold contraction, different thermal strain of the electronic component and its corresponding substrate is caused by the different coefficient of thermal expansion of the electronic component and its corresponding substrate, leading to the phenomenon of stress concentration. So repeatedly, cracks began to sprout and gradually extend [1]. In this paper, the typical thermal fatigue failure models of solder joints of electronic components are classified and the methods of obtaining the parameters in the model are summarized based on domestic and foreign literature research.

Exploring the Subtleties of Inverse Probability Weighting and Marginal Structural Models.

Science.gov (United States)

Breskin, Alexander; Cole, Stephen R; Westreich, Daniel

2018-05-01

Since being introduced to epidemiology in 2000, marginal structural models have become a commonly used method for causal inference in a wide range of epidemiologic settings. In this brief report, we aim to explore three subtleties of marginal structural models. First, we distinguish marginal structural models from the inverse probability weighting estimator, and we emphasize that marginal structural models are not only for longitudinal exposures. Second, we explore the meaning of the word "marginal" in "marginal structural model." Finally, we show that the specification of a marginal structural model can have important implications for the interpretation of its parameters. Each of these concepts have important implications for the use and understanding of marginal structural models, and thus providing detailed explanations of them may lead to better practices for the field of epidemiology.

Intrinsic light variation in very close eclipsing binary systems with distorted components

International Nuclear Information System (INIS)

Binnendijk, L.

1974-01-01

Using the theory of distorted components in very close binaries, the semiaxes are computed for several possible models. The coefficients of limb darkening and the gravity effect are found as weighted mean values of the results of several theoretical investigations. A simple linear relation is found between the coefficient of limb darkening and the logarithm of the effective temperature in the spectral interval A0 to K0. The Fourier series for the intrinsic light variation of such distorted components is given for any polytropic index. The influence of the tidal bulge is described in detail. (IAA)

Stability equation and two-component Eigenmode for domain walls in scalar potential model

International Nuclear Information System (INIS)

Dias, G.S.; Graca, E.L.; Rodrigues, R. de Lima

2002-08-01

Supersymmetric quantum mechanics involving a two-component representation and two-component eigenfunctions is applied to obtain the stability equation associated to a potential model formulated in terms of two coupled real scalar fields. We investigate the question of stability by introducing an operator technique for the Bogomol'nyi-Prasad-Sommerfield (BPS) and non-BPS states on two domain walls in a scalar potential model with minimal N 1-supersymmetry. (author)

A Co-modeling Method Based on Component Features for Mechatronic Devices in Aero-engines

Science.gov (United States)

Wang, Bin; Zhao, Haocen; Ye, Zhifeng

2017-08-01

Data-fused and user-friendly design of aero-engine accessories is required because of their structural complexity and stringent reliability. This paper gives an overview of a typical aero-engine control system and the development process of key mechatronic devices used. Several essential aspects of modeling and simulation in the process are investigated. Considering the limitations of a single theoretic model, feature-based co-modeling methodology is suggested to satisfy the design requirements and compensate for diversity of component sub-models for these devices. As an example, a stepper motor controlled Fuel Metering Unit (FMU) is modeled in view of the component physical features using two different software tools. An interface is suggested to integrate the single discipline models into the synthesized one. Performance simulation of this device using the co-model and parameter optimization for its key components are discussed. Comparison between delivery testing and the simulation shows that the co-model for the FMU has a high accuracy and the absolute superiority over a single model. Together with its compatible interface with the engine mathematical model, the feature-based co-modeling methodology is proven to be an effective technical measure in the development process of the device.

Optics Elements for Modeling Electrostatic Lenses and Accelerator Components: III. Electrostatic Deflectors

International Nuclear Information System (INIS)

Brown, T.A.; Gillespie, G.H.

1999-01-01

Ion-beam optics models for simulating electrostatic prisms (deflectors) of different geometries have been developed for the computer code TRACE 3-D. TRACE 3-D is an envelope (matrix) code, which includes a linear space charge model, that was originally developed to model bunched beams in magnetic transport systems and radiofrequency (RF) accelerators. Several new optical models for a number of electrostatic lenses and accelerator columns have been developed recently that allow the code to be used for modeling beamlines and accelerators with electrostatic components. The new models include a number of options for: (1) Einzel lenses, (2) accelerator columns, (3) electrostatic prisms, and (4) electrostatic quadrupoles. A prescription for setting up the initial beam appropriate to modeling 2-D (continuous) beams has also been developed. The models for electrostatic prisms are described in this paper. The electrostatic prism model options allow the modeling of cylindrical, spherical, and toroidal electrostatic deflectors. The application of these models in the development of ion-beam transport systems is illustrated through the modeling of a spherical electrostatic analyzer as a component of the new low energy beamline at CAMS

Measurement and modeling of shortwave irradiance components in cloud-free atmospheres

Energy Technology Data Exchange (ETDEWEB)

Halthore, R.N.

1999-08-04

Atmosphere scatters and absorbs incident solar radiation modifying its spectral content and decreasing its intensity at the surface. It is very useful to classify the earth-atmospheric solar radiation into several components--direct solar surface irradiance (E{sub direct}), diffuse-sky downward surface irradiance (E{sub diffuse}), total surface irradiance, and upwelling flux at the surface and at the top-of-the atmosphere. E{sub direct} depends only on the extinction properties of the atmosphere without regard to details of extinction, namely scattering or absorption; furthermore it can be accurately measured to high accuracy (0.3%) with the aid of an active cavity radiometer (ACR). E{sub diffuse} has relatively larger uncertainties both in its measurement using shaded pyranometers and in model estimates, owing to the difficulty in accurately characterizing pyranometers and in measuring model inputs such as surface reflectance, aerosol single scattering albedo, and phase function. Radiative transfer model simulations of the above surface radiation components in cloud-free skies using measured atmospheric properties show that while E{sub direct} estimates are closer to measurements, E{sub diffuse} is overestimated by an amount larger than the combined uncertainties in model inputs and measurements, illustrating a fundamental gap in the understanding of the magnitude of atmospheric absorption in cloud-free skies. The excess continuum type absorption required to reduce the E{sub diffuse} model overestimate ({approximately}3--8% absorptance) would significantly impact climate prediction and remote sensing. It is not clear at present what the source for this continuum absorption is. Here issues related to measurements and modeling of the surface irradiance components are discussed.

Prioritizing the refactoring need for critical component using combined approach

Directory of Open Access Journals (Sweden)

Rajni Sehgal

2018-10-01

Full Text Available One of the most promising strategies that will smooth out the maintainability issues of the software is refactoring. Due to lack of proper design approach, the code often inherits some bad smells which may lead to improper functioning of the code, especially when it is subject to change and requires some maintenance. A lot of studies have been performed to optimize the refactoring strategy which is also a very expensive process. In this paper, a component based system is considered, and a Fuzzy Multi Criteria Decision Making (FMCDM model is proposed by combining subjective and objective weights to rank the components as per their urgency of refactoring. Jdeodorant tool is used to detect the code smells from the individual components of a software system. The objective method uses the Entropy approach to rank the component having the code smell. The subjective method uses the Fuzzy TOPSIS approach based on decision makers’ judgement, to identify the critically and dependency of these code smells on the overall software. The suggested approach is implemented on component-based software having 15 components. The constitute components are ranked based on refactoring requirements.

Comparative analysis of different weight matrices in subspace system identification for structural health monitoring

Science.gov (United States)

Shokravi, H.; Bakhary, NH

2017-11-01

Subspace System Identification (SSI) is considered as one of the most reliable tools for identification of system parameters. Performance of a SSI scheme is considerably affected by the structure of the associated identification algorithm. Weight matrix is a variable in SSI that is used to reduce the dimensionality of the state-space equation. Generally one of the weight matrices of Principle Component (PC), Unweighted Principle Component (UPC) and Canonical Variate Analysis (CVA) are used in the structure of a SSI algorithm. An increasing number of studies in the field of structural health monitoring are using SSI for damage identification. However, studies that evaluate the performance of the weight matrices particularly in association with accuracy, noise resistance, and time complexity properties are very limited. In this study, the accuracy, noise-robustness, and time-efficiency of the weight matrices are compared using different qualitative and quantitative metrics. Three evaluation metrics of pole analysis, fit values and elapsed time are used in the assessment process. A numerical model of a mass-spring-dashpot and operational data is used in this research paper. It is observed that the principal components obtained using PC algorithms are more robust against noise uncertainty and give more stable results for the pole distribution. Furthermore, higher estimation accuracy is achieved using UPC algorithm. CVA had the worst performance for pole analysis and time efficiency analysis. The superior performance of the UPC algorithm in the elapsed time is attributed to using unit weight matrices. The obtained results demonstrated that the process of reducing dimensionality in CVA and PC has not enhanced the time efficiency but yield an improved modal identification in PC.

SASSYS-1 balance-of-plant component models for an integrated plant response

International Nuclear Information System (INIS)

Ku, J.-Y.

1989-01-01

Models of power plant heat transfer components and rotating machinery have been added to the balance-of-plant model in the SASSYS-1 liquid metal reactor systems analysis code. This work is part of a continuing effort in plant network simulation based on the general mathematical models developed. The models described in this paper extend the scope of the balance-of-plant model to handle non-adiabatic conditions along flow paths. While the mass and momentum equations remain the same, the energy equation now contains a heat source term due to energy transfer across the flow boundary or to work done through a shaft. The heat source term is treated fully explicitly. In addition, the equation of state is rewritten in terms of the quality and separate parameters for each phase. The models are simple enough to run quickly, yet include sufficient detail of dominant plant component characteristics to provide accurate results. 5 refs., 16 figs., 2 tabs

Does parenting affect children's eating and weight status?

Directory of Open Access Journals (Sweden)

Birch Leann L

2008-03-01

Full Text Available Abstract Background Worldwide, the prevalence of obesity among children has increased dramatically. Although the etiology of childhood obesity is multifactorial, to date, most preventive interventions have focused on school-aged children in school settings and have met with limited success. In this review, we focus on another set of influences that impact the development of children's eating and weight status: parenting and feeding styles and practices. Our review has two aims: (1 to assess the extent to which current evidence supports the hypothesis that parenting, via its effects on children's eating, is causally implicated in childhood obesity; and (2 to identify a set of promising strategies that target aspects of parenting, which can be further evaluated as possible components in childhood obesity prevention. Methods A literature review was conducted between October 2006 and January 2007. Studies published before January 2007 that assessed the association between some combination of parenting, child eating and child weight variables were included. Results A total of 66 articles met the inclusion criteria. The preponderance of these studies focused on the association between parenting and child eating. Although there was substantial experimental evidence for the influence of parenting practices, such as pressure, restriction, modeling and availability, on child eating, the majority of the evidence for the association between parenting and child weight, or the mediation of this association by child eating, was cross-sectional. Conclusion To date, there is substantial causal evidence that parenting affects child eating and there is much correlational evidence that child eating and weight influence parenting. There are few studies, however, that have used appropriate meditational designs to provide causal evidence for the indirect effect of parenting on weight status via effects on child eating. A new approach is suggested for evaluating the

Does parenting affect children's eating and weight status?

Science.gov (United States)

Ventura, Alison K; Birch, Leann L

2008-03-17

Worldwide, the prevalence of obesity among children has increased dramatically. Although the etiology of childhood obesity is multifactorial, to date, most preventive interventions have focused on school-aged children in school settings and have met with limited success. In this review, we focus on another set of influences that impact the development of children's eating and weight status: parenting and feeding styles and practices. Our review has two aims: (1) to assess the extent to which current evidence supports the hypothesis that parenting, via its effects on children's eating, is causally implicated in childhood obesity; and (2) to identify a set of promising strategies that target aspects of parenting, which can be further evaluated as possible components in childhood obesity prevention. A literature review was conducted between October 2006 and January 2007. Studies published before January 2007 that assessed the association between some combination of parenting, child eating and child weight variables were included. A total of 66 articles met the inclusion criteria. The preponderance of these studies focused on the association between parenting and child eating. Although there was substantial experimental evidence for the influence of parenting practices, such as pressure, restriction, modeling and availability, on child eating, the majority of the evidence for the association between parenting and child weight, or the mediation of this association by child eating, was cross-sectional. To date, there is substantial causal evidence that parenting affects child eating and there is much correlational evidence that child eating and weight influence parenting. There are few studies, however, that have used appropriate meditational designs to provide causal evidence for the indirect effect of parenting on weight status via effects on child eating. A new approach is suggested for evaluating the effectiveness of intervention components and creating optimized

Meson-baryon components in the states of the baryon decuplet

Energy Technology Data Exchange (ETDEWEB)

Aceti, F.; Oset, E. [Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Departamento de Fisica Teorica y IFIC, Valencia (Spain); Kavli Institute for Theoretical Physics China, Beijing (China); Dai, L.R. [Liaoning Normal University, Department of Physics, Dalian (China); Kavli Institute for Theoretical Physics China, Beijing (China); Geng, L.S. [Beihang University, School of Physics and Nuclear Energy Engineering and International Research Center for Nuclei and Particles in the Cosmos, Beijing (China); Zhang, Y. [Liaoning Normal University, Department of Physics, Dalian (China)

2014-03-15

We apply an extension of the Weinberg compositeness condition on partial waves of L = 1 and resonant states to determine the weight of the meson-baryon component in the Δ(1232) resonance and the other members of the J{sup P} = (3)/(2){sup +} baryon decuplet. We obtain an appreciable weight of πN in the Δ(1232) wave function, of the order of 60%, which looks more natural when one recalls that experiments on deep inelastic and Drell Yan give a fraction of πN component of 34% for the nucleon. We also show that, as we go to higher energies in the members of the decuplet, the weights of the meson-baryon component decrease and they already show a dominant part for a genuine, non-meson-baryon, component in the wave function. We write a section to interpret the meaning of the Weinberg sum rule when it is extended to complex energies and another one for the case of an energy-dependent potential. (orig.)

Robustness of weighted networks

Science.gov (United States)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

The role of information in a lifetime process - a model of weight maintenance by women over long time periods

Directory of Open Access Journals (Sweden)

Judit Bar-Ilan

2006-01-01

Full Text Available Introduction. This paper proposes a model of information behaviour of women during their life-long struggle to maintain normal weight. Method. The model is integrative and contextual, built on existing models in information science and several other disciplines, and the life stories of about fifty Israeli women aged 25-55 and interviews with professionals. Analysis. The life stories of the participating women were analyzed qualitatively, major themes and phases were identified. Results. Weight loss and/or maintenance behaviour is a lifetime process in which distinctive stages were identified. In most cases the weight gain - weight loss - maintenance cycle is a recurring cycle. Information is a major resource during the process: several roles of information were defined: enabling, motivating, reinforcing, providing background information related to weight problems and creating the internal cognitive schema related to food and weight. Information behaviour and the roles of information vary with the different stages. Information needs are also influenced by the specific stage of the process. Information gathered at previous cycles is reused, and information gained through previous experience effects behaviour in the current cycle. Conclusion. The model has both theoretical and practical implications.

Two component WIMP-FImP dark matter model with singlet fermion, scalar and pseudo scalar

Energy Technology Data Exchange (ETDEWEB)

Dutta Banik, Amit; Pandey, Madhurima; Majumdar, Debasish [Saha Institute of Nuclear Physics, HBNI, Astroparticle Physics and Cosmology Division, Kolkata (India); Biswas, Anirban [Harish Chandra Research Institute, Allahabad (India)

2017-10-15

We explore a two component dark matter model with a fermion and a scalar. In this scenario the Standard Model (SM) is extended by a fermion, a scalar and an additional pseudo scalar. The fermionic component is assumed to have a global U(1){sub DM} and interacts with the pseudo scalar via Yukawa interaction while a Z{sub 2} symmetry is imposed on the other component - the scalar. These ensure the stability of both dark matter components. Although the Lagrangian of the present model is CP conserving, the CP symmetry breaks spontaneously when the pseudo scalar acquires a vacuum expectation value (VEV). The scalar component of the dark matter in the present model also develops a VEV on spontaneous breaking of the Z{sub 2} symmetry. Thus the various interactions of the dark sector and the SM sector occur through the mixing of the SM like Higgs boson, the pseudo scalar Higgs like boson and the singlet scalar boson. We show that the observed gamma ray excess from the Galactic Centre as well as the 3.55 keV X-ray line from Perseus, Andromeda etc. can be simultaneously explained in the present two component dark matter model and the dark matter self interaction is found to be an order of magnitude smaller than the upper limit estimated from the observational results. (orig.)

Lightweighting Impacts on Fuel Economy, Cost, and Component Losses

Energy Technology Data Exchange (ETDEWEB)

Brooker, A. D.; Ward, J.; Wang, L.

2013-01-01

The Future Automotive Systems Technology Simulator (FASTSim) is the U.S. Department of Energy's high-level vehicle powertrain model developed at the National Renewable Energy Laboratory. It uses a time versus speed drive cycle to estimate the powertrain forces required to meet the cycle. It simulates the major vehicle powertrain components and their losses. It includes a cost model based on component sizing and fuel prices. FASTSim simulated different levels of lightweighting for four different powertrains: a conventional gasoline engine vehicle, a hybrid electric vehicle (HEV), a plug-in hybrid electric vehicle (PHEV), and a battery electric vehicle (EV). Weight reductions impacted the conventional vehicle's efficiency more than the HEV, PHEV and EV. Although lightweighting impacted the advanced vehicles' efficiency less, it reduced component cost and overall costs more. The PHEV and EV are less cost effective than the conventional vehicle and HEV using current battery costs. Assuming the DOE's battery cost target of $100/kWh, however, the PHEV attained similar cost and lightweighting benefits. Generally, lightweighting was cost effective when it costs less than $6/kg of mass eliminated.

Hourly cooling load forecasting using time-indexed ARX models with two-stage weighted least squares regression

International Nuclear Information System (INIS)

Guo, Yin; Nazarian, Ehsan; Ko, Jeonghan; Rajurkar, Kamlakar

2014-01-01

Highlights: • Developed hourly-indexed ARX models for robust cooling-load forecasting. • Proposed a two-stage weighted least-squares regression approach. • Considered the effect of outliers as well as trend of cooling load and weather patterns. • Included higher order terms and day type patterns in the forecasting models. • Demonstrated better accuracy compared with some ARX and ANN models. - Abstract: This paper presents a robust hourly cooling-load forecasting method based on time-indexed autoregressive with exogenous inputs (ARX) models, in which the coefficients are estimated through a two-stage weighted least squares regression. The prediction method includes a combination of two separate time-indexed ARX models to improve prediction accuracy of the cooling load over different forecasting periods. The two-stage weighted least-squares regression approach in this study is robust to outliers and suitable for fast and adaptive coefficient estimation. The proposed method is tested on a large-scale central cooling system in an academic institution. The numerical case studies show the proposed prediction method performs better than some ANN and ARX forecasting models for the given test data set

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

Science.gov (United States)

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep

Modeling cellular networks in fading environments with dominant specular components

KAUST Repository

Alammouri, Ahmad; Elsawy, Hesham; Salem, Ahmed Sultan; Di Renzo, Marco; Alouini, Mohamed-Slim

2016-01-01

to the Nakagami-m fading in some special cases. However, neither the Rayleigh nor the Nakagami-m accounts for dominant specular components (DSCs) which may appear in realistic fading channels. In this paper, we present a tractable model for cellular networks

Mathematical modeling of ethanol production in solid-state fermentation based on solid medium' dry weight variation.

Science.gov (United States)

Mazaheri, Davood; Shojaosadati, Seyed Abbas; Zamir, Seyed Morteza; Mousavi, Seyyed Mohammad

2018-04-21

In this work, mathematical modeling of ethanol production in solid-state fermentation (SSF) has been done based on the variation in the dry weight of solid medium. This method was previously used for mathematical modeling of enzyme production; however, the model should be modified to predict the production of a volatile compound like ethanol. The experimental results of bioethanol production from the mixture of carob pods and wheat bran by Zymomonas mobilis in SSF were used for the model validation. Exponential and logistic kinetic models were used for modeling the growth of microorganism. In both cases, the model predictions matched well with the experimental results during the exponential growth phase, indicating the good ability of solid medium weight variation method for modeling a volatile product formation in solid-state fermentation. In addition, using logistic model, better predictions were obtained.

Understanding the Determinants of Weight-Related Quality of Life among Bariatric Surgery Candidates

Directory of Open Access Journals (Sweden)

Annie Tessier

2012-01-01

Full Text Available Obesity and its relation to quality of life are multifaceted. The purpose of this paper was to contribute evidence to support a framework for understanding the impact of obesity on quality of life in 42 morbidly obese subjects considering a wide number of potential determinants. A model of weight-related quality of life (WRQL was developed based on the Wilson-Cleary model, considering subjects' weight characteristics, arterial oxygen pressure (PaO2, walking capacity (6-minute walk test, 6MWT, health-related quality of life (HRQL; Physical and Mental Component Summaries of the SF-36 PCS/MCS, and WRQL. The model of WRQL was tested with linear regressions and a path analysis, which showed that as PaO2 at rest increased 6MWT increased. 6MWT was positively associated with the PCS, which in turn was positively related to WRQL along with the MCS. The model showed good fit and explained 38% of the variance in WRQL.

Weighted Watson-Crick automata

Energy Technology Data Exchange (ETDEWEB)

Tamrin, Mohd Izzuddin Mohd [Department of Information System, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 50728 Gombak, Selangor (Malaysia); Turaev, Sherzod; Sembok, Tengku Mohd Tengku [Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 50728 Gombak, Selangor (Malaysia)

2014-07-10

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

Weighted Watson-Crick automata

International Nuclear Information System (INIS)

Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

2014-01-01

There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power

The relationship between prevalence and duration of weight loss strategies and weight loss among overweight managed care organization members enrolled in a weight loss trial

Directory of Open Access Journals (Sweden)

Jeffery Robert W

2006-02-01

Full Text Available Abstract Background Many adults in the United States report engaging in weight loss behaviors. The current study examined weight loss strategies among managed care organization members, to determine the prevalence and impact of weight loss behaviors in this population. We hypothesized that greater engagement in weight loss strategies would be associated with greater weight loss success. Methods Data were taken from Weigh-to-Be (WTB, a two-year weight loss trial (N = 1801, 72% female, mean age = 50.7 years, mean weight = 95.9 kg, mean BMI = 34.2 kg/m2. Every six months, participants completed a questionnaire assessing frequency and duration of weight loss strategies (calorie reduction, fat reduction, increased fruit/vegetable intake, increased exercise, elimination of sweets, consumption of less food. General linear models and structural equation methods were used to examine associations between weight loss strategy use and weight change over time. Results Weight loss strategy prevalence rates ranged from 68% to 76% over two years. For all dietary strategies, any use of the strategy between baseline and 24 months was associated with weight loss at 24 months; those who did not engage in the strategy showed weight gains during that period. Results of general linear models and structural equation models indicated that increased use of weight loss strategies was significantly associated with greater 24-month weight loss. Conclusion The prevalence of weight loss strategies in this obese adult managed care population was quite high, and use of these strategies was associated in dose-response fashion with better weight loss. Future interventions may benefit from emphasis on persistence of similar strategies to achieve more successful outcomes.

Weight loss methods and changes in eating habits among successful weight losers.

Science.gov (United States)

Soini, Sirpa; Mustajoki, Pertti; Eriksson, Johan G

2016-01-01

Changes in several lifestyle related factors are required for successful long-term weight loss. Identification of these factors is of major importance from a public health point of view. This study was based upon findings from the Finnish Weight Control Registry (FWCR), a web-based registry. In total, 316 people were recruited and 184 met the study inclusion criteria. The aims of this study were to assess means and typical changes in eating habits associated with successful long-term weight loss. Half of the participants (48%) reported that they lost weight slowly primarily with dietary changes. Self-weighing frequency was high, 92% was weighing themselves at least once a week during the weight loss phase, and 75% during the maintenance phase. Dietary aspects associated with successful weight loss and weight maintenance included an increase in intake of vegetables, a reduction in frequency of eating candies and fast food, regular meal frequency and application of the Plate model. Both slow and fast weight loss may lead to successful long-term results and weight maintenance. A decrease in energy intake was achieved by reducing intake of energy-dense food, applying the Plate model and by regular meal frequency. Key messages Successful long-term weight loss is associated with a reduction in intake of energy-dense food. A more regular meal frequency and a high frequency of self-weighing seem to be helpful.

Early weight loss predicts weight loss treatment response regardless of binge-eating disorder status and pretreatment weight change.

Science.gov (United States)

Barnes, Rachel D; Ivezaj, Valentina; Pittman, Brian P; Grilo, Carlos M

2018-04-10

Individuals seeking weight loss treatment have diverse pretreatment weight trajectories, and once enrolled, individuals' response to weight loss treatments also varies greatly and may be influenced by the presence of binge-eating disorder (BED). Reported average weight losses may obscure these considerable differences. This study examined whether BED status and different weight-related change variables are associated with successful weight loss treatment outcomes in a controlled treatment study. Participants (N = 89) with overweight/obesity, with and without BED, participated in a 3-month weight loss trial in primary care with 3- and 12-month follow-ups. We tested the prognostic significance of four weight-related change variables (the last supper, early weight loss, pretreatment weight trajectory, weight suppression) on outcomes (weight loss-overall, weight loss-"subsequent," weight loss during second half of treatment). Early weight loss was positively associated with weight loss-overall at post-treatment, and at 3-month and 12-month follow-up. Early weight loss was positively associated with weight loss-subsequent at post-treatment only. No other weight-related variables were significantly associated with weight loss. Models including BED status and treatment condition were not significant. Participants with early weight loss were more likely to continue losing weight, regardless of BED status or treatment condition. The results highlight the importance of early dedication to weight loss treatment to increase the likelihood of positive outcomes. © 2018 Wiley Periodicals, Inc.