Multiple skeletal muscle metastases revealing a cardiac intimal sarcoma

Energy Technology Data Exchange (ETDEWEB)

Crombe, Amandine [Institut Bergonie, Department of Radiology, Bordeaux (France); Lintingre, Pierre-Francois; Dallaudiere, Benjamin [Clinique du Sport de Bordeaux-Merignac, Department of Musculoskeletal Radiology, Merignac (France); Le Loarer, Francois [Institut Bergonie, Department of Pathology, Bordeaux (France); Lachatre, Denis [Dupuytren University Hospital, Department of Radiology, Limoges (France)

2018-01-15

We report the case of a 59-year-old female with progressive bilateral painful swelling of the thighs. MRI revealed multiple intramuscular necrotic masses with similar morphologic patterns. Whole-body CT and 18-FDG PET-CT scans demonstrated additional hypermetabolic muscular masses and a lobulated lesion within the left atrial cavity. As biopsy of a muscular mass was compatible with a poorly differentiated sarcoma with MDM2 oncogene amplification, two diagnoses were discussed: a dedifferentiated liposarcoma with muscle and heart metastases or a primary cardiac sarcoma, mainly a cardiac intimal sarcoma, with muscular metastases, which was finally confirmed by array-comparative genomic hybridization (aCGH) in a sarcoma reference center. This case emphasizes the potential for intimal sarcoma to disseminate in skeletal muscle prior to any other organ and the need for a genomic approach in addition to classical radiopathologic analyses to distinguish primary from secondary locations facing simultaneous tumors of the heart and skeletal muscles with MDM2 amplification. (orig.)

Geometrical model of multiple production

International Nuclear Information System (INIS)

Chikovani, Z.E.; Jenkovszky, L.L.; Kvaratshelia, T.M.; Struminskij, B.V.

1988-01-01

The relation between geometrical and KNO-scaling and their violation is studied in a geometrical model of multiple production of hadrons. Predictions concerning the behaviour of correlation coefficients at future accelerators are given

Multiplicity Control in Structural Equation Modeling

Science.gov (United States)

Cribbie, Robert A.

2007-01-01

Researchers conducting structural equation modeling analyses rarely, if ever, control for the inflated probability of Type I errors when evaluating the statistical significance of multiple parameters in a model. In this study, the Type I error control, power and true model rates of famsilywise and false discovery rate controlling procedures were…

Nonlinear Modeling and Identification of an Aluminum Honeycomb Panel with Multiple Bolts

Directory of Open Access Journals (Sweden)

Yongpeng Chu

2016-01-01

Full Text Available This paper focuses on the nonlinear dynamics modeling and parameter identification of an Aluminum Honeycomb Panel (AHP with multiple bolted joints. Finite element method using eight-node solid elements is exploited to model the panel and the bolted connection interface as a homogeneous, isotropic plate and as a thin layer of nonlinear elastic-plastic material, respectively. The material properties of a thin layer are defined by a bilinear elastic plastic model, which can describe the energy dissipation and softening phenomena in the bolted joints under nonlinear states. Experimental tests at low and high excitation levels are performed to reveal the dynamic characteristics of the bolted structure. In particular, the linear material parameters of the panel are identified via experimental tests at low excitation levels, whereas the nonlinear material parameters of the thin layer are updated by using the genetic algorithm to minimize the residual error between the measured and the simulation data at a high excitation level. It is demonstrated by comparing the frequency responses of the updated FEM and the experimental system that the thin layer of bilinear elastic-plastic material is very effective for modeling the nonlinear joint interface of the assembled structure with multiple bolts.

Relative efficiency of joint-model and full-conditional-specification multiple imputation when conditional models are compatible: The general location model.

Science.gov (United States)

Seaman, Shaun R; Hughes, Rachael A

2018-06-01

Estimating the parameters of a regression model of interest is complicated by missing data on the variables in that model. Multiple imputation is commonly used to handle these missing data. Joint model multiple imputation and full-conditional specification multiple imputation are known to yield imputed data with the same asymptotic distribution when the conditional models of full-conditional specification are compatible with that joint model. We show that this asymptotic equivalence of imputation distributions does not imply that joint model multiple imputation and full-conditional specification multiple imputation will also yield asymptotically equally efficient inference about the parameters of the model of interest, nor that they will be equally robust to misspecification of the joint model. When the conditional models used by full-conditional specification multiple imputation are linear, logistic and multinomial regressions, these are compatible with a restricted general location joint model. We show that multiple imputation using the restricted general location joint model can be substantially more asymptotically efficient than full-conditional specification multiple imputation, but this typically requires very strong associations between variables. When associations are weaker, the efficiency gain is small. Moreover, full-conditional specification multiple imputation is shown to be potentially much more robust than joint model multiple imputation using the restricted general location model to mispecification of that model when there is substantial missingness in the outcome variable.

Guideline validation in multiple trauma care through business process modeling.

Science.gov (United States)

Stausberg, Jürgen; Bilir, Hüseyin; Waydhas, Christian; Ruchholtz, Steffen

2003-07-01

Clinical guidelines can improve the quality of care in multiple trauma. In our Department of Trauma Surgery a specific guideline is available paper-based as a set of flowcharts. This format is appropriate for the use by experienced physicians but insufficient for electronic support of learning, workflow and process optimization. A formal and logically consistent version represented with a standardized meta-model is necessary for automatic processing. In our project we transferred the paper-based into an electronic format and analyzed the structure with respect to formal errors. Several errors were detected in seven error categories. The errors were corrected to reach a formally and logically consistent process model. In a second step the clinical content of the guideline was revised interactively using a process-modeling tool. Our study reveals that guideline development should be assisted by process modeling tools, which check the content in comparison to a meta-model. The meta-model itself could support the domain experts in formulating their knowledge systematically. To assure sustainability of guideline development a representation independent of specific applications or specific provider is necessary. Then, clinical guidelines could be used for eLearning, process optimization and workflow management additionally.

Integration of multiple, excess, backup, and expected covering models

OpenAIRE

M S Daskin; K Hogan; C ReVelle

1988-01-01

The concepts of multiple, excess, backup, and expected coverage are defined. Model formulations using these constructs are reviewed and contrasted to illustrate the relationships between them. Several new formulations are presented as is a new derivation of the expected covering model which indicates more clearly the relationship of the model to other multi-state covering models. An expected covering model with multiple time standards is also presented.

Evolving Four Part Harmony Using a Multiple Worlds Model

DEFF Research Database (Denmark)

Scirea, Marco; Brown, Joseph Alexander

2015-01-01

This application of the Multiple Worlds Model examines a collaborative fitness model for generating four part harmonies. In this model we have multiple populations and the fitness of the individuals is based on the ability of a member from each population to work with the members of other...

Double-multiple streamtube model for Darrieus in turbines

Science.gov (United States)

Paraschivoiu, I.

1981-01-01

An analytical model is proposed for calculating the rotor performance and aerodynamic blade forces for Darrieus wind turbines with curved blades. The method of analysis uses a multiple-streamtube model, divided into two parts: one modeling the upstream half-cycle of the rotor and the other, the downstream half-cycle. The upwind and downwind components of the induced velocities at each level of the rotor were obtained using the principle of two actuator disks in tandem. Variation of the induced velocities in the two parts of the rotor produces larger forces in the upstream zone and smaller forces in the downstream zone. Comparisons of the overall rotor performance with previous methods and field test data show the important improvement obtained with the present model. The calculations were made using the computer code CARDAA developed at IREQ. The double-multiple streamtube model presented has two major advantages: it requires a much shorter computer time than the three-dimensional vortex model and is more accurate than multiple-streamtube model in predicting the aerodynamic blade loads.

Multiple model cardinalized probability hypothesis density filter

Science.gov (United States)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

Mean multiplicity in the Regge models with rising cross sections

International Nuclear Information System (INIS)

Chikovani, Z.E.; Kobylisky, N.A.; Martynov, E.S.

1979-01-01

Behaviour of the mean multiplicity and the total cross section σsub(t) of hadron-hadron interactions is considered in the framework of the Regge models at high energies. Generating function was plotted for models of dipole and froissaron, and the mean multiplicity and multiplicity moments were calculated. It is shown that approximately ln 2 S (energy square) in the dipole model, which is in good agreement with the experiment. It is also found that in various Regge models approximately σsub(t)lnS

Analysis and application of opinion model with multiple topic interactions.

Science.gov (United States)

Xiong, Fei; Liu, Yun; Wang, Liang; Wang, Ximeng

2017-08-01

To reveal heterogeneous behaviors of opinion evolution in different scenarios, we propose an opinion model with topic interactions. Individual opinions and topic features are represented by a multidimensional vector. We measure an agent's action towards a specific topic by the product of opinion and topic feature. When pairs of agents interact for a topic, their actions are introduced to opinion updates with bounded confidence. Simulation results show that a transition from a disordered state to a consensus state occurs at a critical point of the tolerance threshold, which depends on the opinion dimension. The critical point increases as the dimension of opinions increases. Multiple topics promote opinion interactions and lead to the formation of macroscopic opinion clusters. In addition, more topics accelerate the evolutionary process and weaken the effect of network topology. We use two sets of large-scale real data to evaluate the model, and the results prove its effectiveness in characterizing a real evolutionary process. Our model achieves high performance in individual action prediction and even outperforms state-of-the-art methods. Meanwhile, our model has much smaller computational complexity. This paper provides a demonstration for possible practical applications of theoretical opinion dynamics.

Mycobacterium malmesburyense sp. nov., a non-tuberculous species of the genus Mycobacterium revealed by multiple gene sequence characterization

CSIR Research Space (South Africa)

Gcebe, N

2017-04-01

Full Text Available Journal of Systematic and Evolutionary Microbiology: DOI 10.1099/ijsem.0.001678 Mycobacterium malmesburyense sp. nov., a non-tuberculous species of the genus Mycobacterium revealed by multiple gene sequence characterization Gcebe N Rutten V Gey...

Multiple model adaptive control with mixing

Science.gov (United States)

Kuipers, Matthew

Despite the remarkable theoretical accomplishments and successful applications of adaptive control, the field is not sufficiently mature to solve challenging control problems requiring strict performance and safety guarantees. Towards addressing these issues, a novel deterministic multiple-model adaptive control approach called adaptive mixing control is proposed. In this approach, adaptation comes from a high-level system called the supervisor that mixes into feedback a number of candidate controllers, each finely-tuned to a subset of the parameter space. The mixing signal, the supervisor's output, is generated by estimating the unknown parameters and, at every instant of time, calculating the contribution level of each candidate controller based on certainty equivalence. The proposed architecture provides two characteristics relevant to solving stringent, performance-driven applications. First, the full-suite of linear time invariant control tools is available. A disadvantage of conventional adaptive control is its restriction to utilizing only those control laws whose solutions can be feasibly computed in real-time, such as model reference and pole-placement type controllers. Because its candidate controllers are computed off line, the proposed approach suffers no such restriction. Second, the supervisor's output is smooth and does not necessarily depend on explicit a priori knowledge of the disturbance model. These characteristics can lead to improved performance by avoiding the unnecessary switching and chattering behaviors associated with some other multiple adaptive control approaches. The stability and robustness properties of the adaptive scheme are analyzed. It is shown that the mean-square regulation error is of the order of the modeling error. And when the parameter estimate converges to its true value, which is guaranteed if a persistence of excitation condition is satisfied, the adaptive closed-loop system converges exponentially fast to a closed

Multiple surveys employing a new sample-processing protocol reveal the genetic diversity of placozoans in Japan.

Science.gov (United States)

Miyazawa, Hideyuki; Nakano, Hiroaki

2018-03-01

Placozoans, flat free-living marine invertebrates, possess an extremely simple bauplan lacking neurons and muscle cells and represent one of the earliest-branching metazoan phyla. They are widely distributed from temperate to tropical oceans. Based on mitochondrial 16S rRNA sequences, 19 haplotypes forming seven distinct clades have been reported in placozoans to date. In Japan, placozoans have been found at nine locations, but 16S genotyping has been performed at only two of these locations. Here, we propose a new processing protocol, "ethanol-treated substrate sampling," for collecting placozoans from natural environments. We also report the collection of placozoans from three new locations, the islands of Shikine-jima, Chichi-jima, and Haha-jima, and we present the distribution of the 16S haplotypes of placozoans in Japan. Multiple surveys conducted at multiple locations yielded five haplotypes that were not reported previously, revealing high genetic diversity in Japan, especially at Shimoda and Shikine-jima Island. The observed geographic distribution patterns were different among haplotypes; some were widely distributed, while others were sampled only from a single location. However, samplings conducted on different dates at the same sites yielded different haplotypes, suggesting that placozoans of a given haplotype do not inhabit the same site constantly throughout the year. Continued sampling efforts conducted during all seasons at multiple locations worldwide and the development of molecular markers within the haplotypes are needed to reveal the geographic distribution pattern and dispersal history of placozoans in greater detail.

Design of Xen Hybrid Multiple Police Model

Science.gov (United States)

Sun, Lei; Lin, Renhao; Zhu, Xianwei

2017-10-01

Virtualization Technology has attracted more and more attention. As a popular open-source virtualization tools, XEN is used more and more frequently. Xsm, XEN security model, has also been widespread concern. The safety status classification has not been established in the XSM, and it uses the virtual machine as a managed object to make Dom0 a unique administrative domain that does not meet the minimum privilege. According to these questions, we design a Hybrid multiple police model named SV_HMPMD that organically integrates multiple single security policy models include DTE,RBAC,BLP. It can fullfill the requirement of confidentiality and integrity for security model and use different particle size to different domain. In order to improve BLP’s practicability, the model introduce multi-level security labels. In order to divide the privilege in detail, we combine DTE with RBAC. In order to oversize privilege, we limit the privilege of domain0.

Supersymmetric U(1)' model with multiple dark matters

International Nuclear Information System (INIS)

Hur, Taeil; Lee, Hye-Sung; Nasri, Salah

2008-01-01

We consider a scenario where a supersymmetric model has multiple dark matter particles. Adding a U(1) ' gauge symmetry is a well-motivated extension of the minimal supersymmetric standard model (MSSM). It can cure the problems of the MSSM such as the μ problem or the proton decay problem with high-dimensional lepton number and baryon number violating operators which R parity allows. An extra parity (U parity) may arise as a residual discrete symmetry after U(1) ' gauge symmetry is spontaneously broken. The lightest U-parity particle (LUP) is stable under the new parity becoming a new dark matter candidate. Up to three massive particles can be stable in the presence of the R parity and the U parity. We numerically illustrate that multiple stable particles in our model can satisfy both constraints from the relic density and the direct detection, thus providing a specific scenario where a supersymmetric model has well-motivated multiple dark matters consistent with experimental constraints. The scenario provides new possibilities in the present and upcoming dark matter searches in the direct detection and collider experiments

Multiple Social Networks, Data Models and Measures for

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2017-01-01

Multiple Social Network Analysis is a discipline defining models, measures, methodologies, and algorithms to study multiple social networks together as a single social system. It is particularly valuable when the networks are interconnected, e.g., the same actors are present in more than one...

Multiple roles of integrin-linked kinase in epidermal development, maturation and pigmentation revealed by molecular profiling.

Directory of Open Access Journals (Sweden)

David Judah

Full Text Available Integrin-linked kinase (ILK is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function.

Multiple roles of integrin-linked kinase in epidermal development, maturation and pigmentation revealed by molecular profiling.

Science.gov (United States)

Judah, David; Rudkouskaya, Alena; Wilson, Ryan; Carter, David E; Dagnino, Lina

2012-01-01

Integrin-linked kinase (ILK) is an important scaffold protein that mediates a variety of cellular responses to integrin stimulation by extracellular matrix proteins. Mice with epidermis-restricted inactivation of the Ilk gene exhibit pleiotropic phenotypic defects, including impaired hair follicle morphogenesis, reduced epidermal adhesion to the basement membrane, compromised epidermal integrity, as well as wasting and failure to thrive leading to perinatal death. To better understand the underlying molecular mechanisms that cause such a broad range of alterations, we investigated the impact of Ilk gene inactivation on the epidermis transcriptome. Microarray analysis showed over 700 differentially regulated mRNAs encoding proteins involved in multiple aspects of epidermal function, including keratinocyte differentiation and barrier formation, inflammation, regeneration after injury, and fundamental epidermal developmental pathways. These studies also revealed potential effects on genes not previously implicated in ILK functions, including those important for melanocyte and melanoblast development and function, regulation of cytoskeletal dynamics, and homeobox genes. This study shows that ILK is a critical regulator of multiple aspects of epidermal function and homeostasis, and reveals the previously unreported involvement of ILK not only in epidermal differentiation and barrier formation, but also in melanocyte genesis and function.

SDG and qualitative trend based model multiple scale validation

Science.gov (United States)

Gao, Dong; Xu, Xin; Yin, Jianjin; Zhang, Hongyu; Zhang, Beike

2017-09-01

Verification, Validation and Accreditation (VV&A) is key technology of simulation and modelling. For the traditional model validation methods, the completeness is weak; it is carried out in one scale; it depends on human experience. The SDG (Signed Directed Graph) and qualitative trend based multiple scale validation is proposed. First the SDG model is built and qualitative trends are added to the model. And then complete testing scenarios are produced by positive inference. The multiple scale validation is carried out by comparing the testing scenarios with outputs of simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.

A Multiple Items EPQ/EOQ Model for a Vendor and Multiple Buyers System with Considering Continuous and Discrete Demand Simultaneously

Science.gov (United States)

Jonrinaldi; Rahman, T.; Henmaidi; Wirdianto, E.; Zhang, D. Z.

2018-03-01

This paper proposed a mathematical model for multiple items Economic Production and Order Quantity (EPQ/EOQ) with considering continuous and discrete demand simultaneously in a system consisting of a vendor and multiple buyers. This model is used to investigate the optimal production lot size of the vendor and the number of shipments policy of orders to multiple buyers. The model considers the multiple buyers’ holding cost as well as transportation cost, which minimize the total production and inventory costs of the system. The continuous demand from any other customers can be fulfilled anytime by the vendor while the discrete demand from multiple buyers can be fulfilled by the vendor using the multiple delivery policy with a number of shipments of items in the production cycle time. A mathematical model is developed to illustrate the system based on EPQ and EOQ model. Solution procedures are proposed to solve the model using a Mixed Integer Non Linear Programming (MINLP) and algorithm methods. Then, the numerical example is provided to illustrate the system and results are discussed.

Localization of a small change in a multiple scattering environment without modeling of the actual medium

OpenAIRE

Rakotonarivo , Sandrine; Walker , S.C.; Kuperman , W. A.; Roux , Philippe

2011-01-01

International audience; A method to actively localize a small perturbation in a multiple scattering medium using a collection of remote acoustic sensors is presented. The approach requires only minimal modeling and no knowledge of the scatterer distribution and properties of the scattering medium and the perturbation. The medium is ensonified before and after a perturbation is introduced. The coherent difference between the measured signals then reveals all field components that have interact...

Multiple commodities in statistical microeconomics: Model and market

Science.gov (United States)

Baaquie, Belal E.; Yu, Miao; Du, Xin

2016-11-01

A statistical generalization of microeconomics has been made in Baaquie (2013). In Baaquie et al. (2015), the market behavior of single commodities was analyzed and it was shown that market data provides strong support for the statistical microeconomic description of commodity prices. The case of multiple commodities is studied and a parsimonious generalization of the single commodity model is made for the multiple commodities case. Market data shows that the generalization can accurately model the simultaneous correlation functions of up to four commodities. To accurately model five or more commodities, further terms have to be included in the model. This study shows that the statistical microeconomics approach is a comprehensive and complete formulation of microeconomics, and which is independent to the mainstream formulation of microeconomics.

Monoclonal antibodies reveal multiple forms of expression of human microsomal epoxide hydrolase

Energy Technology Data Exchange (ETDEWEB)

Duan, Hongying; Takagi, Akira [Department of Microbiology, Faculty of Medicine, Saitama Medical University, Moroyama-cho, Iruma-gun, Saitama 350-0495 (Japan); Kayano, Hidekazu [Department of Pathology, Faculty of Medicine, Saitama Medical University, Moroyama-cho, Iruma-gun, Saitama 350-0495 (Japan); Koyama, Isamu [Department of Digestive and General Surgery, Saitama International Medical Center, Faculty of Medicine, Saitama Medical University, 1397-1 Yamane, Hidaka, Saitama 350-1298 (Japan); Morisseau, Christophe; Hammock, Bruce D. [Department of Entomology and Cancer Center, University of California, Davis, One Shields Avenue, Davis, CA 95616-8584 (United States); Akatsuka, Toshitaka, E-mail: akatsuka@saitama-med.ac.jp [Department of Microbiology, Faculty of Medicine, Saitama Medical University, Moroyama-cho, Iruma-gun, Saitama 350-0495 (Japan)

2012-04-01

In a previous study, we developed five kinds of monoclonal antibodies against different portions of human mEH: three, anti-N-terminal; one, anti-C-terminal; one, anti-conformational epitope. Using them, we stained the intact and the permeabilized human cells of various kinds and performed flow cytometric analysis. Primary hepatocytes and peripheral blood mononuclear cells (PBMC) showed remarkable differences. On the surface, hepatocytes exhibited 4 out of 5 epitopes whereas PBMC did not show any of the epitopes. mEH was detected inside both cell types, but the most prominent expression was observed for the conformational epitope in the hepatocytes and the two N-terminal epitopes in PBMC. These differences were also observed between hepatocyte-derived cell lines and mononuclear cell-derived cell lines. In addition, among each group, there were several differences which may be related to the cultivation, the degree of differentiation, or the original cell subsets. We also noted that two glioblastoma cell lines reveal marked expression of the conformational epitope on the surface which seemed to correlate with the brain tumor-associated antigen reported elsewhere. Several cell lines also underwent selective permeabilization before flow cytometric analysis, and we noticed that the topological orientation of mEH on the ER membrane in those cells was in accordance with the previous report. However, the orientation on the cell surface was inconsistent with the report and had a great variation between the cells. These findings show the multiple mode of expression of mEH which may be possibly related to the multiple roles that mEH plays in different cells. -- Highlights: ► We examine expression of five mEH epitopes in human cells. ► Remarkable differences exist between hepatocytes and PBMC. ► mEH expression in cell lines differs depending on several factors. ► Some glioblastoma cell lines reveal marked surface expression of mEH. ► Topology of mEH on the cell

AgMIP Training in Multiple Crop Models and Tools

Science.gov (United States)

Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

2015-01-01

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

Efficient Adoption and Assessment of Multiple Process Improvement Reference Models

Directory of Open Access Journals (Sweden)

Simona Jeners

2013-06-01

Full Text Available A variety of reference models such as CMMI, COBIT or ITIL support IT organizations to improve their processes. These process improvement reference models (IRMs cover different domains such as IT development, IT Services or IT Governance but also share some similarities. As there are organizations that address multiple domains and need to coordinate their processes in their improvement we present MoSaIC, an approach to support organizations to efficiently adopt and conform to multiple IRMs. Our solution realizes a semantic integration of IRMs based on common meta-models. The resulting IRM integration model enables organizations to efficiently implement and asses multiple IRMs and to benefit from synergy effects.

Adaptive Active Noise Suppression Using Multiple Model Switching Strategy

Directory of Open Access Journals (Sweden)

Quanzhen Huang

2017-01-01

Full Text Available Active noise suppression for applications where the system response varies with time is a difficult problem. The computation burden for the existing control algorithms with online identification is heavy and easy to cause control system instability. A new active noise control algorithm is proposed in this paper by employing multiple model switching strategy for secondary path varying. The computation is significantly reduced. Firstly, a noise control system modeling method is proposed for duct-like applications. Then a multiple model adaptive control algorithm is proposed with a new multiple model switching strategy based on filter-u least mean square (FULMS algorithm. Finally, the proposed algorithm was implemented on Texas Instruments digital signal processor (DSP TMS320F28335 and real time experiments were done to test the proposed algorithm and FULMS algorithm with online identification. Experimental verification tests show that the proposed algorithm is effective with good noise suppression performance.

Multiple flood vulnerability assessment approach based on fuzzy comprehensive evaluation method and coordinated development degree model.

Science.gov (United States)

Yang, Weichao; Xu, Kui; Lian, Jijian; Bin, Lingling; Ma, Chao

2018-05-01

Flood is a serious challenge that increasingly affects the residents as well as policymakers. Flood vulnerability assessment is becoming gradually relevant in the world. The purpose of this study is to develop an approach to reveal the relationship between exposure, sensitivity and adaptive capacity for better flood vulnerability assessment, based on the fuzzy comprehensive evaluation method (FCEM) and coordinated development degree model (CDDM). The approach is organized into three parts: establishment of index system, assessment of exposure, sensitivity and adaptive capacity, and multiple flood vulnerability assessment. Hydrodynamic model and statistical data are employed for the establishment of index system; FCEM is used to evaluate exposure, sensitivity and adaptive capacity; and CDDM is applied to express the relationship of the three components of vulnerability. Six multiple flood vulnerability types and four levels are proposed to assess flood vulnerability from multiple perspectives. Then the approach is applied to assess the spatiality of flood vulnerability in Hainan's eastern area, China. Based on the results of multiple flood vulnerability, a decision-making process for rational allocation of limited resources is proposed and applied to the study area. The study shows that multiple flood vulnerability assessment can evaluate vulnerability more completely, and help decision makers learn more information about making decisions in a more comprehensive way. In summary, this study provides a new way for flood vulnerability assessment and disaster prevention decision. Copyright © 2018 Elsevier Ltd. All rights reserved.

A test for the parameters of multiple linear regression models ...

African Journals Online (AJOL)

A test for the parameters of multiple linear regression models is developed for conducting tests simultaneously on all the parameters of multiple linear regression models. The test is robust relative to the assumptions of homogeneity of variances and absence of serial correlation of the classical F-test. Under certain null and ...

Parametric modeling for damped sinusoids from multiple channels

DEFF Research Database (Denmark)

Zhou, Zhenhua; So, Hing Cheung; Christensen, Mads Græsbøll

2013-01-01

frequencies and damping factors are then computed with the multi-channel weighted linear prediction method. The estimated sinusoidal poles are then matched to each channel according to the extreme value theory of distribution of random fields. Simulations are performed to show the performance advantages......The problem of parametric modeling for noisy damped sinusoidal signals from multiple channels is addressed. Utilizing the shift invariance property of the signal subspace, the number of distinct sinusoidal poles in the multiple channels is first determined. With the estimated number, the distinct...... of the proposed multi-channel sinusoidal modeling methodology compared with existing methods....

A model for diagnosing and explaining multiple disorders.

Science.gov (United States)

Jamieson, P W

1991-08-01

The ability to diagnose multiple interacting disorders and explain them in a coherent causal framework has only partially been achieved in medical expert systems. This paper proposes a causal model for diagnosing and explaining multiple disorders whose key elements are: physician-directed hypotheses generation, object-oriented knowledge representation, and novel explanation heuristics. The heuristics modify and link the explanations to make the physician aware of diagnostic complexities. A computer program incorporating the model currently is in use for diagnosing peripheral nerve and muscle disorders. The program successfully diagnoses and explains interactions between diseases in terms of underlying pathophysiologic concepts. The model offers a new architecture for medical domains where reasoning from first principles is difficult but explanation of disease interactions is crucial for the system's operation.

Multilayer Stochastic Block Models Reveal the Multilayer Structure of Complex Networks

Directory of Open Access Journals (Sweden)

Toni Vallès-Català

2016-03-01

Full Text Available In complex systems, the network of interactions we observe between systems components is the aggregate of the interactions that occur through different mechanisms or layers. Recent studies reveal that the existence of multiple interaction layers can have a dramatic impact in the dynamical processes occurring on these systems. However, these studies assume that the interactions between systems components in each one of the layers are known, while typically for real-world systems we do not have that information. Here, we address the issue of uncovering the different interaction layers from aggregate data by introducing multilayer stochastic block models (SBMs, a generalization of single-layer SBMs that considers different mechanisms of layer aggregation. First, we find the complete probabilistic solution to the problem of finding the optimal multilayer SBM for a given aggregate-observed network. Because this solution is computationally intractable, we propose an approximation that enables us to verify that multilayer SBMs are more predictive of network structure in real-world complex systems.

Multiple spectroscopic analyses reveal the fate and metabolism of sulfamide herbicide triafamone in agricultural environments

International Nuclear Information System (INIS)

Wang, Mengcen; Qian, Yuan; Liu, Xiaoyu; Wei, Peng; Deng, Man; Wang, Lei; Wu, Huiming; Zhu, Guonian

2017-01-01

Triafamone, a sulfamide herbicide, has been extensively utilized for weed control in rice paddies in Asia. However, its fate and transformation in the environment have not been established. Through a rice paddy microcosm-based simulation trial combined with multiple spectroscopic analyses, we isolated and identified three novel metabolites of triafamone, including hydroxyl triafamone (HTA), hydroxyl triafamone glycoside (HTAG), and oxazolidinedione triafamone (OTA). When triafamone was applied to rice paddies at a concentration of 34.2 g active ingredient/ha, this was predominantly distributed in the paddy soil and water, and then rapidly dissipated in accordance with the first-order rate model, with half-lives of 4.3–11.0 days. As the main transformation pathway, triafamone was assimilated by the rice plants and was detoxified into HTAG, whereas the rest was reduced into HTA with subsequent formation of OTA. At the senescence stage, brown rice had incurred triafamone at a concentration of 0.0016 mg/kg, but the hazard quotient was <1, suggesting that long-term consumption of the triafamone-containing brown rice is relatively safe. The findings of the present study indicate that triafamone is actively metabolized in the agricultural environment, and elucidation of the link between environmental exposure to these triazine or oxazolidinedione moieties that contain metabolites and their potential impacts is warranted. - Highlights: • Multiple spectroscopic analyses were applied to investigate agrochemicals transformation in environment. • Three novel compounds were isolated and identified as triafamone metabolites. • The fate and transformation pathway of triafamone in rice paddy were revealed. • Long-term consumption of the triafamone-containing brown rice is relatively safe. • Elucidation of environmental impacts by exposure to these triazine or oxazolidinedione metabolites is warranted. - Triafamone rapidly dissipates in agricultural environments

Application of Multiple Evaluation Models in Brazil

Directory of Open Access Journals (Sweden)

Rafael Victal Saliba

2008-07-01

Full Text Available Based on two different samples, this article tests the performance of a number of Value Drivers commonly used for evaluating companies by finance practitioners, through simple regression models of cross-section type which estimate the parameters associated to each Value Driver, denominated Market Multiples. We are able to diagnose the behavior of several multiples in the period 1994-2004, with an outlook also on the particularities of the economic activities performed by the sample companies (and their impacts on the performance through a subsequent analysis with segregation of companies in the sample by sectors. Extrapolating simple multiples evaluation standards from analysts of the main financial institutions in Brazil, we find that adjusting the ratio formulation to allow for an intercept does not provide satisfactory results in terms of pricing errors reduction. Results found, in spite of evidencing certain relative and absolute superiority among the multiples, may not be generically representative, given samples limitation.

Deterministic integer multiple firing depending on initial state in Wang model

Energy Technology Data Exchange (ETDEWEB)

Xie Yong [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)]. E-mail: yxie@mail.xjtu.edu.cn; Xu Jianxue [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China); Jiang Jun [Institute of Nonlinear Dynamics, MSSV, Department of Engineering Mechanics, Xi' an Jiaotong University, Xi' an 710049 (China)

2006-12-15

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables.

Deterministic integer multiple firing depending on initial state in Wang model

International Nuclear Information System (INIS)

Xie Yong; Xu Jianxue; Jiang Jun

2006-01-01

We investigate numerically dynamical behaviour of the Wang model, which describes the rhythmic activities of thalamic relay neurons. The model neuron exhibits Type I excitability from a global view, but Type II excitability from a local view. There exists a narrow range of bistability, in which a subthreshold oscillation and a suprathreshold firing behaviour coexist. A special firing pattern, integer multiple firing can be found in the certain part of the bistable range. The characteristic feature of such firing pattern is that the histogram of interspike intervals has a multipeaked structure, and the peaks are located at about integer multiples of a basic interspike interval. Since the Wang model is noise-free, the integer multiple firing is a deterministic firing pattern. The existence of bistability leads to the deterministic integer multiple firing depending on the initial state of the model neuron, i.e., the initial values of the state variables

Multiple regression and beyond an introduction to multiple regression and structural equation modeling

CERN Document Server

Keith, Timothy Z

2014-01-01

Multiple Regression and Beyond offers a conceptually oriented introduction to multiple regression (MR) analysis and structural equation modeling (SEM), along with analyses that flow naturally from those methods. By focusing on the concepts and purposes of MR and related methods, rather than the derivation and calculation of formulae, this book introduces material to students more clearly, and in a less threatening way. In addition to illuminating content necessary for coursework, the accessibility of this approach means students are more likely to be able to conduct research using MR or SEM--and more likely to use the methods wisely. Covers both MR and SEM, while explaining their relevance to one another Also includes path analysis, confirmatory factor analysis, and latent growth modeling Figures and tables throughout provide examples and illustrate key concepts and techniques For additional resources, please visit: http://tzkeith.com/.

Comparison of Geant4 multiple Coulomb scattering models with theory for radiotherapy protons.

Science.gov (United States)

Makarova, Anastasia; Gottschalk, Bernard; Sauerwein, Wolfgang

2017-07-06

Usually, Monte Carlo models are validated against experimental data. However, models of multiple Coulomb scattering (MCS) in the Gaussian approximation are exceptional in that we have theories which are probably more accurate than the experiments which have, so far, been done to test them. In problems directly sensitive to the distribution of angles leaving the target, the relevant theory is the Molière/Fano/Hanson variant of Molière theory (Gottschalk et al 1993 Nucl. Instrum. Methods Phys. Res. B 74 467-90). For transverse spreading of the beam in the target itself, the theory of Preston and Koehler (Gottschalk (2012 arXiv:1204.4470)) holds. Therefore, in this paper we compare Geant4 simulations, using the Urban and Wentzel models of MCS, with theory rather than experiment, revealing trends which would otherwise be obscured by experimental scatter. For medium-energy (radiotherapy) protons, and low-Z (water-like) target materials, Wentzel appears to be better than Urban in simulating the distribution of outgoing angles. For beam spreading in the target itself, the two models are essentially equal.

New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Zeng, Tieyong

2013-01-01

A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

QSAR models for prediction study of HIV protease inhibitors using support vector machines, neural networks and multiple linear regression

Directory of Open Access Journals (Sweden)

Rachid Darnag

2017-02-01

Full Text Available Support vector machines (SVM represent one of the most promising Machine Learning (ML tools that can be applied to develop a predictive quantitative structure–activity relationship (QSAR models using molecular descriptors. Multiple linear regression (MLR and artificial neural networks (ANNs were also utilized to construct quantitative linear and non linear models to compare with the results obtained by SVM. The prediction results are in good agreement with the experimental value of HIV activity; also, the results reveal the superiority of the SVM over MLR and ANN model. The contribution of each descriptor to the structure–activity relationships was evaluated.

Systematic analysis of fly models with multiple drivers reveals different effects of ataxin-1 and huntingtin in neuron subtype-specific expression.

Directory of Open Access Journals (Sweden)

Risa Shiraishi

Full Text Available The fruit fly, Drosophila melanogaster, is a commonly used model organism for neurodegenerative diseases. Its major advantages include a short lifespan and its susceptibility to manipulation using sophisticated genetic techniques. Here, we report the systematic comparison of fly models of two polyglutamine (polyQ diseases. We induced expression of the normal and mutant forms of full-length Ataxin-1 and Huntingtin exon 1 in cholinergic, dopaminergic, and motor neurons, and glial cells using cell type-specific drivers. We systematically analyzed their effects based on multiple phenotypes: eclosion rate, lifespan, motor performance, and circadian rhythms of spontaneous activity. This systematic assay system enabled us to quantitatively evaluate and compare the functional disabilities of different genotypes. The results suggest different effects of Ataxin-1 and Huntingtin on specific types of neural cells during development and in adulthood. In addition, we confirmed the therapeutic effects of LiCl and butyrate using representative models. These results support the usefulness of this assay system for screening candidate chemical compounds that modify the pathologies of polyQ diseases.

A Bayesian Hierarchical Model for Relating Multiple SNPs within Multiple Genes to Disease Risk

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Lewei Duan

2013-01-01

Full Text Available A variety of methods have been proposed for studying the association of multiple genes thought to be involved in a common pathway for a particular disease. Here, we present an extension of a Bayesian hierarchical modeling strategy that allows for multiple SNPs within each gene, with external prior information at either the SNP or gene level. The model involves variable selection at the SNP level through latent indicator variables and Bayesian shrinkage at the gene level towards a prior mean vector and covariance matrix that depend on external information. The entire model is fitted using Markov chain Monte Carlo methods. Simulation studies show that the approach is capable of recovering many of the truly causal SNPs and genes, depending upon their frequency and size of their effects. The method is applied to data on 504 SNPs in 38 candidate genes involved in DNA damage response in the WECARE study of second breast cancers in relation to radiotherapy exposure.

Predictive performance models and multiple task performance

Science.gov (United States)

Wickens, Christopher D.; Larish, Inge; Contorer, Aaron

1989-01-01

Five models that predict how performance of multiple tasks will interact in complex task scenarios are discussed. The models are shown in terms of the assumptions they make about human operator divided attention. The different assumptions about attention are then empirically validated in a multitask helicopter flight simulation. It is concluded from this simulation that the most important assumption relates to the coding of demand level of different component tasks.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method.

Science.gov (United States)

Tuta, Jure; Juric, Matjaz B

2018-03-24

This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method), a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah) and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.). Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

MFAM: Multiple Frequency Adaptive Model-Based Indoor Localization Method

Directory of Open Access Journals (Sweden)

Jure Tuta

2018-03-01

Full Text Available This paper presents MFAM (Multiple Frequency Adaptive Model-based localization method, a novel model-based indoor localization method that is capable of using multiple wireless signal frequencies simultaneously. It utilizes indoor architectural model and physical properties of wireless signal propagation through objects and space. The motivation for developing multiple frequency localization method lies in the future Wi-Fi standards (e.g., 802.11ah and the growing number of various wireless signals present in the buildings (e.g., Wi-Fi, Bluetooth, ZigBee, etc.. Current indoor localization methods mostly rely on a single wireless signal type and often require many devices to achieve the necessary accuracy. MFAM utilizes multiple wireless signal types and improves the localization accuracy over the usage of a single frequency. It continuously monitors signal propagation through space and adapts the model according to the changes indoors. Using multiple signal sources lowers the required number of access points for a specific signal type while utilizing signals, already present in the indoors. Due to the unavailability of the 802.11ah hardware, we have evaluated proposed method with similar signals; we have used 2.4 GHz Wi-Fi and 868 MHz HomeMatic home automation signals. We have performed the evaluation in a modern two-bedroom apartment and measured mean localization error 2.0 to 2.3 m and median error of 2.0 to 2.2 m. Based on our evaluation results, using two different signals improves the localization accuracy by 18% in comparison to 2.4 GHz Wi-Fi-only approach. Additional signals would improve the accuracy even further. We have shown that MFAM provides better accuracy than competing methods, while having several advantages for real-world usage.

Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

KAUST Repository

Li, Muxingzi

2017-01-01

of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

Directory of Open Access Journals (Sweden)

Wasis Wasis

2013-01-01

Full Text Available Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons peserta tes diskor dengan tiga model partial credit (PCM I; II; dan III dan secara dikotomus. Hasil penskoran dianalisis dengan program Quest untuk mendapat-kan estimasi tingkat kesukaran butir (δ dan estimasi ke-mampuan peserta (θ untuk menentukan nilai fungsi informasi tes dan kesalahan baku estimasi. Penelitian simulasi mengguna-kan data bangkitan berdasarkan parameter empiris (δ dan θ memakai program statistik SAS dan akurasi estimasinya di-analisis dengan metode root mean squared error (RMSE. Hasil penelitian ini menunjukkan: (i Penskoran PCM dengan pem-bobotan mampu mengestimasi kemampuan lebih akurat di-bandingkan tanpa pembobotan maupun secara dikotomus; (ii Semakin banyak jumlah kategori dalam penskoran partial credit, semakin akurat. Kata kunci: model penskoran partial credit, butir multiple true-false ____________________________________________________________ THE PARTIAL CREDIT SCORING MODEL FOR THE MULTIPLE TRUE-FALSE BUTIRS IN PHYSICS Abstract This study is an attempt to overcome the weaknesses. This study aims to produce a polytomous scoring model for responses to multiple true-false butirs in order to get a more accurate estimation of abilities in physics. It adopts the Four-D model and its accuracy is assessed through empirical and simulation studies. The empirical study employed 15 multiple true-false butirs taken from the New Students Entrance Test of State University the year of 1996–2006. It administered to 410 new students enrolled

A collaborative scheduling model for the supply-hub with multiple suppliers and multiple manufacturers.

Science.gov (United States)

Li, Guo; Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Technique of Fuzzy C-Mean in Multiple Linear Regression Model toward Paddy Yield

Science.gov (United States)

Syazwan Wahab, Nur; Saifullah Rusiman, Mohd; Mohamad, Mahathir; Amira Azmi, Nur; Che Him, Norziha; Ghazali Kamardan, M.; Ali, Maselan

2018-04-01

In this paper, we propose a hybrid model which is a combination of multiple linear regression model and fuzzy c-means method. This research involved a relationship between 20 variates of the top soil that are analyzed prior to planting of paddy yields at standard fertilizer rates. Data used were from the multi-location trials for rice carried out by MARDI at major paddy granary in Peninsular Malaysia during the period from 2009 to 2012. Missing observations were estimated using mean estimation techniques. The data were analyzed using multiple linear regression model and a combination of multiple linear regression model and fuzzy c-means method. Analysis of normality and multicollinearity indicate that the data is normally scattered without multicollinearity among independent variables. Analysis of fuzzy c-means cluster the yield of paddy into two clusters before the multiple linear regression model can be used. The comparison between two method indicate that the hybrid of multiple linear regression model and fuzzy c-means method outperform the multiple linear regression model with lower value of mean square error.

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

Infinite Multiple Membership Relational Modeling for Complex Networks

DEFF Research Database (Denmark)

Mørup, Morten; Schmidt, Mikkel Nørgaard; Hansen, Lars Kai

Learning latent structure in complex networks has become an important problem fueled by many types of networked data originating from practically all fields of science. In this paper, we propose a new non-parametric Bayesian multiplemembership latent feature model for networks. Contrary to existing...... multiplemembership models that scale quadratically in the number of vertices the proposedmodel scales linearly in the number of links admittingmultiple-membership analysis in large scale networks. We demonstrate a connection between the single membership relational model and multiple membership models and show...

Proteomic profiling in multiple sclerosis clinical courses reveals potential biomarkers of neurodegeneration.

Directory of Open Access Journals (Sweden)

Maria Liguori

Full Text Available The aim of our project was to perform an exploratory analysis of the cerebrospinal fluid (CSF proteomic profiles of Multiple Sclerosis (MS patients, collected in different phases of their clinical course, in order to investigate the existence of peculiar profiles characterizing the different MS phenotypes. The study was carried out on 24 Clinically Isolated Syndrome (CIS, 16 Relapsing Remitting (RR MS, 11 Progressive (Pr MS patients. The CSF samples were analysed using the Matrix Assisted Laser Desorption Ionisation Time Of Flight (MALDI-TOF mass spectrometer in linear mode geometry and in delayed extraction mode (m/z range: 1000-25000 Da. Peak lists were imported for normalization and statistical analysis. CSF data were correlated with demographic, clinical and MRI parameters. The evaluation of MALDI-TOF spectra revealed 348 peak signals with relative intensity ≥ 1% in the study range. The peak intensity of the signals corresponding to Secretogranin II and Protein 7B2 were significantly upregulated in RRMS patients compared to PrMS (p<0.05, whereas the signals of Fibrinogen and Fibrinopeptide A were significantly downregulated in CIS compared to PrMS patients (p<0.04. Additionally, the intensity of the Tymosin β4 peak was the only signal to be significantly discriminated between the CIS and RRMS patients (p = 0.013. Although with caution due to the relatively small size of the study populations, and considering that not all the findings remained significant after adjustment for multiple comparisons, in our opinion this mass spectrometry evaluation confirms that this technique may provide useful and important information to improve our understanding of the complex pathogenesis of MS.

Optimization of the Darrieus wind turbines with double-multiple-streamtube model

International Nuclear Information System (INIS)

Paraschivoiu, I.

1985-01-01

This paper discusses a new improvement of the double-multiple-stream tube model by considering the stream tube expansion effects on the Darrieus wind turbine. These effects, allowing a more realistic modeling of the upwind/downwind flow field asymmetries inherent in the Darrieus rotor, were calculated by using CARDAAX computer code. When the dynamic stall is introduced in the double-multiple-stream tube model, the aerodynamic loads and performance show significant changes in the range of low tip-speed ratio

Structural model analysis of multiple quantitative traits.

Directory of Open Access Journals (Sweden)

Renhua Li

2006-07-01

Full Text Available We introduce a method for the analysis of multilocus, multitrait genetic data that provides an intuitive and precise characterization of genetic architecture. We show that it is possible to infer the magnitude and direction of causal relationships among multiple correlated phenotypes and illustrate the technique using body composition and bone density data from mouse intercross populations. Using these techniques we are able to distinguish genetic loci that affect adiposity from those that affect overall body size and thus reveal a shortcoming of standardized measures such as body mass index that are widely used in obesity research. The identification of causal networks sheds light on the nature of genetic heterogeneity and pleiotropy in complex genetic systems.

Application of multiple objective models to water resources planning and management

International Nuclear Information System (INIS)

North, R.M.

1993-01-01

Over the past 30 years, we have seen the birth and growth of multiple objective analysis from an idea without tools to one with useful applications. Models have been developed and applications have been researched to address the multiple purposes and objectives inherent in the development and management of water resources. A practical approach to multiple objective modelling incorporates macroeconomic-based policies and expectations in order to optimize the results from both engineering (structural) and management (non-structural) alternatives, while taking into account the economic and environmental trade-offs. (author). 27 refs, 4 figs, 3 tabs

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Directory of Open Access Journals (Sweden)

Guo Li

2014-01-01

Full Text Available This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment.

A Collaborative Scheduling Model for the Supply-Hub with Multiple Suppliers and Multiple Manufacturers

Science.gov (United States)

Lv, Fei; Guan, Xu

2014-01-01

This paper investigates a collaborative scheduling model in the assembly system, wherein multiple suppliers have to deliver their components to the multiple manufacturers under the operation of Supply-Hub. We first develop two different scenarios to examine the impact of Supply-Hub. One is that suppliers and manufacturers make their decisions separately, and the other is that the Supply-Hub makes joint decisions with collaborative scheduling. The results show that our scheduling model with the Supply-Hub is a NP-complete problem, therefore, we propose an auto-adapted differential evolution algorithm to solve this problem. Moreover, we illustrate that the performance of collaborative scheduling by the Supply-Hub is superior to separate decision made by each manufacturer and supplier. Furthermore, we also show that the algorithm proposed has good convergence and reliability, which can be applicable to more complicated supply chain environment. PMID:24892104

Multiple Time Series Ising Model for Financial Market Simulations

International Nuclear Information System (INIS)

Takaishi, Tetsuya

2015-01-01

In this paper we propose an Ising model which simulates multiple financial time series. Our model introduces the interaction which couples to spins of other systems. Simulations from our model show that time series exhibit the volatility clustering that is often observed in the real financial markets. Furthermore we also find non-zero cross correlations between the volatilities from our model. Thus our model can simulate stock markets where volatilities of stocks are mutually correlated

Multi-physics modeling of single/multiple-track defect mechanisms in electron beam selective melting

International Nuclear Information System (INIS)

Yan, Wentao; Ge, Wenjun; Qian, Ya; Lin, Stephen; Zhou, Bin; Liu, Wing Kam; Lin, Feng; Wagner, Gregory J.

2017-01-01

Metallic powder bed-based additive manufacturing technologies have many promising attributes. The single track acts as one fundamental building unit, which largely influences the final product quality such as the surface roughness and dimensional accuracy. A high-fidelity powder-scale model is developed to predict the detailed formation processes of single/multiple-track defects, including the balling effect, single track nonuniformity and inter-track voids. These processes are difficult to observe in experiments; previous studies have proposed different or even conflicting explanations. Our study clarifies the underlying formation mechanisms, reveals the influence of key factors, and guides the improvement of fabrication quality of single tracks. Additionally, the manufacturing processes of multiple tracks along S/Z-shaped scan paths with various hatching distance are simulated to further understand the defects in complex structures. The simulations demonstrate that the hatching distance should be no larger than the width of the remelted region within the substrate rather than the width of the melted region within the powder layer. Thus, single track simulations can provide valuable insight for complex structures.

Bayesian inference based modelling for gene transcriptional dynamics by integrating multiple source of knowledge

Directory of Open Access Journals (Sweden)

Wang Shu-Qiang

2012-07-01

Full Text Available Abstract Background A key challenge in the post genome era is to identify genome-wide transcriptional regulatory networks, which specify the interactions between transcription factors and their target genes. Numerous methods have been developed for reconstructing gene regulatory networks from expression data. However, most of them are based on coarse grained qualitative models, and cannot provide a quantitative view of regulatory systems. Results A binding affinity based regulatory model is proposed to quantify the transcriptional regulatory network. Multiple quantities, including binding affinity and the activity level of transcription factor (TF are incorporated into a general learning model. The sequence features of the promoter and the possible occupancy of nucleosomes are exploited to estimate the binding probability of regulators. Comparing with the previous models that only employ microarray data, the proposed model can bridge the gap between the relative background frequency of the observed nucleotide and the gene's transcription rate. Conclusions We testify the proposed approach on two real-world microarray datasets. Experimental results show that the proposed model can effectively identify the parameters and the activity level of TF. Moreover, the kinetic parameters introduced in the proposed model can reveal more biological sense than previous models can do.

Alternative approaches to reliability modeling of a multiple engineered barrier system

International Nuclear Information System (INIS)

Ananda, M.M.A.; Singh, A.K.

1994-01-01

The lifetime of the engineered barrier system used for containment of high-level radioactive waste will significantly impact the total performance of a geological repository facility. Currently two types of designs are under consideration for an engineered barrier system, single engineered barrier system and multiple engineered barrier system. Multiple engineered barrier system consists of several metal barriers and the waste form (cladding). Some recent work show that a significant improvement of performance can be achieved by utilizing multiple engineered barrier systems. Considering sequential failures for each barrier, we model the reliability of the multiple engineered barrier system. Weibull and exponential lifetime distributions are used through out the analysis. Furthermore, the number of failed engineered barrier systems in a repository at a given time is modeled using a poisson approximation

Feedback structure based entropy approach for multiple-model estimation

Institute of Scientific and Technical Information of China (English)

Shen-tu Han; Xue Anke; Guo Yunfei

2013-01-01

The variable-structure multiple-model (VSMM) approach, one of the multiple-model (MM) methods, is a popular and effective approach in handling problems with mode uncertainties. The model sequence set adaptation (MSA) is the key to design a better VSMM. However, MSA methods in the literature have big room to improve both theoretically and practically. To this end, we propose a feedback structure based entropy approach that could find the model sequence sets with the smallest size under certain conditions. The filtered data are fed back in real time and can be used by the minimum entropy (ME) based VSMM algorithms, i.e., MEVSMM. Firstly, the full Markov chains are used to achieve optimal solutions. Secondly, the myopic method together with particle filter (PF) and the challenge match algorithm are also used to achieve sub-optimal solutions, a trade-off between practicability and optimality. The numerical results show that the proposed algorithm provides not only refined model sets but also a good robustness margin and very high accuracy.

A PDP model of the simultaneous perception of multiple objects

Science.gov (United States)

Henderson, Cynthia M.; McClelland, James L.

2011-06-01

Illusory conjunctions in normal and simultanagnosic subjects are two instances where the visual features of multiple objects are incorrectly 'bound' together. A connectionist model explores how multiple objects could be perceived correctly in normal subjects given sufficient time, but could give rise to illusory conjunctions with damage or time pressure. In this model, perception of two objects benefits from lateral connections between hidden layers modelling aspects of the ventral and dorsal visual pathways. As with simultanagnosia, simulations of dorsal lesions impair multi-object recognition. In contrast, a large ventral lesion has minimal effect on dorsal functioning, akin to dissociations between simple object manipulation (retained in visual form agnosia and semantic dementia) and object discrimination (impaired in these disorders) [Hodges, J.R., Bozeat, S., Lambon Ralph, M.A., Patterson, K., and Spatt, J. (2000), 'The Role of Conceptual Knowledge: Evidence from Semantic Dementia', Brain, 123, 1913-1925; Milner, A.D., and Goodale, M.A. (2006), The Visual Brain in Action (2nd ed.), New York: Oxford]. It is hoped that the functioning of this model might suggest potential processes underlying dorsal and ventral contributions to the correct perception of multiple objects.

MODEL PENSKORAN PARTIAL CREDIT PADA BUTIR MULTIPLE TRUE-FALSE BIDANG FISIKA

OpenAIRE

Wasis Wasis

2013-01-01

Tujuan penelitian ini menghasilkan model penskoran politomus untuk respons butir multiple true-false, sehingga dapat mengestimasi secara lebih akurat kemampuan di bidang fisika. Pengembangan penskoran menggunakan Four-D model dan diuji akurasinya melalui penelitian empiris dan simulasi. Penelitian empiris menggunakan 15 butir multiple true-false yang diambil dari soal UMPTN tahun 1996-2006 dan dikenakan pada 410 mahasiswa baru FMIPA Universitas Negeri Surabaya angkatan tahun 2007. Respons pes...

Hybrid approaches for multiple-species stochastic reaction–diffusion models

International Nuclear Information System (INIS)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-01-01

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries

Hybrid approaches for multiple-species stochastic reaction–diffusion models

Energy Technology Data Exchange (ETDEWEB)

Spill, Fabian, E-mail: fspill@bu.edu [Department of Biomedical Engineering, Boston University, 44 Cummington Street, Boston, MA 02215 (United States); Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139 (United States); Guerrero, Pilar [Department of Mathematics, University College London, Gower Street, London WC1E 6BT (United Kingdom); Alarcon, Tomas [Centre de Recerca Matematica, Campus de Bellaterra, Edifici C, 08193 Bellaterra (Barcelona) (Spain); Departament de Matemàtiques, Universitat Atonòma de Barcelona, 08193 Bellaterra (Barcelona) (Spain); Maini, Philip K. [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Byrne, Helen [Wolfson Centre for Mathematical Biology, Mathematical Institute, University of Oxford, Oxford OX2 6GG (United Kingdom); Computational Biology Group, Department of Computer Science, University of Oxford, Oxford OX1 3QD (United Kingdom)

2015-10-15

Reaction–diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction–diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model. - Highlights: • A novel hybrid stochastic/deterministic reaction–diffusion simulation method is given. • Can massively speed up stochastic simulations while preserving stochastic effects. • Can handle multiple reacting species. • Can handle moving boundaries.

Modeling a Single SEP Event from Multiple Vantage Points Using the iPATH Model

Science.gov (United States)

Hu, Junxiang; Li, Gang; Fu, Shuai; Zank, Gary; Ao, Xianzhi

2018-02-01

Using the recently extended 2D improved Particle Acceleration and Transport in the Heliosphere (iPATH) model, we model an example gradual solar energetic particle event as observed at multiple locations. Protons and ions that are energized via the diffusive shock acceleration mechanism are followed at a 2D coronal mass ejection-driven shock where the shock geometry varies across the shock front. The subsequent transport of energetic particles, including cross-field diffusion, is modeled by a Monte Carlo code that is based on a stochastic differential equation method. Time intensity profiles and particle spectra at multiple locations and different radial distances, separated in longitudes, are presented. The results shown here are relevant to the upcoming Parker Solar Probe mission.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

Science.gov (United States)

Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

2015-01-01

Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

Green communication: The enabler to multiple business models

DEFF Research Database (Denmark)

Lindgren, Peter; Clemmensen, Suberia; Taran, Yariv

2010-01-01

Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...... possibility to enable lower energy consumption. This paper shows how green communication enables innovation of green business models and multiple business models running simultaneously in different markets to different customers.......Companies stand at the forefront of a new business model reality with new potentials - that will change their basic understanding and practice of running their business models radically. One of the drivers to this change is green communication, its strong relation to green business models and its...

Multiple linear regression and regression with time series error models in forecasting PM10 concentrations in Peninsular Malaysia.

Science.gov (United States)

Ng, Kar Yong; Awang, Norhashidah

2018-01-06

Frequent haze occurrences in Malaysia have made the management of PM 10 (particulate matter with aerodynamic less than 10 μm) pollution a critical task. This requires knowledge on factors associating with PM 10 variation and good forecast of PM 10 concentrations. Hence, this paper demonstrates the prediction of 1-day-ahead daily average PM 10 concentrations based on predictor variables including meteorological parameters and gaseous pollutants. Three different models were built. They were multiple linear regression (MLR) model with lagged predictor variables (MLR1), MLR model with lagged predictor variables and PM 10 concentrations (MLR2) and regression with time series error (RTSE) model. The findings revealed that humidity, temperature, wind speed, wind direction, carbon monoxide and ozone were the main factors explaining the PM 10 variation in Peninsular Malaysia. Comparison among the three models showed that MLR2 model was on a same level with RTSE model in terms of forecasting accuracy, while MLR1 model was the worst.

Mathematics revealed

CERN Document Server

Berman, Elizabeth

1979-01-01

Mathematics Revealed focuses on the principles, processes, operations, and exercises in mathematics.The book first offers information on whole numbers, fractions, and decimals and percents. Discussions focus on measuring length, percent, decimals, numbers as products, addition and subtraction of fractions, mixed numbers and ratios, division of fractions, addition, subtraction, multiplication, and division. The text then examines positive and negative numbers and powers and computation. Topics include division and averages, multiplication, ratios, and measurements, scientific notation and estim

An extension of the multiple-trapping model

International Nuclear Information System (INIS)

Shkilev, V. P.

2012-01-01

The hopping charge transport in disordered semiconductors is considered. Using the concept of the transport energy level, macroscopic equations are derived that extend a multiple-trapping model to the case of semiconductors with both energy and spatial disorders. It is shown that, although both types of disorder can cause dispersive transport, the frequency dependence of conductivity is determined exclusively by the spatial disorder.

A Multiple Model Prediction Algorithm for CNC Machine Wear PHM

Directory of Open Access Journals (Sweden)

Huimin Chen

2011-01-01

Full Text Available The 2010 PHM data challenge focuses on the remaining useful life (RUL estimation for cutters of a high speed CNC milling machine using measurements from dynamometer, accelerometer, and acoustic emission sensors. We present a multiple model approach for wear depth estimation of milling machine cutters using the provided data. The feature selection, initial wear estimation and multiple model fusion components of the proposed algorithm are explained in details and compared with several alternative methods using the training data. The final submission ranked #2 among professional and student participants and the method is applicable to other data driven PHM problems.

Estimation of causal mediation effects for a dichotomous outcome in multiple-mediator models using the mediation formula.

Science.gov (United States)

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M

2013-10-30

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a nonzero total mediation effect increases as the correlation coefficient between two mediators increases, whereas power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. Copyright © 2013 John Wiley & Sons, Ltd.

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

Science.gov (United States)

Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets of mediators using the potential outcomes framework. We formulate a model of joint distribution (probit-normal) using continuous latent variables for any binary mediators to account for correlations among multiple mediators. A mediation formula approach is proposed to estimate the total mediation effect and decomposed mediation effects based on this parametric model. Estimation of mediation effects through individual or subsets of mediators requires an assumption involving the joint distribution of multiple counterfactuals. We conduct a simulation study that demonstrates low bias of mediation effect estimators for two-mediator models with various combinations of mediator types. The results also show that the power to detect a non-zero total mediation effect increases as the correlation coefficient between two mediators increases, while power for individual mediation effects reaches a maximum when the mediators are uncorrelated. We illustrate our approach by applying it to a retrospective cohort study of dental caries in adolescents with low and high socioeconomic status. Sensitivity analysis is performed to assess the robustness of conclusions regarding mediation effects when the assumption of no unmeasured mediator-outcome confounders is violated. PMID:23650048

Selecting Tools to Model Integer and Binomial Multiplication

Science.gov (United States)

Pratt, Sarah Smitherman; Eddy, Colleen M.

2017-01-01

Mathematics teachers frequently provide concrete manipulatives to students during instruction; however, the rationale for using certain manipulatives in conjunction with concepts may not be explored. This article focuses on area models that are currently used in classrooms to provide concrete examples of integer and binomial multiplication. The…

Comparative study between a QCD inspired model and a multiple diffraction model

International Nuclear Information System (INIS)

Luna, E.G.S.; Martini, A.F.; Menon, M.J.

2003-01-01

A comparative study between a QCD Inspired Model (QCDIM) and a Multiple Diffraction Model (MDM) is presented, with focus on the results for pp differential cross section at √s = 52.8 GeV. It is shown that the MDM predictions are in agreement with experimental data, except for the dip region and that the QCDIM describes only the diffraction peak region. Interpretations in terms of the corresponding eikonals are also discussed. (author)

A Simple Exercise Reveals the Way Students Think about Scientific Modeling

Science.gov (United States)

Ruebush, Laura; Sulikowski, Michelle; North, Simon

2009-01-01

Scientific modeling is an integral part of contemporary science, yet many students have little understanding of how models are developed, validated, and used to predict and explain phenomena. A simple modeling exercise led to significant gains in understanding key attributes of scientific modeling while revealing some stubborn misconceptions.…

Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

Directory of Open Access Journals (Sweden)

Song-Gui Chen

2016-01-01

Full Text Available This paper presents a three-dimensional (3D parallel multiple-relaxation-time lattice Boltzmann model (MRT-LBM for Bingham plastics which overcomes numerical instabilities in the simulation of non-Newtonian fluids for the Bhatnagar–Gross–Krook (BGK model. The MRT-LBM and several related mathematical models are briefly described. Papanastasiou’s modified model is incorporated for better numerical stability. The impact of the relaxation parameters of the model is studied in detail. The MRT-LBM is then validated through a benchmark problem: a 3D steady Poiseuille flow. The results from the numerical simulations are consistent with those derived analytically which indicates that the MRT-LBM effectively simulates Bingham fluids but with better stability. A parallel MRT-LBM framework is introduced, and the parallel efficiency is tested through a simple case. The MRT-LBM is shown to be appropriate for parallel implementation and to have high efficiency. Finally, a Bingham fluid flowing past a square-based prism with a fixed sphere is simulated. It is found the drag coefficient is a function of both Reynolds number (Re and Bingham number (Bn. These results reveal the flow behavior of Bingham plastics.

Towards Integration of CAx Systems and a Multiple-View Product Modeller in Mechanical Design

Directory of Open Access Journals (Sweden)

H. Song

2005-01-01

Full Text Available This paper deals with the development of an integration framework and its implementation for the connexion of CAx systems and multiple-view product modelling. The integration framework is presented regarding its conceptual level and the implementation level is described currently with the connexion of a functional modeller, a multiple-view product modeller, an optimisation module and a CAD system. The integration between the multiple-view product modeller and CATIA V5 based on the STEP standard is described in detail. Finally, the presented works are discussed and future research developments are suggested. 

Optimized production planning model for a multi-plant cultivation system under uncertainty

Science.gov (United States)

Ke, Shunkui; Guo, Doudou; Niu, Qingliang; Huang, Danfeng

2015-02-01

An inexact multi-constraint programming model under uncertainty was developed by incorporating a production plan algorithm into the crop production optimization framework under the multi-plant collaborative cultivation system. In the production plan, orders from the customers are assigned to a suitable plant under the constraints of plant capabilities and uncertainty parameters to maximize profit and achieve customer satisfaction. The developed model and solution method were applied to a case study of a multi-plant collaborative cultivation system to verify its applicability. As determined in the case analysis involving different orders from customers, the period of plant production planning and the interval between orders can significantly affect system benefits. Through the analysis of uncertain parameters, reliable and practical decisions can be generated using the suggested model of a multi-plant collaborative cultivation system.

Evolutionary Dynamics of Tumor-Stroma Interactions in Multiple Myeloma.

Directory of Open Access Journals (Sweden)

Javad Salimi Sartakhti

Full Text Available Cancer cells and stromal cells cooperate by exchanging diffusible factors that sustain tumor growth, a form of frequency-dependent selection that can be studied in the framework of evolutionary game theory. In the case of multiple myeloma, three types of cells (malignant plasma cells, osteoblasts and osteoclasts exchange growth factors with different effects, and tumor-stroma interactions have been analysed using a model of cooperation with pairwise interactions. Here we show that a model in which growth factors have autocrine and paracrine effects on multiple cells, a more realistic assumption for tumor-stroma interactions, leads to different results, with implications for disease progression and treatment. In particular, the model reveals that reducing the number of malignant plasma cells below a critical threshold can lead to their extinction and thus to restore a healthy balance between osteoclast and osteoblast, a result in line with current therapies against multiple myeloma.

Risk score modeling of multiple gene to gene interactions using aggregated-multifactor dimensionality reduction

Directory of Open Access Journals (Sweden)

Dai Hongying

2013-01-01

Full Text Available Abstract Background Multifactor Dimensionality Reduction (MDR has been widely applied to detect gene-gene (GxG interactions associated with complex diseases. Existing MDR methods summarize disease risk by a dichotomous predisposing model (high-risk/low-risk from one optimal GxG interaction, which does not take the accumulated effects from multiple GxG interactions into account. Results We propose an Aggregated-Multifactor Dimensionality Reduction (A-MDR method that exhaustively searches for and detects significant GxG interactions to generate an epistasis enriched gene network. An aggregated epistasis enriched risk score, which takes into account multiple GxG interactions simultaneously, replaces the dichotomous predisposing risk variable and provides higher resolution in the quantification of disease susceptibility. We evaluate this new A-MDR approach in a broad range of simulations. Also, we present the results of an application of the A-MDR method to a data set derived from Juvenile Idiopathic Arthritis patients treated with methotrexate (MTX that revealed several GxG interactions in the folate pathway that were associated with treatment response. The epistasis enriched risk score that pooled information from 82 significant GxG interactions distinguished MTX responders from non-responders with 82% accuracy. Conclusions The proposed A-MDR is innovative in the MDR framework to investigate aggregated effects among GxG interactions. New measures (pOR, pRR and pChi are proposed to detect multiple GxG interactions.

Application of neural networks to multiple alarm processing and diagnosis in nuclear power plants

International Nuclear Information System (INIS)

Cheon, Se Woo; Chang Soon Heung; Chung, Hak Yeong

1992-01-01

This paper presents feasibility studies of multiple alarm processing and diagnosis using neural networks. The back-propagation neural network model is applied to the training of multiple alarm patterns for the identification of failure in a reactor coolant pump (RCP) system. The general mapping capability of the neural network enables to identify a fault easily. The case studies are performed with emphasis on the applicability of the neural network to pattern recognition problems. It is revealed that the neural network model can identify the cause of multiple alarms properly, even when untrained or sensor-failed alarm symptoms are given. It is also shown that multiple failures are easily identified using the symptoms of multiple alarms

Multiple Imputation of Predictor Variables Using Generalized Additive Models

NARCIS (Netherlands)

de Jong, Roel; van Buuren, Stef; Spiess, Martin

2016-01-01

The sensitivity of multiple imputation methods to deviations from their distributional assumptions is investigated using simulations, where the parameters of scientific interest are the coefficients of a linear regression model, and values in predictor variables are missing at random. The

Model Seleksi Premi Asuransi Jiwa Dwiguna untuk Kasus Multiple Decrement

OpenAIRE

Cita, Devi Ramana; Pane, Rolan; ', Harison

2015-01-01

This article discusses a select survival model for the case of multiple decrements in evaluating endowment life insurance premium for person currently aged ( + ) years, who is selected at age with ℎ years selection period. The case of multiple decrements in this case is limited to two cases. The calculation of the annual premium is done by prior evaluating of the single premium, and the present value of annuity depends on theconstant force assumption.

Application of Soft Computing Techniques and Multiple Regression Models for CBR prediction of Soils

Directory of Open Access Journals (Sweden)

Fatimah Khaleel Ibrahim

2017-08-01

Full Text Available The techniques of soft computing technique such as Artificial Neutral Network (ANN have improved the predicting capability and have actually discovered application in Geotechnical engineering. The aim of this research is to utilize the soft computing technique and Multiple Regression Models (MLR for forecasting the California bearing ratio CBR( of soil from its index properties. The indicator of CBR for soil could be predicted from various soils characterizing parameters with the assist of MLR and ANN methods. The data base that collected from the laboratory by conducting tests on 86 soil samples that gathered from different projects in Basrah districts. Data gained from the experimental result were used in the regression models and soft computing techniques by using artificial neural network. The liquid limit, plastic index , modified compaction test and the CBR test have been determined. In this work, different ANN and MLR models were formulated with the different collection of inputs to be able to recognize their significance in the prediction of CBR. The strengths of the models that were developed been examined in terms of regression coefficient (R2, relative error (RE% and mean square error (MSE values. From the results of this paper, it absolutely was noticed that all the proposed ANN models perform better than that of MLR model. In a specific ANN model with all input parameters reveals better outcomes than other ANN models.

A multiple shock model for common cause failures using discrete Markov chain

International Nuclear Information System (INIS)

Chung, Dae Wook; Kang, Chang Soon

1992-01-01

The most widely used models in common cause analysis are (single) shock models such as the BFR, and the MFR. But, single shock model can not treat the individual common cause separately and has some irrational assumptions. Multiple shock model for common cause failures is developed using Markov chain theory. This model treats each common cause shock as separately and sequently occuring event to implicate the change in failure probability distribution due to each common cause shock. The final failure probability distribution is evaluated and compared with that from the BFR model. The results show that multiple shock model which minimizes the assumptions in the BFR model is more realistic and conservative than the BFR model. The further work for application is the estimations of parameters such as common cause shock rate and component failure probability given a shock,p, through the data analysis

The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

Science.gov (United States)

Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

2014-01-01

In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

Protein structure modeling for CASP10 by multiple layers of global optimization.

Science.gov (United States)

Joo, Keehyoung; Lee, Juyong; Sim, Sangjin; Lee, Sun Young; Lee, Kiho; Heo, Seungryong; Lee, In-Ho; Lee, Sung Jong; Lee, Jooyoung

2014-02-01

In the template-based modeling (TBM) category of CASP10 experiment, we introduced a new protocol called protein modeling system (PMS) to generate accurate protein structures in terms of side-chains as well as backbone trace. In the new protocol, a global optimization algorithm, called conformational space annealing (CSA), is applied to the three layers of TBM procedure: multiple sequence-structure alignment, 3D chain building, and side-chain re-modeling. For 3D chain building, we developed a new energy function which includes new distance restraint terms of Lorentzian type (derived from multiple templates), and new energy terms that combine (physical) energy terms such as dynamic fragment assembly (DFA) energy, DFIRE statistical potential energy, hydrogen bonding term, etc. These physical energy terms are expected to guide the structure modeling especially for loop regions where no template structures are available. In addition, we developed a new quality assessment method based on random forest machine learning algorithm to screen templates, multiple alignments, and final models. For TBM targets of CASP10, we find that, due to the combination of three stages of CSA global optimizations and quality assessment, the modeling accuracy of PMS improves at each additional stage of the protocol. It is especially noteworthy that the side-chains of the final PMS models are far more accurate than the models in the intermediate steps. Copyright © 2013 Wiley Periodicals, Inc.

Interacting Multiple Model (IMM Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking

Directory of Open Access Journals (Sweden)

Hua Liu

2017-06-01

Full Text Available For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF. The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF, the interacting multiple model cubature Kalman filter (IMMCKF and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF.

Interacting Multiple Model (IMM) Fifth-Degree Spherical Simplex-Radial Cubature Kalman Filter for Maneuvering Target Tracking.

Science.gov (United States)

Liu, Hua; Wu, Wen

2017-06-13

For improving the tracking accuracy and model switching speed of maneuvering target tracking in nonlinear systems, a new algorithm named the interacting multiple model fifth-degree spherical simplex-radial cubature Kalman filter (IMM5thSSRCKF) is proposed in this paper. The new algorithm is a combination of the interacting multiple model (IMM) filter and the fifth-degree spherical simplex-radial cubature Kalman filter (5thSSRCKF). The proposed algorithm makes use of Markov process to describe the switching probability among the models, and uses 5thSSRCKF to deal with the state estimation of each model. The 5thSSRCKF is an improved filter algorithm, which utilizes the fifth-degree spherical simplex-radial rule to improve the filtering accuracy. Finally, the tracking performance of the IMM5thSSRCKF is evaluated by simulation in a typical maneuvering target tracking scenario. Simulation results show that the proposed algorithm has better tracking performance and quicker model switching speed when disposing maneuver models compared with the interacting multiple model unscented Kalman filter (IMMUKF), the interacting multiple model cubature Kalman filter (IMMCKF) and the interacting multiple model fifth-degree cubature Kalman filter (IMM5thCKF).

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

Science.gov (United States)

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Linear systems with unstructured multiplicative uncertainty: Modeling and robust stability analysis.

Directory of Open Access Journals (Sweden)

Radek Matušů

Full Text Available This article deals with continuous-time Linear Time-Invariant (LTI Single-Input Single-Output (SISO systems affected by unstructured multiplicative uncertainty. More specifically, its aim is to present an approach to the construction of uncertain models based on the appropriate selection of a nominal system and a weight function and to apply the fundamentals of robust stability investigation for considered sort of systems. The initial theoretical parts are followed by three extensive illustrative examples in which the first order time-delay, second order and third order plants with parametric uncertainty are modeled as systems with unstructured multiplicative uncertainty and subsequently, the robust stability of selected feedback loops containing constructed models and chosen controllers is analyzed and obtained results are discussed.

Degrees of Cooperation in Household Consumption Models : A Revealed Preference Analysis

NARCIS (Netherlands)

Cherchye, L.J.H.; Demuynck, T.; de Rock, B.

2009-01-01

We develop a revealed preference approach to analyze non-unitary con- sumption models with intrahousehold allocations deviating from the cooper- ative (or Pareto e¢ cient) solution. At a theoretical level, we establish re- vealed preference conditions of household consumption models with varying

A latent class multiple constraint multiple discrete-continuous extreme value model of time use and goods consumption.

Science.gov (United States)

2016-06-01

This paper develops a microeconomic theory-based multiple discrete continuous choice model that considers: (a) that both goods consumption and time allocations (to work and non-work activities) enter separately as decision variables in the utility fu...

Hybrid approaches for multiple-species stochastic reaction-diffusion models

Science.gov (United States)

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K.; Byrne, Helen

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian; Guerrero, Pilar; Alarcon, Tomas; Maini, Philip K; Byrne, Helen

2015-01-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Hybrid approaches for multiple-species stochastic reaction-diffusion models.

KAUST Repository

Spill, Fabian

2015-10-01

Reaction-diffusion models are used to describe systems in fields as diverse as physics, chemistry, ecology and biology. The fundamental quantities in such models are individual entities such as atoms and molecules, bacteria, cells or animals, which move and/or react in a stochastic manner. If the number of entities is large, accounting for each individual is inefficient, and often partial differential equation (PDE) models are used in which the stochastic behaviour of individuals is replaced by a description of the averaged, or mean behaviour of the system. In some situations the number of individuals is large in certain regions and small in others. In such cases, a stochastic model may be inefficient in one region, and a PDE model inaccurate in another. To overcome this problem, we develop a scheme which couples a stochastic reaction-diffusion system in one part of the domain with its mean field analogue, i.e. a discretised PDE model, in the other part of the domain. The interface in between the two domains occupies exactly one lattice site and is chosen such that the mean field description is still accurate there. In this way errors due to the flux between the domains are small. Our scheme can account for multiple dynamic interfaces separating multiple stochastic and deterministic domains, and the coupling between the domains conserves the total number of particles. The method preserves stochastic features such as extinction not observable in the mean field description, and is significantly faster to simulate on a computer than the pure stochastic model.

Risk Prediction Models for Other Cancers or Multiple Sites

Science.gov (United States)

Developing statistical models that estimate the probability of developing other multiple cancers over a defined period of time will help clinicians identify individuals at higher risk of specific cancers, allowing for earlier or more frequent screening and counseling of behavioral changes to decrease risk.

Exclusive description of multiple production on nuclei in the additive quark model. Multiplicity distributions in interactions with heavy nuclei

International Nuclear Information System (INIS)

Levchenko, B.B.; Nikolaev, N.N.

1985-01-01

In the framework of the additive quark model of multiple production on nuclei we calculate the multiplicity distributions of secondary particles and the correlations between secondary particles in πA and pA interactions with heavy nuclei. We show that intranuclear cascades are responsible for up to 50% of the nuclear increase of the multiplicity of fast particles. We analyze the sensitivity of the multiplicities and their correlations to the choice of the quark-hadronization function. We show that with good accuracy the yield of relativistic secondary particles from heavy and intermediate nuclei depends only on the number N/sub p/ of protons knocked out of the nucleus, and not on the mass number of the nucleus (N/sub p/ scaling)

Multiple attribute decision making model and application to food safety risk evaluation.

Science.gov (United States)

Ma, Lihua; Chen, Hong; Yan, Huizhe; Yang, Lifeng; Wu, Lifeng

2017-01-01

Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Penerapan Model Pembelajaran Atraktif Berbasis Multiple Intelligences Tentang Pemantulan Cahaya pada Cermin

Directory of Open Access Journals (Sweden)

Intan Kusumawati

2016-03-01

Full Text Available Penelitian ini bertujuan untuk mengetahui efektivitas penerapan model pembelajaran atraktif berbasis multiple intelligences dalam meremediasi miskonsepsi siswa tentang pemantulan cahaya pada cermin. Pada penelitian ini digunakan bentuk pre-eksperimental design dengan rancangan one group pretest-post test design. Alat pengumpulan data berupa tes pilihan ganda dengan reasoning. Hasil validitas sebesar 4,08 dan reliabilitas 0,537. Siswa dibagi menjadi lima kelompok kecerdasan, yaitu kelompok linguistic intelligence, mathematical-logical intelligence, visual-spatial intelligence, bodily-khinestetic intelligence, dan musical intelligence. Siswa membahas konsep fisika sesuai kelompok kecerdasannya dalam bentuk pembuatan pantun-puisi, teka-teki silang, menggambar kreatif, drama, dan mengarang lirik lagu. Efektivitas penerapan model pembelajaran multiple intelligences menggunakan persamaan effect size. Ditemukan bahwa skor effect size masing-masing kelompok berkategori tinggi sebesar 5,76; 3,76; 4,60; 1,70; dan 1,34. Penerapan model pembelajaran atraktif berbasis multiple intelligences efektif dalam meremediasi miskonsepsi siswa. Penelitian ini diharapkan dapat digunakan pada materi fisika dan sekolah lainnya.

A basket two-part model to analyze medical expenditure on interdependent multiple sectors.

Science.gov (United States)

Sugawara, Shinya; Wu, Tianyi; Yamanishi, Kenji

2018-05-01

This study proposes a novel statistical methodology to analyze expenditure on multiple medical sectors using consumer data. Conventionally, medical expenditure has been analyzed by two-part models, which separately consider purchase decision and amount of expenditure. We extend the traditional two-part models by adding the step of basket analysis for dimension reduction. This new step enables us to analyze complicated interdependence between multiple sectors without an identification problem. As an empirical application for the proposed method, we analyze data of 13 medical sectors from the Medical Expenditure Panel Survey. In comparison with the results of previous studies that analyzed the multiple sector independently, our method provides more detailed implications of the impacts of individual socioeconomic status on the composition of joint purchases from multiple medical sectors; our method has a better prediction performance.

MMOSS-I: a CANDU multiple-channel thermosyphoning flow stability model

Energy Technology Data Exchange (ETDEWEB)

Gulshani, P [Atomic Energy of Canada Ltd., Mississauga, ON (Canada); Huynh, H [Hydro-Quebec, Montreal, PQ (Canada)

1996-12-31

This paper presents a multiple-channel flow stability model, dubbed MMOSS, developed to predict the conditions for the onset of flow oscillations in a CANDU-type multiple-channel heat transport system under thermosyphoning conditions. The model generalizes that developed previously to account for the effects of any channel flow reversal. Two-phase thermosyphoning conditions are predicted by thermalhydraulic codes for some postulated accident scenarios in CANDU. Two-phase thermosyphoning experiments in the multiple-channel RD-14M facility have indicated that pass-to-pass out-of-phase oscillations in the loop conditions caused the flow in some of the heated channels to undergo sustained reversal in direction. This channel flow reversal had significant effects on the channel and loop conditions. It is, therefore, important to understand the nature of the oscillations and be able to predict the conditions for the onset of the oscillations or for stable flow in RD-14M and the reactor. For stable flow conditions, oscillation-induced channel flow reversal is not expected. MMOSS was developed for a figure-of-eight system with any number of channels. The system characteristic equation was derived from a linearization of the conservation equations. In this paper, the MMOSS characteristic equation is solved for a system of N identical channel assemblies. The resulting model is called MMOSS-I. This simplification provides valuable physical insight and reasonably accurate results. MMOSS-I and a previously-developed steady-state model THERMOSYPHON are used to predict thermosyphoning flow stability maps for RD-14M and the Gentilly 2 reactor. (author). 11 refs., 7 figs.

Model for nucleus-nucleus, hadron-nucleus and hadron-proton multiplicity distributions

International Nuclear Information System (INIS)

Singh, C.P.; Shyam, M.; Tuli, S.K.

1986-07-01

A model relating hadron-proton, hadron-nucleus and nucleus-nucleus multiplicity distributions is proposed and some interesting consequences are derived. The values of the parameters are the same for all the processes and are given by the QCD hypothesis of ''universal'' hadronic multiplicities which are found to be asymptotically independent of target and beam in hadronic and current induced reactions in particle physics. (author)

Multiple attribute decision making model and application to food safety risk evaluation.

Directory of Open Access Journals (Sweden)

Lihua Ma

Full Text Available Decision making for supermarket food purchase decisions are characterized by network relationships. This paper analyzed factors that influence supermarket food selection and proposes a supplier evaluation index system based on the whole process of food production. The author established the intuitive interval value fuzzy set evaluation model based on characteristics of the network relationship among decision makers, and validated for a multiple attribute decision making case study. Thus, the proposed model provides a reliable, accurate method for multiple attribute decision making.

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

An Integrated Cell Purification and Genomics Strategy Reveals Multiple Regulators of Pancreas Development

Science.gov (United States)

Benitez, Cecil M.; Qu, Kun; Sugiyama, Takuya; Pauerstein, Philip T.; Liu, Yinghua; Tsai, Jennifer; Gu, Xueying; Ghodasara, Amar; Arda, H. Efsun; Zhang, Jiajing; Dekker, Joseph D.; Tucker, Haley O.; Chang, Howard Y.; Kim, Seung K.

2014-01-01

The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus. PMID:25330008

An integrated cell purification and genomics strategy reveals multiple regulators of pancreas development.

Directory of Open Access Journals (Sweden)

Cecil M Benitez

2014-10-01

Full Text Available The regulatory logic underlying global transcriptional programs controlling development of visceral organs like the pancreas remains undiscovered. Here, we profiled gene expression in 12 purified populations of fetal and adult pancreatic epithelial cells representing crucial progenitor cell subsets, and their endocrine or exocrine progeny. Using probabilistic models to decode the general programs organizing gene expression, we identified co-expressed gene sets in cell subsets that revealed patterns and processes governing progenitor cell development, lineage specification, and endocrine cell maturation. Purification of Neurog3 mutant cells and module network analysis linked established regulators such as Neurog3 to unrecognized gene targets and roles in pancreas development. Iterative module network analysis nominated and prioritized transcriptional regulators, including diabetes risk genes. Functional validation of a subset of candidate regulators with corresponding mutant mice revealed that the transcription factors Etv1, Prdm16, Runx1t1 and Bcl11a are essential for pancreas development. Our integrated approach provides a unique framework for identifying regulatory genes and functional gene sets underlying pancreas development and associated diseases such as diabetes mellitus.

A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

DEFF Research Database (Denmark)

Dong, Yiqiu; Tieyong Zeng

2013-01-01

In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees...

Multiplicity in Early Stellar Evolution

Science.gov (United States)

Reipurth, B.; Clarke, C. J.; Boss, A. P.; Goodwin, S. P.; Rodríguez, L. F.; Stassun, K. G.; Tokovinin, A.; Zinnecker, H.

Observations from optical to centimeter wavelengths have demonstrated that multiple systems of two or more bodies is the norm at all stellar evolutionary stages. Multiple systems are widely agreed to result from the collapse and fragmentation of cloud cores, despite the inhibiting influence of magnetic fields. Surveys of class 0 protostars with millimeter interferometers have revealed a very high multiplicity frequency of about 2/3, even though there are observational difficulties in resolving close protobinaries, thus supporting the possibility that all stars could be born in multiple systems. Near-infrared adaptive optics observations of class I protostars show a lower binary frequency relative to the class 0 phase, a declining trend that continues through the class II/III stages to the field population. This loss of companions is a natural consequence of dynamical interplay in small multiple systems, leading to ejection of members. We discuss observational consequences of this dynamical evolution, and its influence on circumstellar disks, and we review the evolution of circumbinary disks and their role in defining binary mass ratios. Special attention is paid to eclipsing PMS binaries, which allow for observational tests of evolutionary models of early stellar evolution. Many stars are born in clusters and small groups, and we discuss how interactions in dense stellar environments can significantly alter the distribution of binary separations through dissolution of wider binaries. The binaries and multiples we find in the field are the survivors of these internal and external destructive processes, and we provide a detailed overview of the multiplicity statistics of the field, which form a boundary condition for all models of binary evolution. Finally, we discuss various formation mechanisms for massive binaries, and the properties of massive trapezia.

The empirical content of models with multiple equilibria in economies with social interactions

OpenAIRE

Alberto Bisin; Andrea Moro; Giorgio Topa

2011-01-01

We study a general class of models with social interactions that might display multiple equilibria. We propose an estimation procedure for these models and evaluate its efficiency and computational feasibility relative to different approaches taken to the curse of dimensionality implied by the multiplicity. Using data on smoking among teenagers, we implement the proposed estimation procedure to understand how group interactions affect health-related choices. We find that interaction effects a...

Dynamic coordinated control laws in multiple agent models

International Nuclear Information System (INIS)

Morgan, David S.; Schwartz, Ira B.

2005-01-01

We present an active control scheme of a kinetic model of swarming. It has been shown previously that the global control scheme for the model, presented in [Systems Control Lett. 52 (2004) 25], gives rise to spontaneous collective organization of agents into a unified coherent swarm, via steering controls and utilizing long-range attractive and short-range repulsive interactions. We extend these results by presenting control laws whereby a single swarm is broken into independently functioning subswarm clusters. The transition between one coordinated swarm and multiple clustered subswarms is managed simply with a homotopy parameter. Additionally, we present as an alternate formulation, a local control law for the same model, which implements dynamic barrier avoidance behavior, and in which swarm coherence emerges spontaneously

Using multiple decrement models to estimate risk and morbidity from specific AIDS illnesses. Multicenter AIDS Cohort Study (MACS).

Science.gov (United States)

Hoover, D R; Peng, Y; Saah, A J; Detels, R R; Day, R S; Phair, J P

A simple non-parametric approach is developed to simultaneously estimate net incidence and morbidity time from specific AIDS illnesses in populations at high risk for death from these illnesses and other causes. The disease-death process has four-stages that can be recast as two sandwiching three-state multiple decrement processes. Non-parametric estimation of net incidence and morbidity time with error bounds are achieved from these sandwiching models through modification of methods from Aalen and Greenwood, and bootstrapping. An application to immunosuppressed HIV-1 infected homosexual men reveals that cytomegalovirus disease, Kaposi's sarcoma and Pneumocystis pneumonia are likely to occur and cause significant morbidity time.

Flexible Modeling of Survival Data with Covariates Subject to Detection Limits via Multiple Imputation.

Science.gov (United States)

Bernhardt, Paul W; Wang, Huixia Judy; Zhang, Daowen

2014-01-01

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time model with a flexible seminonparametric error distribution. The consistency and asymptotic normality of the multiple imputation estimator are established and a consistent variance estimator is provided. An iterative version of the proposed multiple imputation algorithm that approximates the EM algorithm for maximum likelihood is also suggested. Simulation studies demonstrate that the proposed multiple imputation methods work well while alternative methods lead to estimates that are either biased or more variable. The proposed methods are applied to analyze the dataset from a recently-conducted GenIMS study.

A feedback control model for network flow with multiple pure time delays

Science.gov (United States)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

Multiple Model Adaptive Attitude Control of LEO Satellite with Angular Velocity Constraints

Science.gov (United States)

Shahrooei, Abolfazl; Kazemi, Mohammad Hosein

2018-04-01

In this paper, the multiple model adaptive control is utilized to improve the transient response of attitude control system for a rigid spacecraft. An adaptive output feedback control law is proposed for attitude control under angular velocity constraints and its almost global asymptotic stability is proved. The multiple model adaptive control approach is employed to counteract large uncertainty in parameter space of the inertia matrix. The nonlinear dynamics of a low earth orbit satellite is simulated and the proposed control algorithm is implemented. The reported results show the effectiveness of the suggested scheme.

Improving the Pattern Reproducibility of Multiple-Point-Based Prior Models Using Frequency Matching

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Mosegaard, Klaus

2014-01-01

Some multiple-point-based sampling algorithms, such as the snesim algorithm, rely on sequential simulation. The conditional probability distributions that are used for the simulation are based on statistics of multiple-point data events obtained from a training image. During the simulation, data...... events with zero probability in the training image statistics may occur. This is handled by pruning the set of conditioning data until an event with non-zero probability is found. The resulting probability distribution sampled by such algorithms is a pruned mixture model. The pruning strategy leads...... to a probability distribution that lacks some of the information provided by the multiple-point statistics from the training image, which reduces the reproducibility of the training image patterns in the outcome realizations. When pruned mixture models are used as prior models for inverse problems, local re...

Vehicle coordinated transportation dispatching model base on multiple crisis locations

Science.gov (United States)

Tian, Ran; Li, Shanwei; Yang, Guoying

2018-05-01

Many disastrous events are often caused after unconventional emergencies occur, and the requirements of disasters are often different. It is difficult for a single emergency resource center to satisfy such requirements at the same time. Therefore, how to coordinate the emergency resources stored by multiple emergency resource centers to various disaster sites requires the coordinated transportation of emergency vehicles. In this paper, according to the problem of emergency logistics coordination scheduling, based on the related constraints of emergency logistics transportation, an emergency resource scheduling model based on multiple disasters is established.

A P-value model for theoretical power analysis and its applications in multiple testing procedures

Directory of Open Access Journals (Sweden)

Fengqing Zhang

2016-10-01

Full Text Available Abstract Background Power analysis is a critical aspect of the design of experiments to detect an effect of a given size. When multiple hypotheses are tested simultaneously, multiplicity adjustments to p-values should be taken into account in power analysis. There are a limited number of studies on power analysis in multiple testing procedures. For some methods, the theoretical analysis is difficult and extensive numerical simulations are often needed, while other methods oversimplify the information under the alternative hypothesis. To this end, this paper aims to develop a new statistical model for power analysis in multiple testing procedures. Methods We propose a step-function-based p-value model under the alternative hypothesis, which is simple enough to perform power analysis without simulations, but not too simple to lose the information from the alternative hypothesis. The first step is to transform distributions of different test statistics (e.g., t, chi-square or F to distributions of corresponding p-values. We then use a step function to approximate each of the p-value’s distributions by matching the mean and variance. Lastly, the step-function-based p-value model can be used for theoretical power analysis. Results The proposed model is applied to problems in multiple testing procedures. We first show how the most powerful critical constants can be chosen using the step-function-based p-value model. Our model is then applied to the field of multiple testing procedures to explain the assumption of monotonicity of the critical constants. Lastly, we apply our model to a behavioral weight loss and maintenance study to select the optimal critical constants. Conclusions The proposed model is easy to implement and preserves the information from the alternative hypothesis.

Challenges in LCA modelling of multiple loops for aluminium cans

DEFF Research Database (Denmark)

Niero, Monia; Olsen, Stig Irving

considered the case of closed-loop recycling for aluminium cans, where body and lid are different alloys, and discussed the abovementioned challenge. The Life Cycle Inventory (LCI) modelling of aluminium processes is traditionally based on a pure aluminium flow, therefore neglecting the presence of alloying...... elements. We included the effect of alloying elements on the LCA modelling of aluminium can recycling. First, we performed a mass balance of the main alloying elements (Mn, Fe, Si, Cu) in aluminium can recycling at increasing levels of recycling rate. The analysis distinguished between different aluminium...... packaging scrap sources (i.e. used beverage can and mixed aluminium packaging) to understand the limiting factors for multiple loop aluminium can recycling. Secondly, we performed a comparative LCA of aluminium can production and recycling in multiple loops considering the two aluminium packaging scrap...

A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

KAUST Repository

Kannan, Venkateshan

2017-03-29

Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving the immune system and CNS that generates the principal subtypes of the disease observed in patients. The model captures several key features of MS, especially those that distinguish the chronic progressive phase from that of the relapse-remitting. In addition, a rare subtype of the disease, progressive relapsing MS naturally emerges from the model. The model posits the existence of two key thresholds, one in the immune system and the other in the CNS, that separate dynamically distinct behavior of the model. Exploring the two-dimensional space of these thresholds, we obtain multiple phases of disease evolution and these shows greater variation than the clinical classification of MS, thus capturing the heterogeneity that is manifested in patients.

Modelling multiple cycles of static and dynamic recrystallisation using a fully implicit isotropic material model based on dislocation density

Science.gov (United States)

Jansen van Rensburg, Gerhardus J.; Kok, Schalk; Wilke, Daniel N.

2018-03-01

This paper presents the development and numerical implementation of a state variable based thermomechanical material model, intended for use within a fully implicit finite element formulation. Plastic hardening, thermal recovery and multiple cycles of recrystallisation can be tracked for single peak as well as multiple peak recrystallisation response. The numerical implementation of the state variable model extends on a J2 isotropic hypo-elastoplastic modelling framework. The complete numerical implementation is presented as an Abaqus UMAT and linked subroutines. Implementation is discussed with detailed explanation of the derivation and use of various sensitivities, internal state variable management and multiple recrystallisation cycle contributions. A flow chart explaining the proposed numerical implementation is provided as well as verification on the convergence of the material subroutine. The material model is characterised using two high temperature data sets for cobalt and copper. The results of finite element analyses using the material parameter values characterised on the copper data set are also presented.

Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?

Directory of Open Access Journals (Sweden)

Hayduk Leslie A

2012-10-01

Full Text Available Abstract Background Structural equation modeling developed as a statistical melding of path analysis and factor analysis that obscured a fundamental tension between a factor preference for multiple indicators and path modeling’s openness to fewer indicators. Discussion Multiple indicators hamper theory by unnecessarily restricting the number of modeled latents. Using the few best indicators – possibly even the single best indicator of each latent – encourages development of theoretically sophisticated models. Additional latent variables permit stronger statistical control of potential confounders, and encourage detailed investigation of mediating causal mechanisms. Summary We recommend the use of the few best indicators. One or two indicators are often sufficient, but three indicators may occasionally be helpful. More than three indicators are rarely warranted because additional redundant indicators provide less research benefit than single indicators of additional latent variables. Scales created from multiple indicators can introduce additional problems, and are prone to being less desirable than either single or multiple indicators.

A Model of Distraction using new Architectural Mechanisms to Manage Multiple Goals

NARCIS (Netherlands)

Taatgen, Niels; Katidioti, Ioanna; Borst, Jelmer; van Vugt, Marieke; Taatgen, Niels; van Vugt, Marieke; Borst, Jelmer; Mehlhorn, Katja

2015-01-01

Cognitive models assume a one-to-one correspondence between task and goals. We argue that modeling a task by combining multiple goals has several advantages: a task can be constructed from components that are reused from other tasks, and it enables modeling thought processes that compete with or

REDOR NMR Reveals Multiple Conformers for a Protein Kinase C Ligand in a Membrane Environment

Directory of Open Access Journals (Sweden)

Hao Yang

2018-01-01

Full Text Available Bryostatin 1 (henceforth bryostatin is in clinical trials for the treatment of Alzheimer’s disease and for HIV/AIDS eradication. It is also a preclinical lead for cancer immunotherapy and other therapeutic indications. Yet nothing is known about the conformation of bryostatin bound to its protein kinase C (PKC target in a membrane microenvironment. As a result, efforts to design more efficacious, better tolerated, or more synthetically accessible ligands have been limited to structures that do not include PKC or membrane effects known to influence PKC–ligand binding. This problem extends more generally to many membrane-associated proteins in the human proteome. Here, we use rotational-echo double-resonance (REDOR solid-state NMR to determine the conformations of PKC modulators bound to the PKCδ-C1b domain in the presence of phospholipid vesicles. The conformationally limited PKC modulator phorbol diacetate (PDAc is used as an initial test substrate. While unanticipated partitioning of PDAc between an immobilized protein-bound state and a mobile state in the phospholipid assembly was observed, a single conformation in the bound state was identified. In striking contrast, a bryostatin analogue (bryolog was found to exist exclusively in a protein-bound state, but adopts a distribution of conformations as defined by three independent distance measurements. The detection of multiple PKCδ-C1b-bound bryolog conformers in a functionally relevant phospholipid complex reveals the inherent dynamic nature of cellular systems that is not captured with single-conformation static structures. These results indicate that binding, selectivity, and function of PKC modulators, as well as the design of new modulators, are best addressed using a dynamic multistate model, an analysis potentially applicable to other membrane-associated proteins.

Modelling reveals kinetic advantages of co-transcriptional splicing.

Directory of Open Access Journals (Sweden)

Stuart Aitken

2011-10-01

Full Text Available Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

Modelling reveals kinetic advantages of co-transcriptional splicing.

Science.gov (United States)

Aitken, Stuart; Alexander, Ross D; Beggs, Jean D

2011-10-01

Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.

A dynamical model of car-following with the consideration of the multiple information of preceding cars

International Nuclear Information System (INIS)

Peng, G.H.; Sun, D.H.

2010-01-01

An improved multiple car-following (MCF) model is proposed, based on the full velocity difference (FVD) model, but taking into consideration multiple information inputs from preceding vehicles. The linear stability condition of the model is obtained by using the linear stability theory. Through nonlinear analysis, the modified Korteweg-de Vries (mKdV) equation is derived to describe the traffic behavior near the critical point. Numerical simulation shows that the proposed model is theoretically an improvement over others, while retaining many strong points in the previous ones by adjusting the information of the multiple leading vehicles.

Multiple sequential failure model: A probabilistic approach to quantifying human error dependency

International Nuclear Information System (INIS)

Samanta

1985-01-01

This paper rpesents a probabilistic approach to quantifying human error dependency when multiple tasks are performed. Dependent human failures are dominant contributors to risks from nuclear power plants. An overview of the Multiple Sequential Failure (MSF) model developed and its use in probabilistic risk assessments (PRAs) depending on the available data are discussed. A small-scale psychological experiment was conducted on the nature of human dependency and the interpretation of the experimental data by the MSF model show remarkable accommodation of the dependent failure data. The model, which provides an unique method for quantification of dependent failures in human reliability analysis, can be used in conjunction with any of the general methods currently used for performing the human reliability aspect in PRAs

Double-multiple streamtube model for studying vertical-axis wind turbines

Science.gov (United States)

Paraschivoiu, Ion

1988-08-01

This work describes the present state-of-the-art in double-multiple streamtube method for modeling the Darrieus-type vertical-axis wind turbine (VAWT). Comparisons of the analytical results with the other predictions and available experimental data show a good agreement. This method, which incorporates dynamic-stall and secondary effects, can be used for generating a suitable aerodynamic-load model for structural design analysis of the Darrieus rotor.

Multiple Surrogate Modeling for Wire-Wrapped Fuel Assembly Optimization

International Nuclear Information System (INIS)

Raza, Wasim; Kim, Kwang-Yong

2007-01-01

In this work, shape optimization of seven pin wire wrapped fuel assembly has been carried out in conjunction with RANS analysis in order to evaluate the performances of surrogate models. Previously, Ahmad and Kim performed the flow and heat transfer analysis based on the three-dimensional RANS analysis. But numerical optimization has not been applied to the design of wire-wrapped fuel assembly, yet. Surrogate models are being widely used in multidisciplinary optimization. Queipo et al. reviewed various surrogates based models used in aerospace applications. Goel et al. developed weighted average surrogate model based on response surface approximation (RSA), radial basis neural network (RBNN) and Krigging (KRG) models. In addition to the three basic models, RSA, RBNN and KRG, the multiple surrogate model, PBA also has been employed. Two geometric design variables and a multi-objective function with a weighting factor have been considered for this problem

Modeling and optimization of a utility system containing multiple extractions steam turbines

International Nuclear Information System (INIS)

Luo, Xianglong; Zhang, Bingjian; Chen, Ying; Mo, Songping

2011-01-01

Complex turbines with multiple controlled and/or uncontrolled extractions are popularly used in the processing industry and cogeneration plants to provide steam of different levels, electric power, and driving power. To characterize thermodynamic behavior under varying conditions, nonlinear mathematical models are developed based on energy balance, thermodynamic principles, and semi-empirical equations. First, the complex turbine is decomposed into several simple turbines from the controlled extraction stages and modeled in series. THM (The turbine hardware model) developing concept is applied to predict the isentropic efficiency of the decomposed simple turbines. Stodola's formulation is also used to simulate the uncontrolled extraction steam parameters. The thermodynamic properties of steam and water are regressed through linearization or piece-wise linearization. Second, comparison between the simulated results using the proposed model and the data in the working condition diagram provided by the manufacturer is conducted over a wide range of operations. The simulation results yield small deviation from the data in the working condition diagram where the maximum modeling error is 0.87% among the compared seven operation conditions. Last, the optimization model of a utility system containing multiple extraction turbines is established and a detailed case is analyzed. Compared with the conventional operation strategy, a maximum of 5.47% of the total operation cost is saved using the proposed optimization model. -- Highlights: → We develop a complete simulation model for steam turbine with multiple extractions. → We test the simulation model using the performance data of commercial turbines. → The simulation error of electric power generation is no more than 0.87%. → We establish a utility system operational optimization model. → The optimal industrial operation scheme featured with 5.47% of cost saving.

Modelling the Dynamics of Intracellular Processes as an Organisation of Multiple Agents

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.; Armano, G.; Merelli, E.; Denzinger, J.; Martin, A.; Miles, S.; Tianfield, H.; Unland, R.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modeled as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics by structuring

A modeling and numerical algorithm for thermoporomechanics in multiple porosity media for naturally fractured reservoirs

Science.gov (United States)

Kim, J.; Sonnenthal, E. L.; Rutqvist, J.

2011-12-01

Rigorous modeling of coupling between fluid, heat, and geomechanics (thermo-poro-mechanics), in fractured porous media is one of the important and difficult topics in geothermal reservoir simulation, because the physics are highly nonlinear and strongly coupled. Coupled fluid/heat flow and geomechanics are investigated using the multiple interacting continua (MINC) method as applied to naturally fractured media. In this study, we generalize constitutive relations for the isothermal elastic dual porosity model proposed by Berryman (2002) to those for the non-isothermal elastic/elastoplastic multiple porosity model, and derive the coupling coefficients of coupled fluid/heat flow and geomechanics and constraints of the coefficients. When the off-diagonal terms of the total compressibility matrix for the flow problem are zero, the upscaled drained bulk modulus for geomechanics becomes the harmonic average of drained bulk moduli of the multiple continua. In this case, the drained elastic/elastoplastic moduli for mechanics are determined by a combination of the drained moduli and volume fractions in multiple porosity materials. We also determine a relation between local strains of all multiple porosity materials in a gridblock and the global strain of the gridblock, from which we can track local and global elastic/plastic variables. For elastoplasticity, the return mapping is performed for all multiple porosity materials in the gridblock. For numerical implementation, we employ and extend the fixed-stress sequential method of the single porosity model to coupled fluid/heat flow and geomechanics in multiple porosity systems, because it provides numerical stability and high accuracy. This sequential scheme can be easily implemented by using a porosity function and its corresponding porosity correction, making use of the existing robust flow and geomechanics simulators. We implemented the proposed modeling and numerical algorithm to the reaction transport simulator

Airport choice model in multiple airport regions

Directory of Open Access Journals (Sweden)

Claudia Muñoz

2017-02-01

Full Text Available Purpose: This study aims to analyze travel choices made by air transportation users in multi airport regions because it is a crucial component when planning passenger redistribution policies. The purpose of this study is to find a utility function which makes it possible to know the variables that influence users’ choice of the airports on routes to the main cities in the Colombian territory. Design/methodology/approach: This research generates a Multinomial Logit Model (MNL, which is based on the theory of maximizing utility, and it is based on the data obtained on revealed and stated preference surveys applied to users who reside in the metropolitan area of Aburrá Valley (Colombia. This zone is the only one in the Colombian territory which has two neighboring airports for domestic flights. The airports included in the modeling process were Enrique Olaya Herrera (EOH Airport and José María Córdova (JMC Airport. Several structure models were tested, and the MNL proved to be the most significant revealing the common variables that affect passenger airport choice include the airfare, the price to travel the airport, and the time to get to the airport. Findings and Originality/value: The airport choice model which was calibrated corresponds to a valid powerful tool used to calculate the probability of each analyzed airport of being chosen for domestic flights in the Colombian territory. This is done bearing in mind specific characteristic of each of the attributes contained in the utility function. In addition, these probabilities will be used to calculate future market shares of the two airports considered in this study, and this will be done generating a support tool for airport and airline marketing policies.

Revealing the equivalence of two clonal survival models by principal component analysis

International Nuclear Information System (INIS)

Lachet, Bernard; Dufour, Jacques

1976-01-01

The principal component analysis of 21 chlorella cell survival curves, adjusted by one-hit and two-hit target models, lead to quite similar projections on the principal plan: the homologous parameters of these models are linearly correlated; the reason for the statistical equivalence of these two models, in the present state of experimental inaccuracy, is revealed [fr

Model selection with multiple regression on distance matrices leads to incorrect inferences.

Directory of Open Access Journals (Sweden)

Ryan P Franckowiak

Full Text Available In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC, its small-sample correction (AICc, and the Bayesian information criterion (BIC to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.

Multiple Temperature Model for Near Continuum Flows

International Nuclear Information System (INIS)

XU, Kun; Liu, Hongwei; Jiang, Jianzheng

2007-01-01

In the near continuum flow regime, the flow may have different translational temperatures in different directions. It is well known that for increasingly rarefied flow fields, the predictions from continuum formulation, such as the Navier-Stokes equations, lose accuracy. These inaccuracies may be partially due to the single temperature assumption in the Navier-Stokes equations. Here, based on the gas-kinetic Bhatnagar-Gross-Krook (BGK) equation, a multitranslational temperature model is proposed and used in the flow calculations. In order to fix all three translational temperatures, two constraints are additionally proposed to model the energy exchange in different directions. Based on the multiple temperature assumption, the Navier-Stokes relation between the stress and strain is replaced by the temperature relaxation term, and the Navier-Stokes assumption is recovered only in the limiting case when the flow is close to the equilibrium with the same temperature in different directions. In order to validate the current model, both the Couette and Poiseuille flows are studied in the transition flow regime

A toy MCT model for multiple glass transitions: Double swallow tail singularity

Energy Technology Data Exchange (ETDEWEB)

Ryzhov, V.N. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation); Moscow Institute of Physics and Technology, 141700 Moscow (Russian Federation); Tareyeva, E.E. [Institute for High Pressure Physics, Russian Academy of Sciences, Troitsk 142190, Moscow region (Russian Federation)

2014-11-07

We propose a toy model to describe in the frame of Mode Coupling Theory multiple glass transitions. The model is based on the postulated simple form for static structure factor as a sum of two delta-functions. This form makes it possible to solve the MCT equations in almost analytical way. The phase diagram is governed by two swallow tails resulting from two A{sub 4} singularities and includes liquid–glass transition and multiple glasses. The diagram has much in common with those of binary and quasibinary systems. - Highlights: • A simple toy model is proposed for description of glass–glass transitions. • The static structure factor of the model has the form of a sum of delta-functions. • The phase diagram contains A{sub 4} bifurcation singularities and A{sub 3} end points. • The results can be applied for the qualitative description of quasibinary systems.

Validation and calibration of structural models that combine information from multiple sources.

Science.gov (United States)

Dahabreh, Issa J; Wong, John B; Trikalinos, Thomas A

2017-02-01

Mathematical models that attempt to capture structural relationships between their components and combine information from multiple sources are increasingly used in medicine. Areas covered: We provide an overview of methods for model validation and calibration and survey studies comparing alternative approaches. Expert commentary: Model validation entails a confrontation of models with data, background knowledge, and other models, and can inform judgments about model credibility. Calibration involves selecting parameter values to improve the agreement of model outputs with data. When the goal of modeling is quantitative inference on the effects of interventions or forecasting, calibration can be viewed as estimation. This view clarifies issues related to parameter identifiability and facilitates formal model validation and the examination of consistency among different sources of information. In contrast, when the goal of modeling is the generation of qualitative insights about the modeled phenomenon, calibration is a rather informal process for selecting inputs that result in model behavior that roughly reproduces select aspects of the modeled phenomenon and cannot be equated to an estimation procedure. Current empirical research on validation and calibration methods consists primarily of methodological appraisals or case-studies of alternative techniques and cannot address the numerous complex and multifaceted methodological decisions that modelers must make. Further research is needed on different approaches for developing and validating complex models that combine evidence from multiple sources.

Multiplicative point process as a model of trading activity

Science.gov (United States)

Gontis, V.; Kaulakys, B.

2004-11-01

Signals consisting of a sequence of pulses show that inherent origin of the 1/ f noise is a Brownian fluctuation of the average interevent time between subsequent pulses of the pulse sequence. In this paper, we generalize the model of interevent time to reproduce a variety of self-affine time series exhibiting power spectral density S( f) scaling as a power of the frequency f. Furthermore, we analyze the relation between the power-law correlations and the origin of the power-law probability distribution of the signal intensity. We introduce a stochastic multiplicative model for the time intervals between point events and analyze the statistical properties of the signal analytically and numerically. Such model system exhibits power-law spectral density S( f)∼1/ fβ for various values of β, including β= {1}/{2}, 1 and {3}/{2}. Explicit expressions for the power spectra in the low-frequency limit and for the distribution density of the interevent time are obtained. The counting statistics of the events is analyzed analytically and numerically, as well. The specific interest of our analysis is related with the financial markets, where long-range correlations of price fluctuations largely depend on the number of transactions. We analyze the spectral density and counting statistics of the number of transactions. The model reproduces spectral properties of the real markets and explains the mechanism of power-law distribution of trading activity. The study provides evidence that the statistical properties of the financial markets are enclosed in the statistics of the time interval between trades. A multiplicative point process serves as a consistent model generating this statistics.

Modeling Spatial Dependence of Rainfall Extremes Across Multiple Durations

Science.gov (United States)

Le, Phuong Dong; Leonard, Michael; Westra, Seth

2018-03-01

Determining the probability of a flood event in a catchment given that another flood has occurred in a nearby catchment is useful in the design of infrastructure such as road networks that have multiple river crossings. These conditional flood probabilities can be estimated by calculating conditional probabilities of extreme rainfall and then transforming rainfall to runoff through a hydrologic model. Each catchment's hydrological response times are unlikely to be the same, so in order to estimate these conditional probabilities one must consider the dependence of extreme rainfall both across space and across critical storm durations. To represent these types of dependence, this study proposes a new approach for combining extreme rainfall across different durations within a spatial extreme value model using max-stable process theory. This is achieved in a stepwise manner. The first step defines a set of common parameters for the marginal distributions across multiple durations. The parameters are then spatially interpolated to develop a spatial field. Storm-level dependence is represented through the max-stable process for rainfall extremes across different durations. The dependence model shows a reasonable fit between the observed pairwise extremal coefficients and the theoretical pairwise extremal coefficient function across all durations. The study demonstrates how the approach can be applied to develop conditional maps of the return period and return level across different durations.

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

Energy Technology Data Exchange (ETDEWEB)

Yamazaki, Kazutoshi, E-mail: kyamazak@kansai-u.ac.jp [Kansai University, Department of Mathematics, Faculty of Engineering Science (Japan)

2015-08-15

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and to evaluate the efficiency of the algorithm.

Contraction Options and Optimal Multiple-Stopping in Spectrally Negative Lévy Models

International Nuclear Information System (INIS)

Yamazaki, Kazutoshi

2015-01-01

This paper studies the optimal multiple-stopping problem arising in the context of the timing option to withdraw from a project in stages. The profits are driven by a general spectrally negative Lévy process. This allows the model to incorporate sudden declines of the project values, generalizing greatly the classical geometric Brownian motion model. We solve the one-stage case as well as the extension to the multiple-stage case. The optimal stopping times are of threshold-type and the value function admits an expression in terms of the scale function. A series of numerical experiments are conducted to verify the optimality and to evaluate the efficiency of the algorithm

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

Directory of Open Access Journals (Sweden)

Edy Legowo

2017-03-01

Full Text Available Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilitasi guru dapat menstimulasi multiple intelligences siswa. Evaluasi hasil belajar siswa dari pandangan penerapan teori multiple intelligences seharusnya dilakukan menggunakan authentic assessment dan portofolio yang lebih memfasilitasi para siswa mengungkapkan atau mengaktualisasikan hasil belajarnya melalui berbagai cara sesuai dengan kekuatan jenis inteligensinya.

A multiple objective mixed integer linear programming model for power generation expansion planning

Energy Technology Data Exchange (ETDEWEB)

Antunes, C. Henggeler; Martins, A. Gomes [INESC-Coimbra, Coimbra (Portugal); Universidade de Coimbra, Dept. de Engenharia Electrotecnica, Coimbra (Portugal); Brito, Isabel Sofia [Instituto Politecnico de Beja, Escola Superior de Tecnologia e Gestao, Beja (Portugal)

2004-03-01

Power generation expansion planning inherently involves multiple, conflicting and incommensurate objectives. Therefore, mathematical models become more realistic if distinct evaluation aspects, such as cost and environmental concerns, are explicitly considered as objective functions rather than being encompassed by a single economic indicator. With the aid of multiple objective models, decision makers may grasp the conflicting nature and the trade-offs among the different objectives in order to select satisfactory compromise solutions. This paper presents a multiple objective mixed integer linear programming model for power generation expansion planning that allows the consideration of modular expansion capacity values of supply-side options. This characteristic of the model avoids the well-known problem associated with continuous capacity values that usually have to be discretized in a post-processing phase without feedback on the nature and importance of the changes in the attributes of the obtained solutions. Demand-side management (DSM) is also considered an option in the planning process, assuming there is a sufficiently large portion of the market under franchise conditions. As DSM full costs are accounted in the model, including lost revenues, it is possible to perform an evaluation of the rate impact in order to further inform the decision process (Author)

Multiplicative Attribute Graph Model of Real-World Networks

Energy Technology Data Exchange (ETDEWEB)

Kim, Myunghwan [Stanford Univ., CA (United States); Leskovec, Jure [Stanford Univ., CA (United States)

2010-10-20

Large scale real-world network data, such as social networks, Internet andWeb graphs, is ubiquitous in a variety of scientific domains. The study of such social and information networks commonly finds patterns and explain their emergence through tractable models. In most networks, especially in social networks, nodes also have a rich set of attributes (e.g., age, gender) associatedwith them. However, most of the existing network models focus only on modeling the network structure while ignoring the features of nodes in the network. Here we present a class of network models that we refer to as the Multiplicative Attribute Graphs (MAG), which naturally captures the interactions between the network structure and node attributes. We consider a model where each node has a vector of categorical features associated with it. The probability of an edge between a pair of nodes then depends on the product of individual attributeattribute similarities. The model yields itself to mathematical analysis as well as fit to real data. We derive thresholds for the connectivity, the emergence of the giant connected component, and show that the model gives rise to graphs with a constant diameter. Moreover, we analyze the degree distribution to show that the model can produce networks with either lognormal or power-law degree distribution depending on certain conditions.

Multiple Conceptual Modelling of Perceived Quality of In-flight Airline Services

Directory of Open Access Journals (Sweden)

Urban Šebjan

2017-06-01

Full Text Available Despite growing literature on the different aspects of airline service quality in relation to behavioural intentions, less attention has been paid to some specific aspects of in-flight services. The focus of the present research is, therefore, on a multiple conceptual model of the quality of in-flight services in relation to passengers’ perception of value, followed by recommendations (word of mouth - WOM of airlines, as well as the quality and comfort of airline seats. The study is performed using two databases of reviewers’/passengers’ opinions regarding the quality of in-flight airline services and airline seat comfort. Our research results reveal that the perceived comfort of the airplane seat is the most important factor of passengers’ perceived quality of in-flight airline services, which also considerably affects the passengers’ perception of value, and consequently moderates behavioural intentions (in our research, expressed through positive WOM. The analysis of the relative importance of the components of perceived airline seats’ comfort shows that seat width is the most significant factor that contributes to the overall perceived comfort of the airline seat.

INCORPORATING MULTIPLE OBJECTIVES IN PLANNING MODELS OF LOW-RESOURCE FARMERS

OpenAIRE

Flinn, John C.; Jayasuriya, Sisira; Knight, C. Gregory

1980-01-01

Linear goal programming provides a means of formally incorporating the multiple goals of a household into the analysis of farming systems. Using this approach, the set of plans which come as close as possible to achieving a set of desired goals under conditions of land and cash scarcity are derived for a Filipino tenant farmer. A challenge in making LGP models empirically operational is the accurate definition of the goals of the farm household being modelled.

Multiple sclerosis

International Nuclear Information System (INIS)

Sadashima, Hiromichi; Kusaka, Hirofumi; Imai, Terukuni; Takahashi, Ryosuke; Matsumoto, Sadayuki; Yamamoto, Toru; Yamasaki, Masahiro; Maya, Kiyomi

1986-01-01

Eleven patients with a definite diagnosis of multiple sclerosis were examined in terms of correlations between the clinical features and the results of cranial computed tomography (CT), and magnetic resonance imaging (MRI). Results: In 5 of the 11 patients, both CT and MRI demonstrated lesions consistent with a finding of multiple sclerosis. In 3 patients, only MRI demonstrated lesions. In the remaining 3 patients, neither CT nor MRI revealed any lesion in the brain. All 5 patients who showed abnormal findings on both CT and MRI had clinical signs either of cerebral or brainstem - cerebellar lesions. On the other hand, two of the 3 patients with normal CT and MRI findings had optic-nerve and spinal-cord signs. Therefore, our results suggested relatively good correlations between the clinical features, CT, and MRI. MRI revealed cerebral lesions in two of the four patients with clinical signs of only optic-nerve and spinal-cord lesions. MRI demonstrated sclerotic lesions in 3 of the 6 patients whose plaques were not detected by CT. In conclusion, MRI proved to be more helpful in the demonstration of lesions attributable to chronic multiple sclerosis. (author)

Multiple-collision model for pion production in relativistic nucleus-nucleus collisions

International Nuclear Information System (INIS)

Vary, J.P.

1978-01-01

A simple model for pion production in relativistic heavy-ion collisions is developed based on nucleon-nucleon data, nuclear density distribution, and the assumption of straight-line trajectories. Multiplicity distributions for total pion production and for negative-pion production are predicted for 40 Ar incident on a Pb 3 O 4 target at 1.8 GeV/nucleon. Production through intermediate baryon resonances reduces the high-multiplicity region but insufficiently to yield agreement with data. This implies the need for a coherent production mechanism

Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

Science.gov (United States)

Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

2017-08-01

Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

Exploring the Use of Multiple Analogical Models when Teaching and Learning Chemical Equilibrium

Science.gov (United States)

Harrison, Allan G.; De Jong, Onno

2005-01-01

This study describes the multiple analogical models used to introduce and teach Grade 12 chemical equilibrium. We examine the teacher's reasons for using models, explain each model's development during the lessons, and analyze the understandings students derived from the models. A case study approach was used and the data were drawn from the…

Medicare capitation model, functional status, and multiple comorbidities: model accuracy

Science.gov (United States)

Noyes, Katia; Liu, Hangsheng; Temkin-Greener, Helena

2012-01-01

Objective This study examined financial implications of CMS-Hierarchical Condition Categories (HCC) risk-adjustment model on Medicare payments for individuals with comorbid chronic conditions. Study Design The study used 1992-2000 data from the Medicare Current Beneficiary Survey and corresponding Medicare claims. The pairs of comorbidities were formed based on the prior evidence about possible synergy between these conditions and activities of daily living (ADL) deficiencies and included heart disease and cancer, lung disease and cancer, stroke and hypertension, stroke and arthritis, congestive heart failure (CHF) and osteoporosis, diabetes and coronary artery disease, CHF and dementia. Methods For each beneficiary, we calculated the actual Medicare cost ratio as the ratio of the individual’s annualized costs to the mean annual Medicare cost of all people in the study. The actual Medicare cost ratios, by ADLs, were compared to the HCC ratios under the CMS-HCC payment model. Using multivariate regression models, we tested whether having the identified pairs of comorbidities affects the accuracy of CMS-HCC model predictions. Results The CMS-HCC model underpredicted Medicare capitation payments for patients with hypertension, lung disease, congestive heart failure and dementia. The difference between the actual costs and predicted payments was partially explained by beneficiary functional status and less than optimal adjustment for these chronic conditions. Conclusions Information about beneficiary functional status should be incorporated in reimbursement models since underpaying providers for caring for population with multiple comorbidities may provide severe disincentives for managed care plans to enroll such individuals and to appropriately manage their complex and costly conditions. PMID:18837646

Modeling reveals bistability and low-pass filtering in the network module determining blood stem cell fate.

Directory of Open Access Journals (Sweden)

Jatin Narula

2010-05-01

Full Text Available Combinatorial regulation of gene expression is ubiquitous in eukaryotes with multiple inputs converging on regulatory control elements. The dynamic properties of these elements determine the functionality of genetic networks regulating differentiation and development. Here we propose a method to quantitatively characterize the regulatory output of distant enhancers with a biophysical approach that recursively determines free energies of protein-protein and protein-DNA interactions from experimental analysis of transcriptional reporter libraries. We apply this method to model the Scl-Gata2-Fli1 triad-a network module important for cell fate specification of hematopoietic stem cells. We show that this triad module is inherently bistable with irreversible transitions in response to physiologically relevant signals such as Notch, Bmp4 and Gata1 and we use the model to predict the sensitivity of the network to mutations. We also show that the triad acts as a low-pass filter by switching between steady states only in response to signals that persist for longer than a minimum duration threshold. We have found that the auto-regulation loops connecting the slow-degrading Scl to Gata2 and Fli1 are crucial for this low-pass filtering property. Taken together our analysis not only reveals new insights into hematopoietic stem cell regulatory network functionality but also provides a novel and widely applicable strategy to incorporate experimental measurements into dynamical network models.

On the identification of multiple space dependent ionic parameters in cardiac electrophysiology modelling

Science.gov (United States)

Abidi, Yassine; Bellassoued, Mourad; Mahjoub, Moncef; Zemzemi, Nejib

2018-03-01

In this paper, we consider the inverse problem of space dependent multiple ionic parameters identification in cardiac electrophysiology modelling from a set of observations. We use the monodomain system known as a state-of-the-art model in cardiac electrophysiology and we consider a general Hodgkin-Huxley formalism to describe the ionic exchanges at the microscopic level. This formalism covers many physiological transmembrane potential models including those in cardiac electrophysiology. Our main result is the proof of the uniqueness and a Lipschitz stability estimate of ion channels conductance parameters based on some observations on an arbitrary subdomain. The key idea is a Carleman estimate for a parabolic operator with multiple coefficients and an ordinary differential equation system.

Learned helplessness, discouraged workers, and multiple unemployment equilibria in a search model

OpenAIRE

Bjørnstad, Roger

2001-01-01

Abstract: Unemployment varies strongly between countries with comparable economic structure. Some economists have tried to explain these differences with institutional differences in the labour market. Instead, this paper focuses on a model with multiple equilibria so that the same socioeconomic structure can give rise to different levels of unemployment. Unemployed workers' search efficiency are modelled within an equilibrium search model and lay behind these results. In the model learned...

Multiple Posttranslational Modifications of Leptospira biflexa Proteins as Revealed by Proteomic Analysis.

Science.gov (United States)

Stewart, Philip E; Carroll, James A; Olano, L Rennee; Sturdevant, Daniel E; Rosa, Patricia A

2016-02-15

The saprophyte Leptospira biflexa is an excellent model for studying the physiology of the medically important Leptospira genus, the pathogenic members of which are more recalcitrant to genetic manipulation and have significantly slower in vitro growth. However, relatively little is known regarding the proteome of L. biflexa, limiting its utility as a model for some studies. Therefore, we have generated a proteomic map of both soluble and membrane-associated proteins of L. biflexa during exponential growth and in stationary phase. Using these data, we identified abundantly produced proteins in each cellular fraction and quantified the transcript levels from a subset of these genes using quantitative reverse transcription-PCR (RT-PCR). These proteins should prove useful as cellular markers and as controls for gene expression studies. We also observed a significant number of L. biflexa membrane-associated proteins with multiple isoforms, each having unique isoelectric focusing points. L. biflexa cell lysates were examined for several posttranslational modifications suggested by the protein patterns. Methylation and acetylation of lysine residues were predominately observed in the proteins of the membrane-associated fraction, while phosphorylation was detected mainly among soluble proteins. These three posttranslational modification systems appear to be conserved between the free-living species L. biflexa and the pathogenic species Leptospira interrogans, suggesting an important physiological advantage despite the varied life cycles of the different species. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Model Pembelajaran Berbasis Penstimulasian Multiple Intelligences Siswa

OpenAIRE

Edy Legowo

2017-01-01

Tulisan ini membahas mengenai penerapan teori multiple intelligences dalam pembelajaran di sekolah. Pembahasan diawali dengan menguraikan perkembangan konsep inteligensi dan multiple intelligences. Diikuti dengan menjelaskan dampak teori multiple intelligences dalam bidang pendidikan dan pembelajaran di sekolah. Bagian selanjutnya menguraikan tentang implementasi teori multiple intelligences dalam praktik pembelajaran di kelas yaitu bagaimana pemberian pengalaman belajar siswa yang difasilita...

Logic programming reveals alteration of key transcription factors in multiple myeloma.

Science.gov (United States)

Miannay, Bertrand; Minvielle, Stéphane; Roux, Olivier; Drouin, Pierre; Avet-Loiseau, Hervé; Guérin-Charbonnel, Catherine; Gouraud, Wilfried; Attal, Michel; Facon, Thierry; Munshi, Nikhil C; Moreau, Philippe; Campion, Loïc; Magrangeas, Florence; Guziolowski, Carito

2017-08-23

Innovative approaches combining regulatory networks (RN) and genomic data are needed to extract biological information for a better understanding of diseases, such as cancer, by improving the identification of entities and thereby leading to potential new therapeutic avenues. In this study, we confronted an automatically generated RN with gene expression profiles (GEP) from a cohort of multiple myeloma (MM) patients and normal individuals using global reasoning on the RN causality to identify key-nodes. We modeled each patient by his or her GEP, the RN and the possible automatically detected repairs needed to establish a coherent flow of the information that explains the logic of the GEP. These repairs could represent cancer mutations leading to GEP variability. With this reasoning, unmeasured protein states can be inferred, and we can simulate the impact of a protein perturbation on the RN behavior to identify therapeutic targets. We showed that JUN/FOS and FOXM1 activities are altered in almost all MM patients and identified two survival markers for MM patients. Our results suggest that JUN/FOS-activation has a strong impact on the RN in view of the whole GEP, whereas FOXM1-activation could be an interesting way to perturb an MM subgroup identified by our method.

Testing effect of a drug using multiple nested models for the dose–response

DEFF Research Database (Denmark)

Baayen, C.; Hougaard, P.; Pipper, C. B.

2015-01-01

of the assumed dose–response model. Bretz et al. (2005, Biometrics 61, 738–748) suggested a combined approach, which selects one or more suitable models from a set of candidate models using a multiple comparison procedure. The method initially requires a priori estimates of any non-linear parameters...

A new spatial multiple discrete-continuous modeling approach to land use change analysis.

Science.gov (United States)

2013-09-01

This report formulates a multiple discrete-continuous probit (MDCP) land-use model within a : spatially explicit economic structural framework for land-use change decisions. The spatial : MDCP model is capable of predicting both the type and intensit...

Using hidden Markov models to align multiple sequences.

Science.gov (United States)

Mount, David W

2009-07-01

A hidden Markov model (HMM) is a probabilistic model of a multiple sequence alignment (msa) of proteins. In the model, each column of symbols in the alignment is represented by a frequency distribution of the symbols (called a "state"), and insertions and deletions are represented by other states. One moves through the model along a particular path from state to state in a Markov chain (i.e., random choice of next move), trying to match a given sequence. The next matching symbol is chosen from each state, recording its probability (frequency) and also the probability of going to that state from a previous one (the transition probability). State and transition probabilities are multiplied to obtain a probability of the given sequence. The hidden nature of the HMM is due to the lack of information about the value of a specific state, which is instead represented by a probability distribution over all possible values. This article discusses the advantages and disadvantages of HMMs in msa and presents algorithms for calculating an HMM and the conditions for producing the best HMM.

Steam consumption minimization model in a multiple evaporation effect in a sugar plant

International Nuclear Information System (INIS)

Villada, Fernando; Valencia, Jaime A; Moreno, German; Murillo, J. Joaquin

1992-01-01

In this work, a mathematical model to minimize the steam consumption in a multiple effect evaporation system is shown. The model is based in the dynamic programming technique and the results are tested in a Colombian sugar mill

Eikonal multiple scattering model within the framework of Feynman's positron theory

International Nuclear Information System (INIS)

Tekou, A.

1986-07-01

The Bethe Salpeter equation for nucleon-nucleon, nucleon-nucleus and nucleus-nucleus scattering is eikonalized. Multiple scattering series is obtained. Contributions of three body interations are included. The model presented below may be used to investigate atomic collisions. (author)

Nonresonant Multiple-Pulse Control of Molecular Motions in Liquid

Directory of Open Access Journals (Sweden)

Nikiforov V.G.

2015-01-01

Full Text Available We propose the implementation of the multiple-pulse excitation for manipulation of the molecular contributions to the optically-heterodyne-detected optical-Kerr-effect. The key parameters controlling the specificity of the multiple-pulse excitation scenarios are the pulses durations, the delays between pulses, the relation between the pump pulses amplitudes and the pulses polarizations. We model the high-order optical responses and consider some principles of the scenarios construction. We show that it is possible to adjust the excitation scenario in such a way that the some responses can be removed from detected signal along with the enhancement of the interested response amplitude. The theoretical analysis and first experimental data reveal that the multiple-pulse excitation technique can be useful for the selective spectroscopy of the molecular vibrations and rotations in liquid.

A multiple relevance feedback strategy with positive and negative models.

Directory of Open Access Journals (Sweden)

Yunlong Ma

Full Text Available A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are very poor, it is impossible to extract enough useful terms from a few positive documents. Therefore, the positive feedback strategy is incapable to improve retrieval in this situation. Contrarily, there is a relatively large number of negative documents in the top of the result list, and it has been confirmed that negative feedback strategy is an important and useful way for adapting this scenario by several recent studies. In this paper, we consider a scenario when the search results are so poor that there are at most three relevant documents in the top twenty documents. Then, we conduct a novel study of multiple strategies for relevance feedback using both positive and negative examples from the first-pass retrieval to improve retrieval accuracy for such difficult queries. Experimental results on these TREC collections show that the proposed language model based multiple model feedback method which is generally more effective than both the baseline method and the methods using only positive or negative model.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza

2017-02-08

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Shared Authentic Leadership in Research Teams: Testing a Multiple Mediation Model

NARCIS (Netherlands)

Günter, Hannes; Gardner, William L.; Davis McCauley, Kelly; Randolph-Seng, Brandon; P. Prahbu, Veena

2017-01-01

Research teams face complex leadership and coordination challenges. We propose shared authentic leadership (SAL) as a timely approach to addressing these challenges. Drawing from authentic and functional leadership theories, we posit a multiple mediation model that suggests three mechanisms whereby

Sequential optimization of a terrestrial biosphere model constrained by multiple satellite based products

Science.gov (United States)

Ichii, K.; Kondo, M.; Wang, W.; Hashimoto, H.; Nemani, R. R.

2012-12-01

Various satellite-based spatial products such as evapotranspiration (ET) and gross primary productivity (GPP) are now produced by integration of ground and satellite observations. Effective use of these multiple satellite-based products in terrestrial biosphere models is an important step toward better understanding of terrestrial carbon and water cycles. However, due to the complexity of terrestrial biosphere models with large number of model parameters, the application of these spatial data sets in terrestrial biosphere models is difficult. In this study, we established an effective but simple framework to refine a terrestrial biosphere model, Biome-BGC, using multiple satellite-based products as constraints. We tested the framework in the monsoon Asia region covered by AsiaFlux observations. The framework is based on the hierarchical analysis (Wang et al. 2009) with model parameter optimization constrained by satellite-based spatial data. The Biome-BGC model is separated into several tiers to minimize the freedom of model parameter selections and maximize the independency from the whole model. For example, the snow sub-model is first optimized using MODIS snow cover product, followed by soil water sub-model optimized by satellite-based ET (estimated by an empirical upscaling method; Support Vector Regression (SVR) method; Yang et al. 2007), photosynthesis model optimized by satellite-based GPP (based on SVR method), and respiration and residual carbon cycle models optimized by biomass data. As a result of initial assessment, we found that most of default sub-models (e.g. snow, water cycle and carbon cycle) showed large deviations from remote sensing observations. However, these biases were removed by applying the proposed framework. For example, gross primary productivities were initially underestimated in boreal and temperate forest and overestimated in tropical forests. However, the parameter optimization scheme successfully reduced these biases. Our analysis

Laplace transform analysis of a multiplicative asset transfer model

Science.gov (United States)

Sokolov, Andrey; Melatos, Andrew; Kieu, Tien

2010-07-01

We analyze a simple asset transfer model in which the transfer amount is a fixed fraction f of the giver’s wealth. The model is analyzed in a new way by Laplace transforming the master equation, solving it analytically and numerically for the steady-state distribution, and exploring the solutions for various values of f∈(0,1). The Laplace transform analysis is superior to agent-based simulations as it does not depend on the number of agents, enabling us to study entropy and inequality in regimes that are costly to address with simulations. We demonstrate that Boltzmann entropy is not a suitable (e.g. non-monotonic) measure of disorder in a multiplicative asset transfer system and suggest an asymmetric stochastic process that is equivalent to the asset transfer model.

Modelling of diffuse solar fraction with multiple predictors

Energy Technology Data Exchange (ETDEWEB)

Ridley, Barbara; Boland, John [Centre for Industrial and Applied Mathematics, University of South Australia, Mawson Lakes Boulevard, Mawson Lakes, SA 5095 (Australia); Lauret, Philippe [Laboratoire de Physique du Batiment et des Systemes, University of La Reunion, Reunion (France)

2010-02-15

For some locations both global and diffuse solar radiation are measured. However, for many locations, only global radiation is measured, or inferred from satellite data. For modelling solar energy applications, the amount of radiation on a tilted surface is needed. Since only the direct component on a tilted surface can be calculated from direct on some other plane using trigonometry, we need to have diffuse radiation on the horizontal plane available. There are regression relationships for estimating the diffuse on a tilted surface from diffuse on the horizontal. Models for estimating the diffuse on the horizontal from horizontal global that have been developed in Europe or North America have proved to be inadequate for Australia. Boland et al. developed a validated model for Australian conditions. Boland et al. detailed our recent advances in developing the theoretical framework for the use of the logistic function instead of piecewise linear or simple nonlinear functions and was the first step in identifying the means for developing a generic model for estimating diffuse from global and other predictors. We have developed a multiple predictor model, which is much simpler than previous models, and uses hourly clearness index, daily clearness index, solar altitude, apparent solar time and a measure of persistence of global radiation level as predictors. This model performs marginally better than currently used models for locations in the Northern Hemisphere and substantially better for Southern Hemisphere locations. We suggest it can be used as a universal model. (author)

Iron deposition is independent of cellular inflammation in a cerebral model of multiple sclerosis

Directory of Open Access Journals (Sweden)

Lee Phil

2011-06-01

Full Text Available Abstract Background Perivenular inflammation is a common early pathological feature in multiple sclerosis (MS. A recent hypothesis stated that CNS inflammation is induced by perivenular iron deposits that occur in response to altered blood flow in MS subjects. In order to evaluate this hypothesis, an animal model was developed, called cerebral experimental autoimmune encephalomyelitis (cEAE, which presents with CNS perivascular iron deposits. This model was used to investigate the relationship of iron deposition to inflammation. Methods In order to generate cEAE, mice were given an encephalitogen injection followed by a stereotactic intracerebral injection of TNF-α and IFN-γ. Control animals received encephalitogen followed by an intracerebral injection of saline, or no encephalitogen plus an intracerebral injection of saline or cytokines. Laser Doppler was used to measure cerebral blood flow. MRI and iron histochemistry were used to localize iron deposits. Additional histological procedures were used to localize inflammatory cell infiltrates, microgliosis and astrogliosis. Results Doppler analysis revealed that cEAE mice had a reduction in cerebral blood flow compared to controls. MRI revealed T2 hypointense areas in cEAE animals that spatially correlated with iron deposition around vessels and at some sites of inflammation as detected by iron histochemistry. Vessels with associated iron deposits were distributed across both hemispheres. Mice with cEAE had more iron-labeled vessels compared to controls, but these vessels were not commonly associated with inflammatory cell infiltrates. Some iron-laden vessels had associated microgliosis that was above the background microglial response, and iron deposits were observed within reactive microglia. Vessels with associated astrogliosis were more commonly observed without colocalization of iron deposits. Conclusion The findings indicate that iron deposition around vessels can occur independently of

Assessments of Future Maize Yield Potential Changes in the Korean Peninsula Using Multiple Crop Models

Science.gov (United States)

Kim, S. H.; Lim, C. H.; Kim, J.; Lee, W. K.; Kafatos, M.

2016-12-01

The Korean Peninsula has unique agricultural environment due to the differences of political and socio-economical system between Republic of Korea (SK, hereafter) and Democratic Peoples' Republic of Korea (NK, hereafter). NK has been suffering lack of food supplies caused by natural disasters, land degradation and political failure. The neighboring developed country SK has better agricultural system but very low food self-sufficiency rate. Maize is an important crop in both countries since it is staple food for NK and SK is No. 2 maize importing country in the world after Japan. Therefore, evaluating maize yield potential (Yp) in the two distinct regions is essential to assess food security under climate change and variability. In this study, we utilized multiple process-based crop models, having ability of regional scale assessment, to evaluate maize Yp and assess the model uncertainties -EPIC, GEPIC, DSSAT, and APSIM model that has capability of regional scale expansion (apsimRegions). First we evaluated each crop model for 3 years from 2012 to 2014 using reanalysis data (RDAPS; Regional Data Assimilation and Prediction System produced by Korea Meteorological Agency) and observed yield data. Each model performances were compared over the different regions in the Korean Peninsula having different local climate characteristics. To quantify of the major influence of at each climate variables, we also conducted sensitivity test using 20 years of climatology in historical period from 1981 to 2000. Lastly, the multi-crop model ensemble analysis was performed for future period from 2031 to 2050. The required weather variables projected for mid-century were employed from COordinated Regional climate Downscaling EXperiment (CORDEX) East Asia. The high-resolution climate data were obtained from multiple regional climate models (RCM) driven by multiple climate scenarios projected from multiple global climate models (GCMs) in conjunction with multiple greenhouse gas

An explicit statistical model of learning lexical segmentation using multiple cues

NARCIS (Netherlands)

Çöltekin, Ça ̆grı; Nerbonne, John; Lenci, Alessandro; Padró, Muntsa; Poibeau, Thierry; Villavicencio, Aline

2014-01-01

This paper presents an unsupervised and incremental model of learning segmentation that combines multiple cues whose use by children and adults were attested by experimental studies. The cues we exploit in this study are predictability statistics, phonotactics, lexical stress and partial lexical

Multiple imputation to account for measurement error in marginal structural models

Science.gov (United States)

Edwards, Jessie K.; Cole, Stephen R.; Westreich, Daniel; Crane, Heidi; Eron, Joseph J.; Mathews, W. Christopher; Moore, Richard; Boswell, Stephen L.; Lesko, Catherine R.; Mugavero, Michael J.

2015-01-01

Background Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and non-differential measurement error in a marginal structural model. Methods We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. Results In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality [hazard ratio (HR): 1.2 (95% CI: 0.6, 2.3)]. The HR for current smoking and therapy (0.4 (95% CI: 0.2, 0.7)) was similar to the HR for no smoking and therapy (0.4; 95% CI: 0.2, 0.6). Conclusions Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies. PMID:26214338

Multiple Imputation to Account for Measurement Error in Marginal Structural Models.

Science.gov (United States)

Edwards, Jessie K; Cole, Stephen R; Westreich, Daniel; Crane, Heidi; Eron, Joseph J; Mathews, W Christopher; Moore, Richard; Boswell, Stephen L; Lesko, Catherine R; Mugavero, Michael J

2015-09-01

Marginal structural models are an important tool for observational studies. These models typically assume that variables are measured without error. We describe a method to account for differential and nondifferential measurement error in a marginal structural model. We illustrate the method estimating the joint effects of antiretroviral therapy initiation and current smoking on all-cause mortality in a United States cohort of 12,290 patients with HIV followed for up to 5 years between 1998 and 2011. Smoking status was likely measured with error, but a subset of 3,686 patients who reported smoking status on separate questionnaires composed an internal validation subgroup. We compared a standard joint marginal structural model fit using inverse probability weights to a model that also accounted for misclassification of smoking status using multiple imputation. In the standard analysis, current smoking was not associated with increased risk of mortality. After accounting for misclassification, current smoking without therapy was associated with increased mortality (hazard ratio [HR]: 1.2 [95% confidence interval [CI] = 0.6, 2.3]). The HR for current smoking and therapy [0.4 (95% CI = 0.2, 0.7)] was similar to the HR for no smoking and therapy (0.4; 95% CI = 0.2, 0.6). Multiple imputation can be used to account for measurement error in concert with methods for causal inference to strengthen results from observational studies.

A minimal unified model of disease trajectories captures hallmarks of multiple sclerosis

KAUST Repository

Kannan, Venkateshan; Kiani, Narsis A.; Piehl, Fredrik; Tegner, Jesper

2017-01-01

Multiple Sclerosis (MS) is an autoimmune disease targeting the central nervous system (CNS) causing demyelination and neurodegeneration leading to accumulation of neurological disability. Here we present a minimal, computational model involving

Modeling single versus multiple systems in implicit and explicit memory.

Science.gov (United States)

Starns, Jeffrey J; Ratcliff, Roger; McKoon, Gail

2012-04-01

It is currently controversial whether priming on implicit tasks and discrimination on explicit recognition tests are supported by a single memory system or by multiple, independent systems. In a Psychological Review article, Berry and colleagues used mathematical modeling to address this question and provide compelling evidence against the independent-systems approach. Copyright © 2012 Elsevier Ltd. All rights reserved.

On the practical modeling of conceptual overlap among multiple facets in ontology domain concepts (Mini-thesis)

OpenAIRE

Rodriguez-Castro, Benedicto; Glaser, Hugh; Carr, Leslie

2007-01-01

This report presents a study on the practical modelling of the conceptual overlap that might exist among the multiple facets that define a particular ontology domain concept. The notions of conceptual overlap and facet are defined, together with their relation to scenarios of multiple inheritance in ontology models. Starting from the notion of a value partition, a terminology of ontology modelling constructs is introduced that allows the characterization of two types of conceptual overlap wit...

A tactical supply chain planning model with multiple flexibility options

DEFF Research Database (Denmark)

Esmaeilikia, Masoud; Fahimnia, Behnam; Sarkis, Joeseph

2016-01-01

Supply chain flexibility is widely recognized as an approach to manage uncertainty. Uncertainty in the supply chain may arise from a number of sources such as demand and supply interruptions and lead time variability. A tactical supply chain planning model with multiple flexibility options...... incorporated in sourcing, manufacturing and logistics functions can be used for the analysis of flexibility adjustment in an existing supply chain. This paper develops such a tactical supply chain planning model incorporating a realistic range of flexibility options. A novel solution method is designed...

Modelling and simulation of multiple single - phase induction motor in parallel connection

Directory of Open Access Journals (Sweden)

Sujitjorn, S.

2006-11-01

Full Text Available A mathematical model for parallel connected n-multiple single-phase induction motors in generalized state-space form is proposed in this paper. The motor group draws electric power from one inverter. The model is developed by the dq-frame theory and was tested against four loading scenarios in which satisfactory results were obtained.

Improved double-multiple streamtube model for the Darrieus-type vertical axis wind turbine

Science.gov (United States)

Berg, D. E.

Double streamtube codes model the curved blade (Darrieus-type) vertical axis wind turbine (VAWT) as a double actuator fish arrangement (one half) and use conservation of momentum principles to determine the forces acting on the turbine blades and the turbine performance. Sandia National Laboratories developed a double multiple streamtube model for the VAWT which incorporates the effects of the incident wind boundary layer, nonuniform velocity between the upwind and downwind sections of the rotor, dynamic stall effects and local blade Reynolds number variations. The theory underlying this VAWT model is described, as well as the code capabilities. Code results are compared with experimental data from two VAWT's and with the results from another double multiple streamtube and a vortex filament code. The effects of neglecting dynamic stall and horizontal wind velocity distribution are also illustrated.

A Fractional Supervision Game Model of Multiple Stakeholders and Numerical Simulation

Directory of Open Access Journals (Sweden)

Rongwu Lu

2017-01-01

Full Text Available Considering the popular use of a certain kind of supervision management problem in many fields, we firstly build an ordinary supervision game model of multiple stakeholders. Secondly, a fractional supervision game model is set up and solved based on the theory of fractional calculus and a predictor-corrector numerical approach. Thirdly, the methods of phase diagram and time series graph were applied to simulate and analyse the dynamic process of the fractional order game model. Results of numerical solutions are given to illustrate our conclusions and referred to the practice.

Efficient surrogate models for reliability analysis of systems with multiple failure modes

International Nuclear Information System (INIS)

Bichon, Barron J.; McFarland, John M.; Mahadevan, Sankaran

2011-01-01

Despite many advances in the field of computational reliability analysis, the efficient estimation of the reliability of a system with multiple failure modes remains a persistent challenge. Various sampling and analytical methods are available, but they typically require accepting a tradeoff between accuracy and computational efficiency. In this work, a surrogate-based approach is presented that simultaneously addresses the issues of accuracy, efficiency, and unimportant failure modes. The method is based on the creation of Gaussian process surrogate models that are required to be locally accurate only in the regions of the component limit states that contribute to system failure. This approach to constructing surrogate models is demonstrated to be both an efficient and accurate method for system-level reliability analysis. - Highlights: → Extends efficient global reliability analysis to systems with multiple failure modes. → Constructs locally accurate Gaussian process models of each response. → Highly efficient and accurate method for assessing system reliability. → Effectiveness is demonstrated on several test problems from the literature.

Multiplicity distributions in a thermodynamical model of hadron production in e+e- collisions

International Nuclear Information System (INIS)

Becattini, F.; Giovannini, A.; Lupia, S.

1996-01-01

Predictions of a thermodynamical model of hadron production for multiplicity distributions in e + e - annihilations at LEP and PEP-PETRA centre of mass energies are shown. The production process is described as a two-step process in which primary hadrons emitted from the thermal source decay into final observable particles. The final charged track multiplicity distributions turn out to be of negative binomial type and are in quite good agreement with experimental observations. The average number of clans calculated from fitted negative binomial coincides with the average number of primary hadrons predicted by the thermodynamical model, suggesting that clans should be identified with primary hadrons. (orig.)

Inference regarding multiple structural changes in linear models with endogenous regressors

NARCIS (Netherlands)

Boldea, O.; Hall, A.R.; Han, S.

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares

Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

Directory of Open Access Journals (Sweden)

Tang Xiaofeng

2014-01-01

Full Text Available The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Multiple sclerosis

DEFF Research Database (Denmark)

Stenager, E; Knudsen, L; Jensen, K

1994-01-01

In a cross-sectional study of 94 patients (42 males, 52 females) with definite multiple sclerosis (MS) in the age range 25-55 years, the correlation of neuropsychological tests with the ability to read TV-subtitles and with the use of sedatives is examined. A logistic regression analysis reveals...

Robust anti-synchronization of uncertain chaotic systems based on multiple-kernel least squares support vector machine modeling

International Nuclear Information System (INIS)

Chen Qiang; Ren Xuemei; Na Jing

2011-01-01

Highlights: Model uncertainty of the system is approximated by multiple-kernel LSSVM. Approximation errors and disturbances are compensated in the controller design. Asymptotical anti-synchronization is achieved with model uncertainty and disturbances. Abstract: In this paper, we propose a robust anti-synchronization scheme based on multiple-kernel least squares support vector machine (MK-LSSVM) modeling for two uncertain chaotic systems. The multiple-kernel regression, which is a linear combination of basic kernels, is designed to approximate system uncertainties by constructing a multiple-kernel Lagrangian function and computing the corresponding regression parameters. Then, a robust feedback control based on MK-LSSVM modeling is presented and an improved update law is employed to estimate the unknown bound of the approximation error. The proposed control scheme can guarantee the asymptotic convergence of the anti-synchronization errors in the presence of system uncertainties and external disturbances. Numerical examples are provided to show the effectiveness of the proposed method.

Simultaneous small-sample comparisons in longitudinal or multi-endpoint trials using multiple marginal models

DEFF Research Database (Denmark)

Pallmann, Philip; Ritz, Christian; Hothorn, Ludwig A

2018-01-01

, however only asymptotically. In this paper, we show how to make the approach also applicable to small-sample data problems. Specifically, we discuss the computation of adjusted P values and simultaneous confidence bounds for comparisons of randomised treatment groups as well as for levels......Simultaneous inference in longitudinal, repeated-measures, and multi-endpoint designs can be onerous, especially when trying to find a reasonable joint model from which the interesting effects and covariances are estimated. A novel statistical approach known as multiple marginal models greatly...... simplifies the modelling process: the core idea is to "marginalise" the problem and fit multiple small models to different portions of the data, and then estimate the overall covariance matrix in a subsequent, separate step. Using these estimates guarantees strong control of the family-wise error rate...

Generation of connectivity-preserving surface models of multiple sclerosis lesions.

Science.gov (United States)

Meruvia-Pastor, Oscar; Xiao, Mei; Soh, Jung; Sensen, Christoph W

2011-01-01

Progression of multiple sclerosis (MS) results in brain lesions caused by white matter inflammation. MS lesions have various shapes, sizes and locations, affecting cognitive abilities of patients to different extents. To facilitate the visualization of the brain lesion distribution, we have developed a software tool to build 3D surface models of MS lesions. This tool allows users to create 3D models of lesions quickly and to visualize the lesions and brain tissues using various visual attributes and configurations. The software package is based on breadth-first search based 3D connected component analysis and a 3D flood-fill based region growing algorithm to generate 3D models from binary or non-binary segmented medical image stacks.

Statistical models for quantifying diagnostic accuracy with multiple lesions per patient

NARCIS (Netherlands)

Zwinderman, Aeilko H.; Glas, Afina S.; Bossuyt, Patrick M.; Florie, Jasper; Bipat, Shandra; Stoker, Jaap

2008-01-01

We propose random-effects models to summarize and quantify the accuracy of the diagnosis of multiple lesions on a single image without assuming independence between lesions. The number of false-positive lesions was assumed to be distributed as a Poisson mixture, and the proportion of true-positive

Anti-inflammatory mechanisms of IFN-γ studied in experimental autoimmune encephalomyelitis reveal neutrophils as a potential target in multiple sclerosis

Directory of Open Access Journals (Sweden)

Nichole M Miller

2015-08-01

Full Text Available Multiple sclerosis (MS is an autoimmune disease of the central nervous system (CNS mediated by T helper (h1 and/or Th17 CD4 T cells that drive inflammatory lesion development along with demyelination and neuronal damage. Defects in immune regulatory mechanisms are thought to play a role in the pathogenesis of MS. While an early clinical trial indicated that IFN-γ administration was detrimental to MS, studies in the mouse model of MS, experimental autoimmune encephalomyelitis (EAE, indicated that IFN-γ exhibits a number of anti-inflammatory properties within the CNS. These mechanisms include inhibition of IL-17 production, induction of regulatory T cells, T cell apoptosis and regulation of chemokine production. Mice deficient in IFN-γ or its receptor were instrumental in deciphering the anti-inflammatory properties of IFN-γ in the CNS. In particular, they revealed that IFN-γ is a major regulator of neutrophil recruitment into the CNS, which by a variety of mechanisms including disruption of the blood-brain-barrier (BBB and production of reactive oxygen species are thought to contribute to the onset and progression of EAE. Neutrophils were also shown to be instrumental in EAE relapses. To date neutrophils have not been appreciated as a driver of MS, but more recently based largely on the strong EAE data this view is being reevaluated by some investigators in the field.

Multiple-relaxation-time lattice Boltzmann model for compressible fluids

International Nuclear Information System (INIS)

Chen Feng; Xu Aiguo; Zhang Guangcai; Li Yingjun

2011-01-01

We present an energy-conserving multiple-relaxation-time finite difference lattice Boltzmann model for compressible flows. The collision step is first calculated in the moment space and then mapped back to the velocity space. The moment space and corresponding transformation matrix are constructed according to the group representation theory. Equilibria of the nonconserved moments are chosen according to the need of recovering compressible Navier-Stokes equations through the Chapman-Enskog expansion. Numerical experiments showed that compressible flows with strong shocks can be well simulated by the present model. The new model works for both low and high speeds compressible flows. It contains more physical information and has better numerical stability and accuracy than its single-relaxation-time version. - Highlights: → We present an energy-conserving MRT finite-difference LB model. → The moment space is constructed according to the group representation theory. → The new model works for both low and high speeds compressible flows. → It has better numerical stability and wider applicable range than its SRT version.

Multiple myeloma

International Nuclear Information System (INIS)

Sohn, Jeong Ick; Ha, Choon Ho; Choi, Karp Shik

1994-01-01

Multiple myeloma is a malignant plasma cell tumor that is thought to originate proliferation of a single clone of abnormal plasma cell resulting production of a whole monoclonal paraprotein. The authors experienced a case of multiple myeloma with severe mandibular osteolytic lesions in 46-year-old female. As a result of careful analysis of clinical, radiological, histopathological features, and laboratory findings, we diagnosed it as multiple myeloma, and the following results were obtained. 1. Main clinical symptoms were intermittent dull pain on the mandibular body area, abnormal sensation of lip and pain due to the fracture on the right clavicle. 2. Laboratory findings revealed M-spike, reversed serum albumin-globulin ratio, markedly elevated ESR and hypercalcemia. 3. Radiographically, multiple osteolytic punched-out radiolucencies were evident on the skull, zygoma, jaw bones, ribs, clavicle and upper extremities. Enlarged liver and increased uptakes on the lesional sites in RN scan were also observed. 4. Histopathologically, markedly hypercellular marrow with sheets of plasmoblasts and megakaryocytes were also observed.

Improving multiple-point-based a priori models for inverse problems by combining Sequential Simulation with the Frequency Matching Method

DEFF Research Database (Denmark)

Cordua, Knud Skou; Hansen, Thomas Mejer; Lange, Katrine

In order to move beyond simplified covariance based a priori models, which are typically used for inverse problems, more complex multiple-point-based a priori models have to be considered. By means of marginal probability distributions ‘learned’ from a training image, sequential simulation has...... proven to be an efficient way of obtaining multiple realizations that honor the same multiple-point statistics as the training image. The frequency matching method provides an alternative way of formulating multiple-point-based a priori models. In this strategy the pattern frequency distributions (i.......e. marginals) of the training image and a subsurface model are matched in order to obtain a solution with the same multiple-point statistics as the training image. Sequential Gibbs sampling is a simulation strategy that provides an efficient way of applying sequential simulation based algorithms as a priori...

Identification of Multiple-Mode Linear Models Based on Particle Swarm Optimizer with Cyclic Network Mechanism

Directory of Open Access Journals (Sweden)

Tae-Hyoung Kim

2017-01-01

Full Text Available This paper studies the metaheuristic optimizer-based direct identification of a multiple-mode system consisting of a finite set of linear regression representations of subsystems. To this end, the concept of a multiple-mode linear regression model is first introduced, and its identification issues are established. A method for reducing the identification problem for multiple-mode models to an optimization problem is also described in detail. Then, to overcome the difficulties that arise because the formulated optimization problem is inherently ill-conditioned and nonconvex, the cyclic-network-topology-based constrained particle swarm optimizer (CNT-CPSO is introduced, and a concrete procedure for the CNT-CPSO-based identification methodology is developed. This scheme requires no prior knowledge of the mode transitions between subsystems and, unlike some conventional methods, can handle a large amount of data without difficulty during the identification process. This is one of the distinguishing features of the proposed method. The paper also considers an extension of the CNT-CPSO-based identification scheme that makes it possible to simultaneously obtain both the optimal parameters of the multiple submodels and a certain decision parameter involved in the mode transition criteria. Finally, an experimental setup using a DC motor system is established to demonstrate the practical usability of the proposed metaheuristic optimizer-based identification scheme for developing a multiple-mode linear regression model.

Validation of a multiple compartment model for the transport of cesium through animals

International Nuclear Information System (INIS)

Assimakopoulos, P.A.; Ioannides, K.G.; Pakou, A.A.

1991-01-01

A general multiple compartment model, which describes the transport of trace elements through animals is presented. This model considers a system of K interconnected compartments of volume V i , i = 1,2,....,K, each containing, at a given time t, N i molecules of a trace substance. (5 figs.)

Monitoring urban greenness dynamics using multiple endmember spectral mixture analysis.

Directory of Open Access Journals (Sweden)

Muye Gan

Full Text Available Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents' quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development.

Unfolding mechanism of thrombin-binding aptamer revealed by molecular dynamics simulation and Markov State Model.

Science.gov (United States)

Zeng, Xiaojun; Zhang, Liyun; Xiao, Xiuchan; Jiang, Yuanyuan; Guo, Yanzhi; Yu, Xinyan; Pu, Xuemei; Li, Menglong

2016-04-05

Thrombin-binding aptamer (TBA) with the sequence 5'GGTTGGTGTGGTTGG3' could fold into G-quadruplex, which correlates with functionally important genomic regionsis. However, unfolding mechanism involved in the structural stability of G-quadruplex has not been satisfactorily elucidated on experiments so far. Herein, we studied the unfolding pathway of TBA by a combination of molecular dynamics simulation (MD) and Markov State Model (MSM). Our results revealed that the unfolding of TBA is not a simple two-state process but proceeds along multiple pathways with multistate intermediates. One high flux confirms some observations from NMR experiment. Another high flux exhibits a different and simpler unfolding pathway with less intermediates. Two important intermediate states were identified. One is similar to the G-triplex reported in the folding of G-quadruplex, but lack of H-bonding between guanines in the upper plane. More importantly, another intermediate state acting as a connector to link the folding region and the unfolding one, was the first time identified, which exhibits higher population and stability than the G-triplex-like intermediate. These results will provide valuable information for extending our understanding the folding landscape of G-quadruplex formation.

Inferring Ice Thickness from a Glacier Dynamics Model and Multiple Surface Datasets.

Science.gov (United States)

Guan, Y.; Haran, M.; Pollard, D.

2017-12-01

The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea level rise. Understanding the current state of WAIS is therefore of great interest. WAIS is drained by fast-flowing glaciers which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice sheet surface data sets with a glacier dynamics model. Our approach allows us to (1) infer important parameters describing the glacier dynamics, (2) learn about ice sheet thickness, and (3) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

47 CFR 2.924 - Marketing of electrically identical equipment having multiple trade names and models or type...

Science.gov (United States)

2010-10-01

... Authorizations § 2.924 Marketing of electrically identical equipment having multiple trade names and models or... 47 Telecommunication 1 2010-10-01 2010-10-01 false Marketing of electrically identical equipment having multiple trade names and models or type numbers under the same FCC Identifier. 2.924 Section 2.924...

Rapidity correlations at fixed multiplicity in cluster emission models

CERN Document Server

Berger, M C

1975-01-01

Rapidity correlations in the central region among hadrons produced in proton-proton collisions of fixed final state multiplicity n at NAL and ISR energies are investigated in a two-step framework in which clusters of hadrons are emitted essentially independently, via a multiperipheral-like model, and decay isotropically. For n>or approximately=/sup 1///sub 2/(n), these semi-inclusive distributions are controlled by the reaction mechanism which dominates production in the central region. Thus, data offer cleaner insight into the properties of this mechanism than can be obtained from fully inclusive spectra. A method of experimental analysis is suggested to facilitate the extraction of new dynamical information. It is shown that the n independence of the magnitude of semi-inclusive correlation functions reflects directly the structure of the internal cluster multiplicity distribution. This conclusion is independent of certain assumptions concerning the form of the single cluster density in rapidity space. (23 r...

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

Science.gov (United States)

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

2017-07-01

An extension of the point kinetics model is developed to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If the detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. The spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.

Entropic multiple-relaxation-time multirange pseudopotential lattice Boltzmann model for two-phase flow

Science.gov (United States)

Qin, Feifei; Mazloomi Moqaddam, Ali; Kang, Qinjun; Derome, Dominique; Carmeliet, Jan

2018-03-01

An entropic multiple-relaxation-time lattice Boltzmann approach is coupled to a multirange Shan-Chen pseudopotential model to study the two-phase flow. Compared with previous multiple-relaxation-time multiphase models, this model is stable and accurate for the simulation of a two-phase flow in a much wider range of viscosity and surface tension at a high liquid-vapor density ratio. A stationary droplet surrounded by equilibrium vapor is first simulated to validate this model using the coexistence curve and Laplace's law. Then, two series of droplet impact behavior, on a liquid film and a flat surface, are simulated in comparison with theoretical or experimental results. Droplet impact on a liquid film is simulated for different Reynolds numbers at high Weber numbers. With the increase of the Sommerfeld parameter, onset of splashing is observed and multiple secondary droplets occur. The droplet spreading ratio agrees well with the square root of time law and is found to be independent of Reynolds number. Moreover, shapes of simulated droplets impacting hydrophilic and superhydrophobic flat surfaces show good agreement with experimental observations through the entire dynamic process. The maximum spreading ratio of a droplet impacting the superhydrophobic flat surface is studied for a large range of Weber numbers. Results show that the rescaled maximum spreading ratios are in good agreement with a universal scaling law. This series of simulations demonstrates that the proposed model accurately captures the complex fluid-fluid and fluid-solid interfacial physical processes for a wide range of Reynolds and Weber numbers at high density ratios.

Direction of Effects in Multiple Linear Regression Models.

Science.gov (United States)

Wiedermann, Wolfgang; von Eye, Alexander

2015-01-01

Previous studies analyzed asymmetric properties of the Pearson correlation coefficient using higher than second order moments. These asymmetric properties can be used to determine the direction of dependence in a linear regression setting (i.e., establish which of two variables is more likely to be on the outcome side) within the framework of cross-sectional observational data. Extant approaches are restricted to the bivariate regression case. The present contribution extends the direction of dependence methodology to a multiple linear regression setting by analyzing distributional properties of residuals of competing multiple regression models. It is shown that, under certain conditions, the third central moments of estimated regression residuals can be used to decide upon direction of effects. In addition, three different approaches for statistical inference are discussed: a combined D'Agostino normality test, a skewness difference test, and a bootstrap difference test. Type I error and power of the procedures are assessed using Monte Carlo simulations, and an empirical example is provided for illustrative purposes. In the discussion, issues concerning the quality of psychological data, possible extensions of the proposed methods to the fourth central moment of regression residuals, and potential applications are addressed.

Integrated model of multiple kernel learning and differential evolution for EUR/USD trading.

Science.gov (United States)

Deng, Shangkun; Sakurai, Akito

2014-01-01

Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL) with differential evolution (DE) for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI), while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX) currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Integrated Model of Multiple Kernel Learning and Differential Evolution for EUR/USD Trading

Directory of Open Access Journals (Sweden)

Shangkun Deng

2014-01-01

Full Text Available Currency trading is an important area for individual investors, government policy decisions, and organization investments. In this study, we propose a hybrid approach referred to as MKL-DE, which combines multiple kernel learning (MKL with differential evolution (DE for trading a currency pair. MKL is used to learn a model that predicts changes in the target currency pair, whereas DE is used to generate the buy and sell signals for the target currency pair based on the relative strength index (RSI, while it is also combined with MKL as a trading signal. The new hybrid implementation is applied to EUR/USD trading, which is the most traded foreign exchange (FX currency pair. MKL is essential for utilizing information from multiple information sources and DE is essential for formulating a trading rule based on a mixture of discrete structures and continuous parameters. Initially, the prediction model optimized by MKL predicts the returns based on a technical indicator called the moving average convergence and divergence. Next, a combined trading signal is optimized by DE using the inputs from the prediction model and technical indicator RSI obtained from multiple timeframes. The experimental results showed that trading using the prediction learned by MKL yielded consistent profits.

Fast solar radiation pressure modelling with ray tracing and multiple reflections

Science.gov (United States)

Li, Zhen; Ziebart, Marek; Bhattarai, Santosh; Harrison, David; Grey, Stuart

2018-05-01

Physics based SRP (Solar Radiation Pressure) models using ray tracing methods are powerful tools when modelling the forces on complex real world space vehicles. Currently high resolution (1 mm) ray tracing with secondary intersections is done on high performance computers at UCL (University College London). This study introduces the BVH (Bounding Volume Hierarchy) into the ray tracing approach for physics based SRP modelling and makes it possible to run high resolution analysis on personal computers. The ray tracer is both general and efficient enough to cope with the complex shape of satellites and multiple reflections (three or more, with no upper limit). In this study, the traditional ray tracing technique is introduced in the first place and then the BVH is integrated into the ray tracing. Four aspects of the ray tracer were tested for investigating the performance including runtime, accuracy, the effects of multiple reflections and the effects of pixel array resolution.Test results in runtime on GPS IIR and Galileo IOV (In Orbit Validation) satellites show that the BVH can make the force model computation 30-50 times faster. The ray tracer has an absolute accuracy of several nanonewtons by comparing the test results for spheres and planes with the analytical computations. The multiple reflection effects are investigated both in the intersection number and acceleration on GPS IIR, Galileo IOV and Sentinel-1 spacecraft. Considering the number of intersections, the 3rd reflection can capture 99.12 %, 99.14 % , and 91.34 % of the total reflections for GPS IIR, Galileo IOV satellite bus and the Sentinel-1 spacecraft respectively. In terms of the multiple reflection effects on the acceleration, the secondary reflection effect for Galileo IOV satellite and Sentinel-1 can reach 0.2 nm /s2 and 0.4 nm /s2 respectively. The error percentage in the accelerations magnitude results show that the 3rd reflection should be considered in order to make it less than 0.035 % . The

Scaling of multiplicity distribution in hadron collisions and diffractive-excitation like models

International Nuclear Information System (INIS)

Buras, A.J.; Dethlefsen, J.M.; Koba, Z.

1974-01-01

Multiplicity distribution of secondary particles in inelastic hadron collision at high energy is studied in the semiclassical impact parameter representation. The scaling function is shown to consist of two factors: one geometrical and the other dynamical. We propose a specific choice of these factors, which describe satisfactorily the elastic scattering, the ratio of elastic to total cross-section and the simple scaling behaviour of multiplicity distribution in p-p collisions. Two versions of diffractive-excitation like models (global and local excitation) are presented as interpretation of our choice of dynamical factor. (author)

Slow walking model for children with multiple disabilities via an application of humanoid robot

Science.gov (United States)

Wang, ZeFeng; Peyrodie, Laurent; Cao, Hua; Agnani, Olivier; Watelain, Eric; Wang, HaoPing

2016-02-01

Walk training research with children having multiple disabilities is presented. Orthosis aid in walking for children with multiple disabilities such as Cerebral Palsy continues to be a clinical and technological challenge. In order to reduce pain and improve treatment strategies, an intermediate structure - humanoid robot NAO - is proposed as an assay platform to study walking training models, to be transferred to future special exoskeletons for children. A suitable and stable walking model is proposed for walk training. It would be simulated and tested on NAO. This comparative study of zero moment point (ZMP) supports polygons and energy consumption validates the model as more stable than the conventional NAO. Accordingly direction variation of the center of mass and the slopes of linear regression knee/ankle angles, the Slow Walk model faithfully emulates the gait pattern of children.

Power Allocation in Multiple Access Networks: Implementation Aspects via Verhulst and Perron-Frobenius Models

Directory of Open Access Journals (Sweden)

Fábio Engel de Camargo

2012-11-01

Full Text Available In this work, the Verhulst model and the Perron-Frobenius theorem are applied on the power control problem which is a concern in multiple access communication networks due to the multiple access interference. This paper deals with the performance versus complexity tradeoff of both power control algorithm (PCA, as well as highlights the computational cost aspects regarding the implementability of distributed PCA (DPCA version for both algorithms. As a proof-of-concept the DPCA implementation is carried out deploying a commercial point-floating DSP platform. Numerical results in terms of DSP cycles and computational time as well indicate a feasibility of implementing the PCA-Verhulst model in 2G and 3G cellular systems; b high computational cost for the PCA-Perron-Frobenius model.

Multiple Concurrent Visual-Motor Mappings: Implications for Models of Adaptation

Science.gov (United States)

Cunningham, H. A.; Welch, Robert B.

1994-01-01

Previous research on adaptation to visual-motor rearrangement suggests that the central nervous system represents accurately only 1 visual-motor mapping at a time. This idea was examined in 3 experiments where subjects tracked a moving target under repeated alternations between 2 initially interfering mappings (the 'normal' mapping characteristic of computer input devices and a 108' rotation of the normal mapping). Alternation between the 2 mappings led to significant reduction in error under the rotated mapping and significant reduction in the adaptation aftereffect ordinarily caused by switching between mappings. Color as a discriminative cue, interference versus decay in adaptation aftereffect, and intermanual transfer were also examined. The results reveal a capacity for multiple concurrent visual-motor mappings, possibly controlled by a parametric process near the motor output stage of processing.

An improved null model for assessing the net effects of multiple stressors on communities.

Science.gov (United States)

Thompson, Patrick L; MacLennan, Megan M; Vinebrooke, Rolf D

2018-01-01

Ecological stressors (i.e., environmental factors outside their normal range of variation) can mediate each other through their interactions, leading to unexpected combined effects on communities. Determining whether the net effect of stressors is ecologically surprising requires comparing their cumulative impact to a null model that represents the linear combination of their individual effects (i.e., an additive expectation). However, we show that standard additive and multiplicative null models that base their predictions on the effects of single stressors on community properties (e.g., species richness or biomass) do not provide this linear expectation, leading to incorrect interpretations of antagonistic and synergistic responses by communities. We present an alternative, the compositional null model, which instead bases its predictions on the effects of stressors on individual species, and then aggregates them to the community level. Simulations demonstrate the improved ability of the compositional null model to accurately provide a linear expectation of the net effect of stressors. We simulate the response of communities to paired stressors that affect species in a purely additive fashion and compare the relative abilities of the compositional null model and two standard community property null models (additive and multiplicative) to predict these linear changes in species richness and community biomass across different combinations (both positive, negative, or opposite) and intensities of stressors. The compositional model predicts the linear effects of multiple stressors under almost all scenarios, allowing for proper classification of net effects, whereas the standard null models do not. Our findings suggest that current estimates of the prevalence of ecological surprises on communities based on community property null models are unreliable, and should be improved by integrating the responses of individual species to the community level as does our

Model selection in Bayesian segmentation of multiple DNA alignments.

Science.gov (United States)

Oldmeadow, Christopher; Keith, Jonathan M

2011-03-01

The analysis of multiple sequence alignments is allowing researchers to glean valuable insights into evolution, as well as identify genomic regions that may be functional, or discover novel classes of functional elements. Understanding the distribution of conservation levels that constitutes the evolutionary landscape is crucial to distinguishing functional regions from non-functional. Recent evidence suggests that a binary classification of evolutionary rates is inappropriate for this purpose and finds only highly conserved functional elements. Given that the distribution of evolutionary rates is multi-modal, determining the number of modes is of paramount concern. Through simulation, we evaluate the performance of a number of information criterion approaches derived from MCMC simulations in determining the dimension of a model. We utilize a deviance information criterion (DIC) approximation that is more robust than the approximations from other information criteria, and show our information criteria approximations do not produce superfluous modes when estimating conservation distributions under a variety of circumstances. We analyse the distribution of conservation for a multiple alignment comprising four primate species and mouse, and repeat this on two additional multiple alignments of similar species. We find evidence of six distinct classes of evolutionary rates that appear to be robust to the species used. Source code and data are available at http://dl.dropbox.com/u/477240/changept.zip.

Mathematical model quantifies multiple daylight exposure and burial events for rock surfaces using luminescence dating

International Nuclear Information System (INIS)

Freiesleben, Trine; Sohbati, Reza; Murray, Andrew; Jain, Mayank; Al Khasawneh, Sahar; Hvidt, Søren; Jakobsen, Bo

2015-01-01

Interest in the optically stimulated luminescence (OSL) dating of rock surfaces has increased significantly over the last few years, as the potential of the method has been explored. It has been realized that luminescence-depth profiles show qualitative evidence for multiple daylight exposure and burial events. To quantify both burial and exposure events a new mathematical model is developed by expanding the existing models of evolution of luminescence–depth profiles, to include repeated sequential events of burial and exposure to daylight. This new model is applied to an infrared stimulated luminescence-depth profile from a feldspar-rich granite cobble from an archaeological site near Aarhus, Denmark. This profile shows qualitative evidence for multiple daylight exposure and burial events; these are quantified using the model developed here. By determining the burial ages from the surface layer of the cobble and by fitting the new model to the luminescence profile, it is concluded that the cobble was well bleached before burial. This indicates that the OSL burial age is likely to be reliable. In addition, a recent known exposure event provides an approximate calibration for older daylight exposure events. This study confirms the suggestion that rock surfaces contain a record of exposure and burial history, and that these events can be quantified. The burial age of rock surfaces can thus be dated with confidence, based on a knowledge of their pre-burial light exposure; it may also be possible to determine the length of a fossil exposure, using a known natural light exposure as calibration. - Highlights: • Evidence for multiple exposure and burial events in the history of a single cobble. • OSL rock surface dating model improved to include multiple burial/exposure cycles. • Application of the new model quantifies burial and exposure events.

Multiple Model Predictive Hybrid Feedforward Control of Fuel Cell Power Generation System

Directory of Open Access Journals (Sweden)

Long Wu

2018-02-01

Full Text Available Solid oxide fuel cell (SOFC is widely considered as an alternative solution among the family of the sustainable distributed generation. Its load flexibility enables it adjusting the power output to meet the requirements from power grid balance. Although promising, its control is challenging when faced with load changes, during which the output voltage is required to be maintained as constant and fuel utilization rate kept within a safe range. Moreover, it makes the control even more intractable because of the multivariable coupling and strong nonlinearity within the wide-range operating conditions. To this end, this paper developed a multiple model predictive control strategy for reliable SOFC operation. The resistance load is regarded as a measurable disturbance, which is an input to the model predictive control as feedforward compensation. The coupling is accommodated by the receding horizon optimization. The nonlinearity is mitigated by the multiple linear models, the weighted sum of which serves as the final control execution. The merits of the proposed control structure are demonstrated by the simulation results.

Stepwise Analysis of Differential Item Functioning Based on Multiple-Group Partial Credit Model.

Science.gov (United States)

Muraki, Eiji

1999-01-01

Extended an Item Response Theory (IRT) method for detection of differential item functioning to the partial credit model and applied the method to simulated data using a stepwise procedure. Then applied the stepwise DIF analysis based on the multiple-group partial credit model to writing trend data from the National Assessment of Educational…

Localization of a small change in a multiple scattering environment without modeling of the actual medium.

Science.gov (United States)

Rakotonarivo, S T; Walker, S C; Kuperman, W A; Roux, P

2011-12-01

A method to actively localize a small perturbation in a multiple scattering medium using a collection of remote acoustic sensors is presented. The approach requires only minimal modeling and no knowledge of the scatterer distribution and properties of the scattering medium and the perturbation. The medium is ensonified before and after a perturbation is introduced. The coherent difference between the measured signals then reveals all field components that have interacted with the perturbation. A simple single scatter filter (that ignores the presence of the medium scatterers) is matched to the earliest change of the coherent difference to localize the perturbation. Using a multi-source/receiver laboratory setup in air, the technique has been successfully tested with experimental data at frequencies varying from 30 to 60 kHz (wavelength ranging from 0.5 to 1 cm) for cm-scale scatterers in a scattering medium with a size two to five times bigger than its transport mean free path. © 2011 Acoustical Society of America

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

KAUST Repository

Sang, Huiyan; Jun, Mikyoung; Huang, Jianhua Z.

2011-01-01

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models

Biosensor reveals multiple sources for mitochondrial NAD⁺.

Science.gov (United States)

Cambronne, Xiaolu A; Stewart, Melissa L; Kim, DongHo; Jones-Brunette, Amber M; Morgan, Rory K; Farrens, David L; Cohen, Michael S; Goodman, Richard H

2016-06-17

Nicotinamide adenine dinucleotide (NAD(+)) is an essential substrate for sirtuins and poly(adenosine diphosphate-ribose) polymerases (PARPs), which are NAD(+)-consuming enzymes localized in the nucleus, cytosol, and mitochondria. Fluctuations in NAD(+) concentrations within these subcellular compartments are thought to regulate the activity of NAD(+)-consuming enzymes; however, the challenge in measuring compartmentalized NAD(+) in cells has precluded direct evidence for this type of regulation. We describe the development of a genetically encoded fluorescent biosensor for directly monitoring free NAD(+) concentrations in subcellular compartments. We found that the concentrations of free NAD(+) in the nucleus, cytoplasm, and mitochondria approximate the Michaelis constants for sirtuins and PARPs in their respective compartments. Systematic depletion of enzymes that catalyze the final step of NAD(+) biosynthesis revealed cell-specific mechanisms for maintaining mitochondrial NAD(+) concentrations. Copyright © 2016, American Association for the Advancement of Science.

MULTIPLE OBJECTS

Directory of Open Access Journals (Sweden)

A. A. Bosov

2015-04-01

Full Text Available Purpose. The development of complicated techniques of production and management processes, information systems, computer science, applied objects of systems theory and others requires improvement of mathematical methods, new approaches for researches of application systems. And the variety and diversity of subject systems makes necessary the development of a model that generalizes the classical sets and their development – sets of sets. Multiple objects unlike sets are constructed by multiple structures and represented by the structure and content. The aim of the work is the analysis of multiple structures, generating multiple objects, the further development of operations on these objects in application systems. Methodology. To achieve the objectives of the researches, the structure of multiple objects represents as constructive trio, consisting of media, signatures and axiomatic. Multiple object is determined by the structure and content, as well as represented by hybrid superposition, composed of sets, multi-sets, ordered sets (lists and heterogeneous sets (sequences, corteges. Findings. In this paper we study the properties and characteristics of the components of hybrid multiple objects of complex systems, proposed assessments of their complexity, shown the rules of internal and external operations on objects of implementation. We introduce the relation of arbitrary order over multiple objects, we define the description of functions and display on objects of multiple structures. Originality.In this paper we consider the development of multiple structures, generating multiple objects.Practical value. The transition from the abstract to the subject of multiple structures requires the transformation of the system and multiple objects. Transformation involves three successive stages: specification (binding to the domain, interpretation (multiple sites and particularization (goals. The proposed describe systems approach based on hybrid sets

Development of Physics and Control of Multiple Forcing Mechanisms for the Alaska Tsunami Forecast Model

Science.gov (United States)

Bahng, B.; Whitmore, P.; Macpherson, K. A.; Knight, W. R.

2016-12-01

The Alaska Tsunami Forecast Model (ATFM) is a numerical model used to forecast propagation and inundation of tsunamis generated by earthquakes or other mechanisms in either the Pacific Ocean, Atlantic Ocean or Gulf of Mexico. At the U.S. National Tsunami Warning Center (NTWC), the use of the model has been mainly for tsunami pre-computation due to earthquakes. That is, results for hundreds of hypothetical events are computed before alerts, and are accessed and calibrated with observations during tsunamis to immediately produce forecasts. The model has also been used for tsunami hindcasting due to submarine landslides and due to atmospheric pressure jumps, but in a very case-specific and somewhat limited manner. ATFM uses the non-linear, depth-averaged, shallow-water equations of motion with multiply nested grids in two-way communications between domains of each parent-child pair as waves approach coastal waters. The shallow-water wave physics is readily applicable to all of the above tsunamis as well as to tides. Recently, the model has been expanded to include multiple forcing mechanisms in a systematic fashion, and to enhance the model physics for non-earthquake events.ATFM is now able to handle multiple source mechanisms, either individually or jointly, which include earthquake, submarine landslide, meteo-tsunami and tidal forcing. As for earthquakes, the source can be a single unit source or multiple, interacting source blocks. Horizontal slip contribution can be added to the sea-floor displacement. The model now includes submarine landslide physics, modeling the source either as a rigid slump, or as a viscous fluid. Additional shallow-water physics have been implemented for the viscous submarine landslides. With rigid slumping, any trajectory can be followed. As for meteo-tsunami, the forcing mechanism is capable of following any trajectory shape. Wind stress physics has also been implemented for the meteo-tsunami case, if required. As an example of multiple

Bayesian models based on test statistics for multiple hypothesis testing problems.

Science.gov (United States)

Ji, Yuan; Lu, Yiling; Mills, Gordon B

2008-04-01

We propose a Bayesian method for the problem of multiple hypothesis testing that is routinely encountered in bioinformatics research, such as the differential gene expression analysis. Our algorithm is based on modeling the distributions of test statistics under both null and alternative hypotheses. We substantially reduce the complexity of the process of defining posterior model probabilities by modeling the test statistics directly instead of modeling the full data. Computationally, we apply a Bayesian FDR approach to control the number of rejections of null hypotheses. To check if our model assumptions for the test statistics are valid for various bioinformatics experiments, we also propose a simple graphical model-assessment tool. Using extensive simulations, we demonstrate the performance of our models and the utility of the model-assessment tool. In the end, we apply the proposed methodology to an siRNA screening and a gene expression experiment.

Formation of multiple networks

DEFF Research Database (Denmark)

Magnani, Matteo; Rossi, Luca

2013-01-01

we introduce the first network formation model for multiple networks. Network formation models are among the most popular tools in traditional network studies, because of both their practical and theoretical impact. However, existing models are not sufficient to describe the generation of multiple...

Optimal Retail Price Model for Partial Consignment to Multiple Retailers

Directory of Open Access Journals (Sweden)

Po-Yu Chen

2017-01-01

Full Text Available This paper investigates the product pricing decision-making problem under a consignment stock policy in a two-level supply chain composed of one supplier and multiple retailers. The effects of the supplier’s wholesale prices and its partial inventory cost absorption of the retail prices of retailers with different market shares are investigated. In the partial product consignment model this paper proposes, the seller and the retailers each absorb part of the inventory costs. This model also provides general solutions for the complete product consignment and the traditional policy that adopts no product consignment. In other words, both the complete consignment and nonconsignment models are extensions of the proposed model (i.e., special cases. Research results indicated that the optimal retail price must be between 1/2 (50% and 2/3 (66.67% times the upper limit of the gross profit. This study also explored the results and influence of parameter variations on optimal retail price in the model.

Characterising and modelling regolith stratigraphy using multiple geophysical techniques

Science.gov (United States)

Thomas, M.; Cremasco, D.; Fotheringham, T.; Hatch, M. A.; Triantifillis, J.; Wilford, J.

2013-12-01

Regolith is the weathered, typically mineral-rich layer from fresh bedrock to land surface. It encompasses soil (A, E and B horizons) that has undergone pedogenesis. Below is the weathered C horizon that retains at least some of the original rocky fabric and structure. At the base of this is the lower regolith boundary of continuous hard bedrock (the R horizon). Regolith may be absent, e.g. at rocky outcrops, or may be many 10's of metres deep. Comparatively little is known about regolith, and critical questions remain regarding composition and characteristics - especially deeper where the challenge of collecting reliable data increases with depth. In Australia research is underway to characterise and map regolith using consistent methods at scales ranging from local (e.g. hillslope) to continental scales. These efforts are driven by many research needs, including Critical Zone modelling and simulation. Pilot research in South Australia using digitally-based environmental correlation techniques modelled the depth to bedrock to 9 m for an upland area of 128 000 ha. One finding was the inability to reliably model local scale depth variations over horizontal distances of 2 - 3 m and vertical distances of 1 - 2 m. The need to better characterise variations in regolith to strengthen models at these fine scales was discussed. Addressing this need, we describe high intensity, ground-based multi-sensor geophysical profiling of three hillslope transects in different regolith-landscape settings to characterise fine resolution (i.e. a number of frequencies; multiple frequency, multiple coil electromagnetic induction; and high resolution resistivity. These were accompanied by georeferenced, closely spaced deep cores to 9 m - or to core refusal. The intact cores were sub-sampled to standard depths and analysed for regolith properties to compile core datasets consisting of: water content; texture; electrical conductivity; and weathered state. After preprocessing (filtering, geo

Mechanisms of multiple production processes

International Nuclear Information System (INIS)

Dremin, I.M.

1977-01-01

Theoretical approaches to multiple production processes are discussed. A large number of models proceeds from the notion about common excited system produced by colliding hadrons. This class of models includes the hydrodynamical, statistical, thermodynamical and statistical bootstrap models. Sometimes the production process is due to excitation and decay of two colliding particles. The fragmentation bremsstrahlung and inelastic diffraction models belong to this group. The largest group of models describes the multiple production process as a result of formation of many excited centers. The typical example is the multiperipheral model. An interesting direction is given by the attempts to interrelate the mechanism of multiple production with internal structure of particles that is with their constituents (C-group)'-quarks, gluons, etc. Besides the models there are phenomenological (p group) attempts to connect different features of multiple production. Experimental data indicate the existence of leading and pionization particles thus giving an evidence for applications of different models. The data about increase of total and inclusive cross sections, the behaviour of the mean multiplicity and correlations at high energies provide a clue for further development of multiple production theory

Mixture models reveal multiple positional bias types in RNA-Seq data and lead to accurate transcript concentration estimates.

Directory of Open Access Journals (Sweden)

Andreas Tuerk

2017-05-01

Full Text Available Accuracy of transcript quantification with RNA-Seq is negatively affected by positional fragment bias. This article introduces Mix2 (rd. "mixquare", a transcript quantification method which uses a mixture of probability distributions to model and thereby neutralize the effects of positional fragment bias. The parameters of Mix2 are trained by Expectation Maximization resulting in simultaneous transcript abundance and bias estimates. We compare Mix2 to Cufflinks, RSEM, eXpress and PennSeq; state-of-the-art quantification methods implementing some form of bias correction. On four synthetic biases we show that the accuracy of Mix2 overall exceeds the accuracy of the other methods and that its bias estimates converge to the correct solution. We further evaluate Mix2 on real RNA-Seq data from the Microarray and Sequencing Quality Control (MAQC, SEQC Consortia. On MAQC data, Mix2 achieves improved correlation to qPCR measurements with a relative increase in R2 between 4% and 50%. Mix2 also yields repeatable concentration estimates across technical replicates with a relative increase in R2 between 8% and 47% and reduced standard deviation across the full concentration range. We further observe more accurate detection of differential expression with a relative increase in true positives between 74% and 378% for 5% false positives. In addition, Mix2 reveals 5 dominant biases in MAQC data deviating from the common assumption of a uniform fragment distribution. On SEQC data, Mix2 yields higher consistency between measured and predicted concentration ratios. A relative error of 20% or less is obtained for 51% of transcripts by Mix2, 40% of transcripts by Cufflinks and RSEM and 30% by eXpress. Titration order consistency is correct for 47% of transcripts for Mix2, 41% for Cufflinks and RSEM and 34% for eXpress. We, further, observe improved repeatability across laboratory sites with a relative increase in R2 between 8% and 44% and reduced standard deviation.

Enhancing CIDOC-CRM and compatible models with the concept of multiple interpretation

Science.gov (United States)

Van Ruymbeke, M.; Hallot, P.; Billen, R.

2017-08-01

Modelling cultural heritage and archaeological objects is used as much for management as for research purposes. To ensure the sustainable benefit of digital data, models benefit from taking the data specificities of historical and archaeological domains into account. Starting from a conceptual model tailored to storing these specificities, we present, in this paper, an extended mapping to CIDOC-CRM and its compatible models. Offering an ideal framework to structure and highlight the best modelling practices, these ontologies are essentially dedicated to storing semantic data which provides information about cultural heritage objects. Based on this standard, our proposal focuses on multiple interpretation and sequential reality.

[Prediction model of health workforce and beds in county hospitals of Hunan by multiple linear regression].

Science.gov (United States)

Ling, Ru; Liu, Jiawang

2011-12-01

To construct prediction model for health workforce and hospital beds in county hospitals of Hunan by multiple linear regression. We surveyed 16 counties in Hunan with stratified random sampling according to uniform questionnaires,and multiple linear regression analysis with 20 quotas selected by literature view was done. Independent variables in the multiple linear regression model on medical personnels in county hospitals included the counties' urban residents' income, crude death rate, medical beds, business occupancy, professional equipment value, the number of devices valued above 10 000 yuan, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, and utilization rate of hospital beds. Independent variables in the multiple linear regression model on county hospital beds included the the population of aged 65 and above in the counties, disposable income of urban residents, medical personnel of medical institutions in county area, business occupancy, the total value of professional equipment, fixed assets, long-term debt, medical income, medical expenses, outpatient and emergency visits, hospital visits, actual available bed days, utilization rate of hospital beds, and length of hospitalization. The prediction model shows good explanatory and fitting, and may be used for short- and mid-term forecasting.

Hybrid models for the simulation of microstructural evolution influenced by coupled, multiple physical processes

Energy Technology Data Exchange (ETDEWEB)

Tikare, Veena [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Hernandez-Rivera, Efrain [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Madison, Jonathan D. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Holm, Elizabeth Ann [Carnegie Mellon Univ., Pittsburgh, PA (United States); Patterson, Burton R. [Univ. of Florida, Gainesville, FL (United States). Dept. of Materials Science and Engineering; Homer, Eric R. [Brigham Young Univ., Provo, UT (United States). Dept. of Mechanical Engineering

2013-09-01

Most materials microstructural evolution processes progress with multiple processes occurring simultaneously. In this work, we have concentrated on the processes that are active in nuclear materials, in particular, nuclear fuels. These processes are coarsening, nucleation, differential diffusion, phase transformation, radiation-induced defect formation and swelling, often with temperature gradients present. All these couple and contribute to evolution that is unique to nuclear fuels and materials. Hybrid model that combines elements from the Potts Monte Carlo, phase-field models and others have been developed to address these multiple physical processes. These models are described and applied to several processes in this report. An important feature of the models developed are that they are coded as applications within SPPARKS, a Sandiadeveloped framework for simulation at the mesoscale of microstructural evolution processes by kinetic Monte Carlo methods. This makes these codes readily accessible and adaptable for future applications.

Multiple-event probability in general-relativistic quantum mechanics. II. A discrete model

International Nuclear Information System (INIS)

Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We introduce a simple quantum mechanical model in which time and space are discrete and periodic. These features avoid the complications related to continuous-spectrum operators and infinite-norm states. The model provides a tool for discussing the probabilistic interpretation of generally covariant quantum systems, without the confusion generated by spurious infinities. We use the model to illustrate the formalism of general-relativistic quantum mechanics, and to test the definition of multiple-event probability introduced in a companion paper [Phys. Rev. D 75, 084033 (2007)]. We consider a version of the model with unitary time evolution and a version without unitary time evolution

A prediction method based on wavelet transform and multiple models fusion for chaotic time series

International Nuclear Information System (INIS)

Zhongda, Tian; Shujiang, Li; Yanhong, Wang; Yi, Sha

2017-01-01

In order to improve the prediction accuracy of chaotic time series, a prediction method based on wavelet transform and multiple models fusion is proposed. The chaotic time series is decomposed and reconstructed by wavelet transform, and approximate components and detail components are obtained. According to different characteristics of each component, least squares support vector machine (LSSVM) is used as predictive model for approximation components. At the same time, an improved free search algorithm is utilized for predictive model parameters optimization. Auto regressive integrated moving average model (ARIMA) is used as predictive model for detail components. The multiple prediction model predictive values are fusion by Gauss–Markov algorithm, the error variance of predicted results after fusion is less than the single model, the prediction accuracy is improved. The simulation results are compared through two typical chaotic time series include Lorenz time series and Mackey–Glass time series. The simulation results show that the prediction method in this paper has a better prediction.

Multivariate Multiple Regression Models for a Big Data-Empowered SON Framework in Mobile Wireless Networks

Directory of Open Access Journals (Sweden)

Yoonsu Shin

2016-01-01

Full Text Available In the 5G era, the operational cost of mobile wireless networks will significantly increase. Further, massive network capacity and zero latency will be needed because everything will be connected to mobile networks. Thus, self-organizing networks (SON are needed, which expedite automatic operation of mobile wireless networks, but have challenges to satisfy the 5G requirements. Therefore, researchers have proposed a framework to empower SON using big data. The recent framework of a big data-empowered SON analyzes the relationship between key performance indicators (KPIs and related network parameters (NPs using machine-learning tools, and it develops regression models using a Gaussian process with those parameters. The problem, however, is that the methods of finding the NPs related to the KPIs differ individually. Moreover, the Gaussian process regression model cannot determine the relationship between a KPI and its various related NPs. In this paper, to solve these problems, we proposed multivariate multiple regression models to determine the relationship between various KPIs and NPs. If we assume one KPI and multiple NPs as one set, the proposed models help us process multiple sets at one time. Also, we can find out whether some KPIs are conflicting or not. We implement the proposed models using MapReduce.

A Point Kinetics Model for Estimating Neutron Multiplication of Bare Uranium Metal in Tagged Neutron Measurements

International Nuclear Information System (INIS)

Tweardy, Matthew C.; McConchie, Seth; Hayward, Jason P.

2017-01-01

An extension of the point kinetics model is developed in this paper to describe the neutron multiplicity response of a bare uranium object under interrogation by an associated particle imaging deuterium-tritium (D-T) measurement system. This extended model is used to estimate the total neutron multiplication of the uranium. Both MCNPX-PoliMi simulations and data from active interrogation measurements of highly enriched and depleted uranium geometries are used to evaluate the potential of this method and to identify the sources of systematic error. The detection efficiency correction for measured coincidence response is identified as a large source of systematic error. If the detection process is not considered, results suggest that the method can estimate total multiplication to within 13% of the simulated value. Values for multiplicity constants in the point kinetics equations are sensitive to enrichment due to (n, xn) interactions by D-T neutrons and can introduce another significant source of systematic bias. This can theoretically be corrected if isotopic composition is known a priori. Finally, the spatial dependence of multiplication is also suspected of introducing further systematic bias for high multiplication uranium objects.

A minimal model for multiple epidemics and immunity spreading.

Science.gov (United States)

Sneppen, Kim; Trusina, Ala; Jensen, Mogens H; Bornholdt, Stefan

2010-10-18

Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

Modeling Pan Evaporation for Kuwait by Multiple Linear Regression

Science.gov (United States)

Almedeij, Jaber

2012-01-01

Evaporation is an important parameter for many projects related to hydrology and water resources systems. This paper constitutes the first study conducted in Kuwait to obtain empirical relations for the estimation of daily and monthly pan evaporation as functions of available meteorological data of temperature, relative humidity, and wind speed. The data used here for the modeling are daily measurements of substantial continuity coverage, within a period of 17 years between January 1993 and December 2009, which can be considered representative of the desert climate of the urban zone of the country. Multiple linear regression technique is used with a procedure of variable selection for fitting the best model forms. The correlations of evaporation with temperature and relative humidity are also transformed in order to linearize the existing curvilinear patterns of the data by using power and exponential functions, respectively. The evaporation models suggested with the best variable combinations were shown to produce results that are in a reasonable agreement with observation values. PMID:23226984

Automatic Generation of 3D Building Models with Multiple Roofs

Institute of Scientific and Technical Information of China (English)

Kenichi Sugihara; Yoshitugu Hayashi

2008-01-01

Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons' edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.

Modeling the Potential Effects of New Tobacco Products and Policies: A Dynamic Population Model for Multiple Product Use and Harm

Science.gov (United States)

Vugrin, Eric D.; Rostron, Brian L.; Verzi, Stephen J.; Brodsky, Nancy S.; Brown, Theresa J.; Choiniere, Conrad J.; Coleman, Blair N.; Paredes, Antonio; Apelberg, Benjamin J.

2015-01-01

Background Recent declines in US cigarette smoking prevalence have coincided with increases in use of other tobacco products. Multiple product tobacco models can help assess the population health impacts associated with use of a wide range of tobacco products. Methods and Findings We present a multi-state, dynamical systems population structure model that can be used to assess the effects of tobacco product use behaviors on population health. The model incorporates transition behaviors, such as initiation, cessation, switching, and dual use, related to the use of multiple products. The model tracks product use prevalence and mortality attributable to tobacco use for the overall population and by sex and age group. The model can also be used to estimate differences in these outcomes between scenarios by varying input parameter values. We demonstrate model capabilities by projecting future cigarette smoking prevalence and smoking-attributable mortality and then simulating the effects of introduction of a hypothetical new lower-risk tobacco product under a variety of assumptions about product use. Sensitivity analyses were conducted to examine the range of population impacts that could occur due to differences in input values for product use and risk. We demonstrate that potential benefits from cigarette smokers switching to the lower-risk product can be offset over time through increased initiation of this product. Model results show that population health benefits are particularly sensitive to product risks and initiation, switching, and dual use behaviors. Conclusion Our model incorporates the variety of tobacco use behaviors and risks that occur with multiple products. As such, it can evaluate the population health impacts associated with the introduction of new tobacco products or policies that may result in product switching or dual use. Further model development will include refinement of data inputs for non-cigarette tobacco products and inclusion of health

The implementation of multiple intelligences based teaching model to improve mathematical problem solving ability for student of junior high school

Science.gov (United States)

Fasni, Nurli; Fatimah, Siti; Yulanda, Syerli

2017-05-01

This research aims to achieve some purposes such as: to know whether mathematical problem solving ability of students who have learned mathematics using Multiple Intelligences based teaching model is higher than the student who have learned mathematics using cooperative learning; to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using Multiple Intelligences based teaching model., to know the improvement of the mathematical problem solving ability of the student who have learned mathematics using cooperative learning; to know the attitude of the students to Multiple Intelligences based teaching model. The method employed here is quasi-experiment which is controlled by pre-test and post-test. The population of this research is all of VII grade in SMP Negeri 14 Bandung even-term 2013/2014, later on two classes of it were taken for the samples of this research. A class was taught using Multiple Intelligences based teaching model and the other one was taught using cooperative learning. The data of this research were gotten from the test in mathematical problem solving, scale questionnaire of the student attitudes, and observation. The results show the mathematical problem solving of the students who have learned mathematics using Multiple Intelligences based teaching model learning is higher than the student who have learned mathematics using cooperative learning, the mathematical problem solving ability of the student who have learned mathematics using cooperative learning and Multiple Intelligences based teaching model are in intermediate level, and the students showed the positive attitude in learning mathematics using Multiple Intelligences based teaching model. As for the recommendation for next author, Multiple Intelligences based teaching model can be tested on other subject and other ability.

The impacts of multiple stressors to model ecological structures

International Nuclear Information System (INIS)

Landis, W.G.; Kelly, S.A.; Markiewicz, A.J.; Matthews, R.A.; Matthews, G.B.

1995-01-01

The basis of the community conditioning hypothesis is that ecological structures are the result of their unique etiology. Systems that have been exposed to a variety of stressors should reflect this history. The authors how conducted a series of microcosm experiments that can compare the effects of multiple stressors upon community dynamics. The microcosm protocols are derived from the Standardized Aquatic Microcosm (SAM) and have Lemma and additional protozoan species. Two multiple stressor experiments have been conducted. In an extended length SAM (ELSAM), two of four treatments were dosed with the turbine fuel JP-8 one week into the experiment. Two treatments were later exposed to the heat stress, one that had received jet fuel and one that had not. Similarly, an ELSAM was conducted with the second stressor being the further addition of JP-8 replacing the heat shock. Biological, physical and chemical data were analyzed with multivariate techniques including nonmetric clustering and association analysis. Space-time worms and phase diagrams were also employed to ascertain the dynamic relationships of variables identified as important by the multivariate techniques. The experiments do not result in a simple additive linear response to the additional stressor. Examination of the relative population dynamics reveal alterations in trajectories that suggest treatment related effects. As in previous single stressor experiments, recovery does not occur even after extended experimental periods. The authors are now attempting to measure the resulting trajectories, changes in similarity vectors and overall dynamics. However, community conditioning does appear to be an important framework in understanding systems with a heterogeneous array of stressors

Merging for Particle-Mesh Complex Particle Kinetic Modeling of the Multiple Plasma Beams

Science.gov (United States)

Lipatov, Alexander S.

2011-01-01

We suggest a merging procedure for the Particle-Mesh Complex Particle Kinetic (PMCPK) method in case of inter-penetrating flow (multiple plasma beams). We examine the standard particle-in-cell (PIC) and the PMCPK methods in the case of particle acceleration by shock surfing for a wide range of the control numerical parameters. The plasma dynamics is described by a hybrid (particle-ion-fluid-electron) model. Note that one may need a mesh if modeling with the computation of an electromagnetic field. Our calculations use specified, time-independent electromagnetic fields for the shock, rather than self-consistently generated fields. While a particle-mesh method is a well-verified approach, the CPK method seems to be a good approach for multiscale modeling that includes multiple regions with various particle/fluid plasma behavior. However, the CPK method is still in need of a verification for studying the basic plasma phenomena: particle heating and acceleration by collisionless shocks, magnetic field reconnection, beam dynamics, etc.

A role for VAV1 in experimental autoimmune encephalomyelitis and multiple sclerosis

DEFF Research Database (Denmark)

Jagodic, Maja; Colacios, Celine; Nohra, Rita

2009-01-01

Multiple sclerosis, the most common cause of progressive neurological disability in young adults, is a chronic inflammatory disease. There is solid evidence for a genetic influence in multiple sclerosis, and deciphering the causative genes could reveal key pathways influencing the disease. A genome...... region on rat chromosome 9 regulates experimental autoimmune encephalomyelitis, a model for multiple sclerosis. Using interval-specific congenic rat lines and association of single-nucleotide polymorphisms with inflammatory phenotypes, we localized the gene of influence to Vav1, which codes for a signal......-transducing protein in leukocytes. Analysis of seven human cohorts (12,735 individuals) demonstrated an association of rs2546133-rs2617822 haplotypes in the first VAV1 intron with multiple sclerosis (CA: odds ratio, 1.18; CG: odds ratio, 0.86; TG: odds ratio, 0.90). The risk CA haplotype also predisposed for higher...

New transient-flow modelling of a multiple-fractured horizontal well

International Nuclear Information System (INIS)

Jia, Yong-Lu; Wang, Ben-Cheng; Nie, Ren-Shi; Wang, Dan-Ling

2014-01-01

A new transient-flow modelling of a multiple-fractured horizontal well is presented. Compared to conventional modelling, the new modelling considered more practical physical conditions, such as various inclined angles for different fractures, different fracture intervals, different fracture lengths and partially penetrating fractures to formation. A kind of new mathematical method, including a three-dimensional eigenvalue and orthogonal transform, was created to deduce the exact analytical solutions of pressure transients for constant-rate production in real space. In order to consider a wellbore storage coefficient and skin factor, we used a Laplace-transform approach to convert the exact analytical solutions to the solutions in Laplace space. Then the numerical solutions of pressure transients in real space were gained using a Stehfest numerical inversion. Standard type curves were plotted to describe the transient-flow characteristics. Flow regimes were clearly identified from type curves. Furthermore, the differences between the new modelling and the conventional modelling in pressure transients were especially compared and discussed. Finally, an example application to show the accordance of the new modelling with real conditions was implemented. Our new modelling is different from, but more practical than, conventional modelling. (paper)

A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

OpenAIRE

Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

2013-01-01

Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

Micro-macro multilevel latent class models with multiple discrete individual-level variables

NARCIS (Netherlands)

Bennink, M.; Croon, M.A.; Kroon, B.; Vermunt, J.K.

2016-01-01

An existing micro-macro method for a single individual-level variable is extended to the multivariate situation by presenting two multilevel latent class models in which multiple discrete individual-level variables are used to explain a group-level outcome. As in the univariate case, the

A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites

Science.gov (United States)

Wang, Q. J.; Robertson, D. E.; Chiew, F. H. S.

2009-05-01

Seasonal forecasting of streamflows can be highly valuable for water resources management. In this paper, a Bayesian joint probability (BJP) modeling approach for seasonal forecasting of streamflows at multiple sites is presented. A Box-Cox transformed multivariate normal distribution is proposed to model the joint distribution of future streamflows and their predictors such as antecedent streamflows and El Niño-Southern Oscillation indices and other climate indicators. Bayesian inference of model parameters and uncertainties is implemented using Markov chain Monte Carlo sampling, leading to joint probabilistic forecasts of streamflows at multiple sites. The model provides a parametric structure for quantifying relationships between variables, including intersite correlations. The Box-Cox transformed multivariate normal distribution has considerable flexibility for modeling a wide range of predictors and predictands. The Bayesian inference formulated allows the use of data that contain nonconcurrent and missing records. The model flexibility and data-handling ability means that the BJP modeling approach is potentially of wide practical application. The paper also presents a number of statistical measures and graphical methods for verification of probabilistic forecasts of continuous variables. Results for streamflows at three river gauges in the Murrumbidgee River catchment in southeast Australia show that the BJP modeling approach has good forecast quality and that the fitted model is consistent with observed data.

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

Science.gov (United States)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments

Science.gov (United States)

Lane, Peter C. R.; Gobet, Fernand

2013-03-01

Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.

QTL mapping in multiple populations and development stages reveals dynamic quantitative trait loci for fruit size in cucumbers of different market classes.

Science.gov (United States)

Weng, Yiqun; Colle, Marivi; Wang, Yuhui; Yang, Luming; Rubinstein, Mor; Sherman, Amir; Ophir, Ron; Grumet, Rebecca

2015-09-01

QTL analysis in multi-development stages with different QTL models identified 12 consensus QTLs underlying fruit elongation and radial growth presenting a dynamic view of genetic control of cucumber fruit development. Fruit size is an important quality trait in cucumber (Cucumis sativus L.) of different market classes. However, the genetic and molecular basis of fruit size variations in cucumber is not well understood. In this study, we conducted QTL mapping of fruit size in cucumber using F2, F2-derived F3 families and recombinant inbred lines (RILs) from a cross between two inbred lines Gy14 (North American picking cucumber) and 9930 (North China fresh market cucumber). Phenotypic data of fruit length and diameter were collected at three development stages (anthesis, immature and mature fruits) in six environments over 4 years. QTL analysis was performed with three QTL models including composite interval mapping (CIM), Bayesian interval mapping (BIM), and multiple QTL mapping (MQM). Twenty-nine consistent and distinct QTLs were detected for nine traits from multiple mapping populations and QTL models. Synthesis of information from available fruit size QTLs allowed establishment of 12 consensus QTLs underlying fruit elongation and radial growth, which presented a dynamic view of genetic control of cucumber fruit development. Results from this study highlighted the benefits of QTL analysis with multiple QTL models and different mapping populations in improving the power of QTL detection. Discussion was presented in the context of domestication and diversifying selection of fruit length and diameter, marker-assisted selection of fruit size, as well as identification of candidate genes for fruit size QTLs in cucumber.

Efficient multiple-trait association and estimation of genetic correlation using the matrix-variate linear mixed model.

Science.gov (United States)

Furlotte, Nicholas A; Eskin, Eleazar

2015-05-01

Multiple-trait association mapping, in which multiple traits are used simultaneously in the identification of genetic variants affecting those traits, has recently attracted interest. One class of approaches for this problem builds on classical variance component methodology, utilizing a multitrait version of a linear mixed model. These approaches both increase power and provide insights into the genetic architecture of multiple traits. In particular, it is possible to estimate the genetic correlation, which is a measure of the portion of the total correlation between traits that is due to additive genetic effects. Unfortunately, the practical utility of these methods is limited since they are computationally intractable for large sample sizes. In this article, we introduce a reformulation of the multiple-trait association mapping approach by defining the matrix-variate linear mixed model. Our approach reduces the computational time necessary to perform maximum-likelihood inference in a multiple-trait model by utilizing a data transformation. By utilizing a well-studied human cohort, we show that our approach provides more than a 10-fold speedup, making multiple-trait association feasible in a large population cohort on the genome-wide scale. We take advantage of the efficiency of our approach to analyze gene expression data. By decomposing gene coexpression into a genetic and environmental component, we show that our method provides fundamental insights into the nature of coexpressed genes. An implementation of this method is available at http://genetics.cs.ucla.edu/mvLMM. Copyright © 2015 by the Genetics Society of America.

Multiple Regions of a Cortical Network Commonly Encode the Meaning of Words in Multiple Grammatical Positions of Read Sentences.

Science.gov (United States)

Anderson, Andrew James; Lalor, Edmund C; Lin, Feng; Binder, Jeffrey R; Fernandino, Leonardo; Humphries, Colin J; Conant, Lisa L; Raizada, Rajeev D S; Grimm, Scott; Wang, Xixi

2018-05-16

Deciphering how sentence meaning is represented in the brain remains a major challenge to science. Semantically related neural activity has recently been shown to arise concurrently in distributed brain regions as successive words in a sentence are read. However, what semantic content is represented by different regions, what is common across them, and how this relates to words in different grammatical positions of sentences is weakly understood. To address these questions, we apply a semantic model of word meaning to interpret brain activation patterns elicited in sentence reading. The model is based on human ratings of 65 sensory/motor/emotional and cognitive features of experience with words (and their referents). Through a process of mapping functional Magnetic Resonance Imaging activation back into model space we test: which brain regions semantically encode content words in different grammatical positions (e.g., subject/verb/object); and what semantic features are encoded by different regions. In left temporal, inferior parietal, and inferior/superior frontal regions we detect the semantic encoding of words in all grammatical positions tested and reveal multiple common components of semantic representation. This suggests that sentence comprehension involves a common core representation of multiple words' meaning being encoded in a network of regions distributed across the brain.

Multiple Polyploidization Events across Asteraceae with Two Nested Events in the Early History Revealed by Nuclear Phylogenomics.

Science.gov (United States)

Huang, Chien-Hsun; Zhang, Caifei; Liu, Mian; Hu, Yi; Gao, Tiangang; Qi, Ji; Ma, Hong

2016-11-01

Biodiversity results from multiple evolutionary mechanisms, including genetic variation and natural selection. Whole-genome duplications (WGDs), or polyploidizations, provide opportunities for large-scale genetic modifications. Many evolutionarily successful lineages, including angiosperms and vertebrates, are ancient polyploids, suggesting that WGDs are a driving force in evolution. However, this hypothesis is challenged by the observed lower speciation and higher extinction rates of recently formed polyploids than diploids. Asteraceae includes about 10% of angiosperm species, is thus undoubtedly one of the most successful lineages and paleopolyploidization was suggested early in this family using a small number of datasets. Here, we used genes from 64 new transcriptome datasets and others to reconstruct a robust Asteraceae phylogeny, covering 73 species from 18 tribes in six subfamilies. We estimated their divergence times and further identified multiple potential ancient WGDs within several tribes and shared by the Heliantheae alliance, core Asteraceae (Asteroideae-Mutisioideae), and also with the sister family Calyceraceae. For two of the WGD events, there were subsequent great increases in biodiversity; the older one proceeded the divergence of at least 10 subfamilies within 10 My, with great variation in morphology and physiology, whereas the other was followed by extremely high species richness in the Heliantheae alliance clade. Our results provide different evidence for several WGDs in Asteraceae and reveal distinct association among WGD events, dramatic changes in environment and species radiations, providing a possible scenario for polyploids to overcome the disadvantages of WGDs and to evolve into lineages with high biodiversity. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

Science.gov (United States)

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

Compacton solutions and multiple compacton solutions for a continuum Toda lattice model

International Nuclear Information System (INIS)

Fan Xinghua; Tian Lixin

2006-01-01

Some special solutions of the Toda lattice model with a transversal degree of freedom are obtained. With the aid of Mathematica and Wu elimination method, more explicit solitary wave solutions, including compacton solutions, multiple compacton solutions, peakon solutions, as well as periodic solutions are found in this paper

The perspective awareness model - Eliciting multiple perspectives to formulate high quality decisions

International Nuclear Information System (INIS)

Boucher, Laurel

2013-01-01

A great deal of attention is given to the importance of communication in environmental remediation and radioactive waste management. However, very little attention is given to eliciting multiple perspectives so as to formulate high quality decisions. Plans that are based on a limited number of perspectives tend to be narrowly focused whereas those that are based on a wide variety of perspectives tend to be comprehensive, higher quality, and more apt to be put into application. In addition, existing methods of dialogue have built-in limitations in that they typically draw from the predominant thinking patterns which focus in some areas but ignore others. This can result in clarity but a lack of comprehensiveness. This paper presents a Perspective Awareness Model which helps groups such as partnering teams, interagency teams, steering committees, and working groups elicit a wide net of perspectives and viewpoints. The paper begins by describing five factors that makes cooperation among such groups challenging. Next, a Perspective Awareness Model that makes it possible to manage these five factors is presented. The two primary components of this model --- the eight 'Thinking Directions' and the 'Shared Documentation' --- are described in detail. Several examples are given to illustrate how the Perspective Awareness Model can be used to elicit multiple perspectives to formulate high quality decisions in the area of environmental remediation and radioactive waste management. (authors)

A geospatial modelling approach to predict seagrass habitat recovery under multiple stressor regimes

Science.gov (United States)

Restoration of estuarine seagrass habitats requires a clear understanding of the modes of action of multiple interacting stressors including nutrients, climate change, coastal land-use change, and habitat modification. We have developed and demonstrated a geospatial modeling a...

INTRODUCTION TO A COMBINED MULTIPLE LINEAR REGRESSION AND ARMA MODELING APPROACH FOR BEACH BACTERIA PREDICTION

Science.gov (United States)

Due to the complexity of the processes contributing to beach bacteria concentrations, many researchers rely on statistical modeling, among which multiple linear regression (MLR) modeling is most widely used. Despite its ease of use and interpretation, there may be time dependence...

Writing in the workplace: Constructing documents using multiple digital sources

Directory of Open Access Journals (Sweden)

Mariëlle Leijten

2014-02-01

Full Text Available In today’s workplaces professional communication often involves constructing documents from multiple digital sources—integrating one’s own texts/graphics with ideas based on others’ text/graphics. This article presents a case study of a professional communication designer as he constructs a proposal over several days. Drawing on keystroke and interview data, we map the professional’s overall process, plot the time course of his writing/design, illustrate how he searches for content and switches among optional digital sources, and show how he modifies and reuses others’ content. The case study reveals not only that the professional (1 searches extensively through multiple sources for content and ideas but that he also (2 constructs visual content (charts, graphs, photographs as well as verbal content, and (3 manages his attention and motivation over this extended task. Since these three activities are not represented in current models of writing, we propose their addition not just to models of communication design, but also to models of writing in general.

Phylogeographic investigation and ecological niche modelling of the endemic frog species Nanorana pleskei revealed multiple refugia in the eastern Tibetan Plateau.

Science.gov (United States)

Wang, Bin; Xie, Feng; Li, Jiannan; Wang, Gang; Li, Cheng; Jiang, Jianping

2017-01-01

The largest plateau Tibetan Plateau supplied an excellent opportunity to investigate the influence of the Pleistocene events on the high-elevation species. To test for the alternative hypotheses of Pleistocene glacial refugia, we used partial sequences of two mitochondrial genes and one nuclear gene to examine the phylogeographic patterns of the endemic frog species Nanorana pleskei across its known range in the eastern Tibetan Plateau, and conducted species distribution modelling (SDM) to explore changes of its distribution range through current and paleo periods. In all data sets, the species was divided into lineage north occupying open plateau platform and lineage south colonizing the mountainous plateau. The divergence of two major clades was estimated at the early Pleistocene. In mtDNA, lineage north contained northeastern and northwestern sublineages, and lineage south had two overlapping-distributed sublineages. Different lineages possessed distinct demographic characteristics, i.e., subdivision in the northeastern sublineage, historical bottleneck effects and recent expansions in the northwestern sublineage and the southeastern sublineage. SDMs depicted that stable suitable habitats had existed in the upper-middle streams of the Yellow River, Dadu River, Jinsha River and Yalong River. These regions were also recognized as the ancestral areas of different lineages. In conclusion, Nanorana pleskei lineages have probably experienced long-term separations. Stable suitable habitats existing in upper-middle streams of major rivers on the eastern Tibetan Plateau and distinct demographic dynamics of different lineages indicated that the lineages possessed independent evolutionary processes in multiple glacial refugia. The findings verified the profound effects of Pleistocene climatic fluctuations on the plateau endemic species.

A minimal model for multiple epidemics and immunity spreading.

Directory of Open Access Journals (Sweden)

Kim Sneppen

Full Text Available Pathogens and parasites are ubiquitous in the living world, being limited only by availability of suitable hosts. The ability to transmit a particular disease depends on competing infections as well as on the status of host immunity. Multiple diseases compete for the same resource and their fate is coupled to each other. Such couplings have many facets, for example cross-immunization between related influenza strains, mutual inhibition by killing the host, or possible even a mutual catalytic effect if host immunity is impaired. We here introduce a minimal model for an unlimited number of unrelated pathogens whose interaction is simplified to simple mutual exclusion. The model incorporates an ongoing development of host immunity to past diseases, while leaving the system open for emergence of new diseases. The model exhibits a rich dynamical behavior with interacting infection waves, leaving broad trails of immunization in the host population. This obtained immunization pattern depends only on the system size and on the mutation rate that initiates new diseases.

Many-electron model for multiple ionization in atomic collisions

International Nuclear Information System (INIS)

Archubi, C D; Montanari, C C; Miraglia, J E

2007-01-01

We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data

Many-electron model for multiple ionization in atomic collisions

Energy Technology Data Exchange (ETDEWEB)

Archubi, C D [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Montanari, C C [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina); Miraglia, J E [Instituto de AstronomIa y Fisica del Espacio, Casilla de Correo 67, Sucursal 28 (C1428EGA) Buenos Aires (Argentina)

2007-03-14

We have developed a many-electron model for multiple ionization of heavy atoms bombarded by bare ions. It is based on the transport equation for an ion in an inhomogeneous electronic density. Ionization probabilities are obtained by employing the shell-to-shell local plasma approximation with the Levine and Louie dielectric function to take into account the binding energy of each shell. Post-collisional contributions due to Auger-like processes are taken into account by employing recent photoemission data. Results for single-to-quadruple ionization of Ne, Ar, Kr and Xe by protons are presented showing a very good agreement with experimental data.

Multiple Scattering Model for Optical Coherence Tomography with Rytov Approximation

KAUST Repository

Li, Muxingzi

2017-04-24

Optical Coherence Tomography (OCT) is a coherence-gated, micrometer-resolution imaging technique that focuses a broadband near-infrared laser beam to penetrate into optical scattering media, e.g. biological tissues. The OCT resolution is split into two parts, with the axial resolution defined by half the coherence length, and the depth-dependent lateral resolution determined by the beam geometry, which is well described by a Gaussian beam model. The depth dependence of lateral resolution directly results in the defocusing effect outside the confocal region and restricts current OCT probes to small numerical aperture (NA) at the expense of lateral resolution near the focus. Another limitation on OCT development is the presence of a mixture of speckles due to multiple scatterers within the coherence length, and other random noise. Motivated by the above two challenges, a multiple scattering model based on Rytov approximation and Gaussian beam optics is proposed for the OCT setup. Some previous papers have adopted the first Born approximation with the assumption of small perturbation of the incident field in inhomogeneous media. The Rytov method of the same order with smooth phase perturbation assumption benefits from a wider spatial range of validity. A deconvolution method for solving the inverse problem associated with the first Rytov approximation is developed, significantly reducing the defocusing effect through depth and therefore extending the feasible range of NA.

Resveratrol Neuroprotection in a Chronic Mouse Model of Multiple Sclerosis

Directory of Open Access Journals (Sweden)

Zoe eFonseca-Kelly

2012-05-01

Full Text Available Resveratrol is a naturally-occurring polyphenol that activates SIRT1, an NAD-dependent deacetylase. SRT501, a pharmaceutical formulation of resveratrol with enhanced systemic absorption, prevents neuronal loss without suppressing inflammation in mice with relapsing experimental autoimmune encephalomyelitis (EAE, a model of multiple sclerosis. In contrast, resveratrol has been reported to suppress inflammation in chronic EAE, although neuroprotective effects were not evaluated. The current studies examine potential neuroprotective and immunomodulatory effects of resveratrol in chronic EAE induced by immunization with myelin oligodendroglial glycoprotein peptide in C57/Bl6 mice. Effects of two distinct formulations of resveratrol administered daily orally were compared. Resveratrol delayed the onset of EAE compared to vehicle-treated EAE mice, but did not prevent or alter the phenotype of inflammation in spinal cords or optic nerves. Significant neuroprotective effects were observed, with higher numbers of retinal ganglion cells found in eyes of resveratrol-treated EAE mice with optic nerve inflammation. Results demonstrate that resveratrol prevents neuronal loss in this chronic demyelinating disease model, similar to its effects in relapsing EAE. Differences in immunosuppression compared with prior studies suggest that immunomodulatory effects may be limited and may depend on specific immunization parameters or timing of treatment. Importantly, neuroprotective effects can occur without immunosuppression, suggesting a potential additive benefit of resveratrol in combination with anti-inflammatory therapies for multiple sclerosis.

Constraints on signaling network logic reveal functional subgraphs on Multiple Myeloma OMIC data.

Science.gov (United States)

Miannay, Bertrand; Minvielle, Stéphane; Magrangeas, Florence; Guziolowski, Carito

2018-03-21

The integration of gene expression profiles (GEPs) and large-scale biological networks derived from pathways databases is a subject which is being widely explored. Existing methods are based on network distance measures among significantly measured species. Only a small number of them include the directionality and underlying logic existing in biological networks. In this study we approach the GEP-networks integration problem by considering the network logic, however our approach does not require a prior species selection according to their gene expression level. We start by modeling the biological network representing its underlying logic using Logic Programming. This model points to reachable network discrete states that maximize a notion of harmony between the molecular species active or inactive possible states and the directionality of the pathways reactions according to their activator or inhibitor control role. Only then, we confront these network states with the GEP. From this confrontation independent graph components are derived, each of them related to a fixed and optimal assignment of active or inactive states. These components allow us to decompose a large-scale network into subgraphs and their molecular species state assignments have different degrees of similarity when compared to the same GEP. We apply our method to study the set of possible states derived from a subgraph from the NCI-PID Pathway Interaction Database. This graph links Multiple Myeloma (MM) genes to known receptors for this blood cancer. We discover that the NCI-PID MM graph had 15 independent components, and when confronted to 611 MM GEPs, we find 1 component as being more specific to represent the difference between cancer and healthy profiles.

Multiple Solutions of Nonlinear Boundary Value Problems of Fractional Order: A New Analytic Iterative Technique

Directory of Open Access Journals (Sweden)

Omar Abu Arqub

2014-01-01

Full Text Available The purpose of this paper is to present a new kind of analytical method, the so-called residual power series, to predict and represent the multiplicity of solutions to nonlinear boundary value problems of fractional order. The present method is capable of calculating all branches of solutions simultaneously, even if these multiple solutions are very close and thus rather difficult to distinguish even by numerical techniques. To verify the computational efficiency of the designed proposed technique, two nonlinear models are performed, one of them arises in mixed convection flows and the other one arises in heat transfer, which both admit multiple solutions. The results reveal that the method is very effective, straightforward, and powerful for formulating these multiple solutions.

Single-copy nuclear genes place haustorial Hydnoraceae within piperales and reveal a cretaceous origin of multiple parasitic angiosperm lineages.

Directory of Open Access Journals (Sweden)

Julia Naumann

Full Text Available Extreme haustorial parasites have long captured the interest of naturalists and scientists with their greatly reduced and highly specialized morphology. Along with the reduction or loss of photosynthesis, the plastid genome often decays as photosynthetic genes are released from selective constraint. This makes it challenging to use traditional plastid genes for parasitic plant phylogenetics, and has driven the search for alternative phylogenetic and molecular evolutionary markers. Thus, evolutionary studies, such as molecular clock-based age estimates, are not yet available for all parasitic lineages. In the present study, we extracted 14 nuclear single copy genes (nSCG from Illumina transcriptome data from one of the "strangest plants in the world", Hydnora visseri (Hydnoraceae. A ~15,000 character molecular dataset, based on all three genomic compartments, shows the utility of nSCG for reconstructing phylogenetic relationships in parasitic lineages. A relaxed molecular clock approach with the same multi-locus dataset, revealed an ancient age of ~91 MYA for Hydnoraceae. We then estimated the stem ages of all independently originated parasitic angiosperm lineages using a published dataset, which also revealed a Cretaceous origin for Balanophoraceae, Cynomoriaceae and Apodanthaceae. With the exception of Santalales, older parasite lineages tend to be more specialized with respect to trophic level and have lower species diversity. We thus propose the "temporal specialization hypothesis" (TSH implementing multiple independent specialization processes over time during parasitic angiosperm evolution.

A Lévy HJM Multiple-Curve Model with Application to CVA Computation

DEFF Research Database (Denmark)

Crépey, Stéphane; Grbac, Zorana; Ngor, Nathalie

2015-01-01

, the calibration to OTM swaptions guaranteeing that the model correctly captures volatility smile effects and the calibration to co-terminal ATM swaptions ensuring an appropriate term structure of the volatility in the model. To account for counterparty risk and funding issues, we use the calibrated multiple......-curve model as an underlying model for CVA computation. We follow a reduced-form methodology through which the problem of pricing the counterparty risk and funding costs can be reduced to a pre-default Markovian BSDE, or an equivalent semi-linear PDE. As an illustration, we study the case of a basis swap...... and a related swaption, for which we compute the counterparty risk and funding adjustments...

Proteotyping of laboratory-scale biogas plants reveals multiple steady-states in community composition.

Science.gov (United States)

Kohrs, F; Heyer, R; Bissinger, T; Kottler, R; Schallert, K; Püttker, S; Behne, A; Rapp, E; Benndorf, D; Reichl, U

2017-08-01

Complex microbial communities are the functional core of anaerobic digestion processes taking place in biogas plants (BGP). So far, however, a comprehensive characterization of the microbiomes involved in methane formation is technically challenging. As an alternative, enriched communities from laboratory-scale experiments can be investigated that have a reduced number of organisms and are easier to characterize by state of the art mass spectrometric-based (MS) metaproteomic workflows. Six parallel laboratory digesters were inoculated with sludge from a full-scale BGP to study the development of enriched microbial communities under defined conditions. During the first three month of cultivation, all reactors (R1-R6) were functionally comparable regarding biogas productions (375-625 NL L reactor volume -1 d -1 ), methane yields (50-60%), pH values (7.1-7.3), and volatile fatty acids (VFA, 1 gNH 3 L -1 ) showed an increase to pH 7.5-8.0, accumulation of acetate (>10 mM), and decreasing biogas production (<125 NL L reactor volume -1 d -1 ). Tandem MS (MS/MS)-based proteotyping allowed the identification of taxonomic abundances and biological processes. Although all reactors showed similar performances, proteotyping and terminal restriction fragment length polymorphisms (T-RFLP) fingerprinting revealed significant differences in the composition of individual microbial communities, indicating multiple steady-states. Furthermore, cellulolytic enzymes and cellulosomal proteins of Clostridium thermocellum were identified to be specific markers for the thermophilic reactors (R3, R4). Metaproteins found in R3 indicated hydrogenothrophic methanogenesis, whereas metaproteins of acetoclastic methanogenesis were identified in R4. This suggests not only an individual evolution of microbial communities even for the case that BGPs are started at the same initial conditions under well controlled environmental conditions, but also a high compositional variance of microbiomes under

SOME STATISTICAL ISSUES RELATED TO MULTIPLE LINEAR REGRESSION MODELING OF BEACH BACTERIA CONCENTRATIONS

Science.gov (United States)

As a fast and effective technique, the multiple linear regression (MLR) method has been widely used in modeling and prediction of beach bacteria concentrations. Among previous works on this subject, however, several issues were insufficiently or inconsistently addressed. Those is...

A multiple-location model for natural gas forward curves

International Nuclear Information System (INIS)

Buffington, J.C.

1999-06-01

This thesis presents an approach for financial modelling of natural gas in which connections between locations are incorporated and the complexities of forward curves in natural gas are considered. Apart from electricity, natural gas is the most volatile commodity traded. Its price is often dependent on the weather and price shocks can be felt across several geographic locations. This modelling approach incorporates multiple risk factors that correspond to various locations. One of the objectives was to determine if the model could be used for closed-form option prices. It was suggested that an adequate model for natural gas must consider 3 statistical properties: volatility term structure, backwardation and contango, and stochastic basis. Data from gas forward prices at Chicago, NYMEX and AECO were empirically tested to better understand these 3 statistical properties at each location and to verify if the proposed model truly incorporates these properties. In addition, this study examined the time series property of the difference of two locations (the basis) and determines that these empirical properties are consistent with the model properties. Closed-form option solutions were also developed for call options of forward contracts and call options on forward basis. The options were calibrated and compared to other models. The proposed model is capable of pricing options, but the prices derived did not pass the test of economic reasonableness. However, the model was able to capture the effect of transportation as well as aspects of seasonality which is a benefit over other existing models. It was determined that modifications will be needed regarding the estimation of the convenience yields. 57 refs., 2 tabs., 7 figs., 1 append

Electronic transport in single-helical protein molecules: Effects of multiple charge conduction pathways and helical symmetry

Energy Technology Data Exchange (ETDEWEB)

Kundu, Sourav, E-mail: sourav.kunduphy@gmail.com; Karmakar, S.N.

2016-07-15

We propose a tight-binding model to investigate electronic transport properties of single helical protein molecules incorporating both the helical symmetry and the possibility of multiple charge transfer pathways. Our study reveals that due to existence of both the multiple charge transfer pathways and helical symmetry, the transport properties are quite rigid under influence of environmental fluctuations which indicates that these biomolecules can serve as better alternatives in nanoelectronic devices than its other biological counterparts e.g., single-stranded DNA.

Sarcoidosis and multiple myeloma: Concurrent presentation of an unusual association

Directory of Open Access Journals (Sweden)

Vidya Nair

2016-01-01

Full Text Available Literature on concurrent association of sarcoidosis with lymphoproliferative malignancies other than lymphoma e.g. multiple myeloma is meager. The rarity of the situation prompted us to report this patient who was a 51-year-old woman with a 2-years history of breathlessness, cough with expectoration, chest pain and backache. Initial evaluation revealed mild anemia, increased alkaline phosphatase with chest skiagram showing both lower zone non homogenous opacities with calcified hilar lymph nodes. CECT chest showed mediastinal with bilateral hilar lymphadenopathy, parenchymal fibrosis, traction bronchiectasis, ground glass opacities, septal and peribronchovascular thickening affecting mid and lower lung zones bilaterally. MRI Dorsolumbar spine was suggestive of marrow infiltrative disorder. EBUS FNA of intrathoracic nodes, EBB and TBLB confirmed sarcoidosis. PET CT revealed hyper metabolic activity in lung, multiple lymph nodes and lytic bone lesions. Serum protein electrophoresis and immunofixation revealed a monoclonal paraprotein, immunoglobulin IgG kappa type. Bone marrow biopsy revealed an increase in plasma cells (15%, but no granulomas. Diagnosis of Indolent or multiple myeloma with sarcoidosis was established. 12 cases of sarcoidosis and multiple myeloma have been reported in literature, and mostly preceding the onset of multiple myeloma by many years, in our case both were diagnosed concurrently.

Generalized internal multiple imaging

KAUST Repository

Zuberi, M. A. H.

2014-08-05

Internal multiples deteriorate the image when the imaging procedure assumes only single scattering, especially if the velocity model does not have sharp contrasts to reproduce such scattering in the Green’s function through forward modeling. If properly imaged, internal multiples (internally scattered energy) can enhance the seismic image. Conventionally, to image internal multiples, accurate, sharp contrasts in the velocity model are required to construct a Green’s function with all the scattered energy. As an alternative, we have developed a generalized internal multiple imaging procedure that images any order internal scattering using the background Green’s function (from the surface to each image point), constructed from a smooth velocity model, usually used for conventional imaging. For the first-order internal multiples, the approach consisted of three steps, in which we first back propagated the recorded surface seismic data using the background Green’s function, then crosscorrelated the back-propagated data with the recorded data, and finally crosscorrelated the result with the original background Green’s function. This procedure images the contribution of the recorded first-order internal multiples, and it is almost free of the single-scattering recorded energy. The cost includes one additional crosscorrelation over the conventional single-scattering imaging application. We generalized this method to image internal multiples of any order separately. The resulting images can be added to the conventional single-scattering image, obtained, e.g., from Kirchhoff or reverse-time migration, to enhance the image. Application to synthetic data with reflectors illuminated by multiple scattering (double scattering) demonstrated the effectiveness of the approach.

Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

International Nuclear Information System (INIS)

Valor, A.; Caleyo, F.; Alfonso, L.; Rivas, D.; Hallen, J.M.

2007-01-01

In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion

Stochastic modeling of pitting corrosion: A new model for initiation and growth of multiple corrosion pits

Energy Technology Data Exchange (ETDEWEB)

Valor, A. [Facultad de Fisica, Universidad de La Habana, San Lazaro y L, Vedado, 10400 Havana (Cuba); Caleyo, F. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)]. E-mail: fcaleyo@gmail.com; Alfonso, L. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Rivas, D. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico); Hallen, J.M. [Departamento de Ingenieria, Metalurgica, IPN-ESIQIE, UPALM Edif. 7, Zacatenco, Mexico DF 07738 (Mexico)

2007-02-15

In this work, a new stochastic model capable of simulating pitting corrosion is developed and validated. Pitting corrosion is modeled as the combination of two stochastic processes: pit initiation and pit growth. Pit generation is modeled as a nonhomogeneous Poisson process, in which induction time for pit initiation is simulated as the realization of a Weibull process. In this way, the exponential and Weibull distributions can be considered as the possible distributions for pit initiation time. Pit growth is simulated using a nonhomogeneous Markov process. Extreme value statistics is used to find the distribution of maximum pit depths resulting from the combination of the initiation and growth processes for multiple pits. The proposed model is validated using several published experiments on pitting corrosion. It is capable of reproducing the experimental observations with higher quality than the stochastic models available in the literature for pitting corrosion.

Multiple regression models for energy use in air-conditioned office buildings in different climates

International Nuclear Information System (INIS)

Lam, Joseph C.; Wan, Kevin K.W.; Liu Dalong; Tsang, C.L.

2010-01-01

An attempt was made to develop multiple regression models for office buildings in the five major climates in China - severe cold, cold, hot summer and cold winter, mild, and hot summer and warm winter. A total of 12 key building design variables were identified through parametric and sensitivity analysis, and considered as inputs in the regression models. The coefficient of determination R 2 varies from 0.89 in Harbin to 0.97 in Kunming, indicating that 89-97% of the variations in annual building energy use can be explained by the changes in the 12 parameters. A pseudo-random number generator based on three simple multiplicative congruential generators was employed to generate random designs for evaluation of the regression models. The difference between regression-predicted and DOE-simulated annual building energy use are largely within 10%. It is envisaged that the regression models developed can be used to estimate the likely energy savings/penalty during the initial design stage when different building schemes and design concepts are being considered.

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.

Phosphoproteomics reveals that glycogen synthase kinase-3 phosphorylates multiple splicing factors and is associated with alternative splicing

Science.gov (United States)

Shinde, Mansi Y.; Sidoli, Simone; Kulej, Katarzyna; Mallory, Michael J.; Radens, Caleb M.; Reicherter, Amanda L.; Myers, Rebecca L.; Barash, Yoseph; Lynch, Kristen W.; Garcia, Benjamin A.; Klein, Peter S.

2017-01-01

Glycogen synthase kinase-3 (GSK-3) is a constitutively active, ubiquitously expressed protein kinase that regulates multiple signaling pathways. In vitro kinase assays and genetic and pharmacological manipulations of GSK-3 have identified more than 100 putative GSK-3 substrates in diverse cell types. Many more have been predicted on the basis of a recurrent GSK-3 consensus motif ((pS/pT)XXX(S/T)), but this prediction has not been tested by analyzing the GSK-3 phosphoproteome. Using stable isotope labeling of amino acids in culture (SILAC) and MS techniques to analyze the repertoire of GSK-3–dependent phosphorylation in mouse embryonic stem cells (ESCs), we found that ∼2.4% of (pS/pT)XXX(S/T) sites are phosphorylated in a GSK-3–dependent manner. A comparison of WT and Gsk3a;Gsk3b knock-out (Gsk3 DKO) ESCs revealed prominent GSK-3–dependent phosphorylation of multiple splicing factors and regulators of RNA biosynthesis as well as proteins that regulate transcription, translation, and cell division. Gsk3 DKO reduced phosphorylation of the splicing factors RBM8A, SRSF9, and PSF as well as the nucleolar proteins NPM1 and PHF6, and recombinant GSK-3β phosphorylated these proteins in vitro. RNA-Seq of WT and Gsk3 DKO ESCs identified ∼190 genes that are alternatively spliced in a GSK-3–dependent manner, supporting a broad role for GSK-3 in regulating alternative splicing. The MS data also identified posttranscriptional regulation of protein abundance by GSK-3, with ∼47 proteins (1.4%) whose levels increased and ∼78 (2.4%) whose levels decreased in the absence of GSK-3. This study provides the first unbiased analysis of the GSK-3 phosphoproteome and strong evidence that GSK-3 broadly regulates alternative splicing. PMID:28916722

A study of single multiplicative neuron model with nonlinear filters for hourly wind speed prediction

International Nuclear Information System (INIS)

Wu, Xuedong; Zhu, Zhiyu; Su, Xunliang; Fan, Shaosheng; Du, Zhaoping; Chang, Yanchao; Zeng, Qingjun

2015-01-01

Wind speed prediction is one important methods to guarantee the wind energy integrated into the whole power system smoothly. However, wind power has a non–schedulable nature due to the strong stochastic nature and dynamic uncertainty nature of wind speed. Therefore, wind speed prediction is an indispensable requirement for power system operators. Two new approaches for hourly wind speed prediction are developed in this study by integrating the single multiplicative neuron model and the iterated nonlinear filters for updating the wind speed sequence accurately. In the presented methods, a nonlinear state–space model is first formed based on the single multiplicative neuron model and then the iterated nonlinear filters are employed to perform dynamic state estimation on wind speed sequence with stochastic uncertainty. The suggested approaches are demonstrated using three cases wind speed data and are compared with autoregressive moving average, artificial neural network, kernel ridge regression based residual active learning and single multiplicative neuron model methods. Three types of prediction errors, mean absolute error improvement ratio and running time are employed for different models’ performance comparison. Comparison results from Tables 1–3 indicate that the presented strategies have much better performance for hourly wind speed prediction than other technologies. - Highlights: • Developed two novel hybrid modeling methods for hourly wind speed prediction. • Uncertainty and fluctuations of wind speed can be better explained by novel methods. • Proposed strategies have online adaptive learning ability. • Proposed approaches have shown better performance compared with existed approaches. • Comparison and analysis of two proposed novel models for three cases are provided

Multiplicity distributions in a thermodynamical model of hadron production in e{sup +}e{sup -} collisions

Energy Technology Data Exchange (ETDEWEB)

Becattini, F. [Florence Univ. (Italy)]|[Istituto Nazionale di Fisica Nucleare, Florence (Italy); Giovannini, A. [Turin Univ. (Italy). Ist. di Fisica Teorica]|[Istituto Nazionale di Fisica Nucleare, Turin (Italy); Lupia, S. [Max-Planck-Institut fuer Physik, Muenchen (Germany). Werner-Heisenberg-Institut

1996-10-01

Predictions of a thermodynamical model of hadron production for multiplicity distributions in e{sup +}e{sup -} annihilations at LEP and PEP-PETRA centre of mass energies are shown. The production process is described as a two-step process in which primary hadrons emitted from the thermal source decay into final observable particles. The final charged track multiplicity distributions turn out to be of negative binomial type and are in quite good agreement with experimental observations. The average number of clans calculated from fitted negative binomial coincides with the average number of primary hadrons predicted by the thermodynamical model, suggesting that clans should be identified with primary hadrons. (orig.)

Testing a multiple mediation model of Asian American college students' willingness to see a counselor.

Science.gov (United States)

Kim, Paul Youngbin; Park, Irene J K

2009-07-01

Adapting the theory of reasoned action, the present study examined help-seeking beliefs, attitudes, and intent among Asian American college students (N = 110). A multiple mediation model was tested to see if the relation between Asian values and willingness to see a counselor was mediated by attitudes toward seeking professional psychological help and subjective norm. A bootstrapping procedure was used to test the multiple mediation model. Results indicated that subjective norm was the sole significant mediator of the effect of Asian values on willingness to see a counselor. The findings highlight the importance of social influences on help-seeking intent among Asian American college students.

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems

Directory of Open Access Journals (Sweden)

Xiaofei He

2018-02-01

Full Text Available Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT (smart cities, smart grid, smart transportation, etc. and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy, our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems.

Science.gov (United States)

He, Xiaofei; Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu

2018-02-24

Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries

Classification of Multiple Seizure-Like States in Three Different Rodent Models of Epileptogenesis.

Science.gov (United States)

Guirgis, Mirna; Serletis, Demitre; Zhang, Jane; Florez, Carlos; Dian, Joshua A; Carlen, Peter L; Bardakjian, Berj L

2014-01-01

Epilepsy is a dynamical disease and its effects are evident in over fifty million people worldwide. This study focused on objective classification of the multiple states involved in the brain's epileptiform activity. Four datasets from three different rodent hippocampal preparations were explored, wherein seizure-like-events (SLE) were induced by the perfusion of a low - Mg(2+) /high-K(+) solution or 4-Aminopyridine. Local field potentials were recorded from CA3 pyramidal neurons and interneurons and modeled as Markov processes. Specifically, hidden Markov models (HMM) were used to determine the nature of the states present. Properties of the Hilbert transform were used to construct the feature spaces for HMM training. By sequentially applying the HMM training algorithm, multiple states were identified both in episodes of SLE and nonSLE activity. Specifically, preSLE and postSLE states were differentiated and multiple inner SLE states were identified. This was accomplished using features extracted from the lower frequencies (1-4 Hz, 4-8 Hz) alongside those of both the low- (40-100 Hz) and high-gamma (100-200 Hz) of the recorded electrical activity. The learning paradigm of this HMM-based system eliminates the inherent bias associated with other learning algorithms that depend on predetermined state segmentation and renders it an appropriate candidate for SLE classification.

A versatile method for confirmatory evaluation of the effects of a covariate in multiple models

DEFF Research Database (Denmark)

Pipper, Christian Bressen; Ritz, Christian; Bisgaard, Hans

2012-01-01

to provide a fine-tuned control of the overall type I error in a wide range of epidemiological experiments where in reality no other useful alternative exists. The methodology proposed is applied to a multiple-end-point study of the effect of neonatal bacterial colonization on development of childhood asthma.......Modern epidemiology often requires testing of the effect of a covariate on multiple end points from the same study. However, popular state of the art methods for multiple testing require the tests to be evaluated within the framework of a single model unifying all end points. This severely limits...

Modeling freedom from progression for standard-risk medulloblastoma: a mathematical tumor control model with multiple modes of failure

DEFF Research Database (Denmark)

Brodin, Nils Patrik; Vogelius, Ivan R.; Bjørk-Eriksson, Thomas

2013-01-01

As pediatric medulloblastoma (MB) is a relatively rare disease, it is important to extract the maximum information from trials and cohort studies. Here, a framework was developed for modeling tumor control with multiple modes of failure and time-to-progression for standard-risk MB, using published...

Occupational stress and psychopathology in health professionals: an explorative study with the multiple indicators multiple causes (MIMIC) model approach.

Science.gov (United States)

Iliceto, Paolo; Pompili, Maurizio; Spencer-Thomas, Sally; Ferracuti, Stefano; Erbuto, Denise; Lester, David; Candilera, Gabriella; Girardi, Paolo

2013-03-01

Occupational stress is a multivariate process involving sources of pressure, psycho-physiological distress, locus of control, work dissatisfaction, depression, anxiety, mental health disorders, hopelessness, and suicide ideation. Healthcare professionals are known for higher rates of occupational-related distress (burnout and compassion fatigue) and higher rates of suicide. The purpose of this study was to explain the relationships between occupational stress and some psychopathological dimensions in a sample of health professionals. We investigated 156 nurses and physicians, 62 males and 94 females, who were administered self-report questionnaires to assess occupational stress [occupational stress inventory (OSI)], temperament (temperament evaluation of Memphis, Pisa, Paris, and San Diego autoquestionnaire), and hopelessness (Beck hopelessness scale). The best Multiple Indicators Multiple Causes model with five OSI predictors yielded the following results: χ2(9) = 14.47 (p = 0.11); χ2/df = 1.60; comparative fit index = 0.99; root mean square error of approximation = 0.05. This model provided a good fit to the empirical data, showing a strong direct influence of casual variables such as work dissatisfaction, absence of type A behavior, and especially external locus of control, psychological and physiological distress on latent variable psychopathology. Occupational stress is in a complex relationship with temperament and hopelessness and also common among healthcare professionals.

More Popsicle-Stick Multiplication.

Science.gov (United States)

Dunkels, Andrejs

1982-01-01

A way to use tongue depressors in a model of multiplication is presented. The original intent was to use the sticks to teach about fractions, but "mistakes" in student responses led to new ideas. It is felt that teachers should use the model in teaching multiplication. (MP)

Atomic force microscopy reveals multiple patterns of antenna organization in purple bacteria: implications for energy transduction mechanisms and membrane modeling.

Science.gov (United States)

Sturgis, James N; Niederman, Robert A

2008-01-01

Recent topographs of the intracytoplasmic membrane (ICM) of purple bacteria obtained by atomic force microscopy (AFM) have provided the first surface views of the native architecture of a multicomponent biological membrane at submolecular resolution, representing an important landmark in structural biology. A variety of species-dependent, closely packed arrangements of light-harvesting (LH) complexes was revealed: the most highly organized was found in Rhodobacter sphaeroides in which the peripheral LH2 antenna was seen either in large clusters or in fixed rows interspersed among ordered arrays of dimeric LH1-reaction center (RC) core complexes. A more random organization was observed in other species containing both the LH1 and LH2 complexes, as typified by Rhododspirillum photometricum with randomly packed monomeric LH1-RC core complexes intermingled with large, paracrystalline domains of LH2 antenna. Surprisingly, no structures that could be identified as the ATP synthase or cytochrome bc (1) complexes were observed, which may reflect their localization at ICM vesicle poles or in curved membrane areas, out of view from the flat regions imaged by AFM. This possible arrangement of energy transducing complexes has required a reassessment of energy tranduction mechanisms which place the cytochrome bc (1) complex in close association with the RC. Instead, more plausible proposals must account for the movement of quinone redox species over considerable membrane distances on appropriate time scales. AFM, together with atomic resolution structures are also providing the basis for molecular modeling of the ICM that is leading to an improved picture of the supramolecular organization of photosynthetic complexes, as well as the forces that drive their segregation into distinct domains.

Three-dimensional simulations of Bingham plastic flows with the multiple-relaxation-time lattice Boltzmann model

OpenAIRE

Song-Gui Chen; Chuan-Hu Zhang; Yun-Tian Feng; Qi-Cheng Sun; Feng Jin

2016-01-01

This paper presents a three-dimensional (3D) parallel multiple-relaxation-time lattice Boltzmann model (MRT-LBM) for Bingham plastics which overcomes numerical instabilities in the simulation of non-Newtonian fluids for the Bhatnagar–Gross–Krook (BGK) model. The MRT-LBM and several related mathematical models are briefly described. Papanastasiou’s modified model is incorporated for better numerical stability. The impact of the relaxation parameters of the model is studied in detail. The MRT-L...

A Hidden Markov Model Representing the Spatial and Temporal Correlation of Multiple Wind Farms

DEFF Research Database (Denmark)

Fang, Jiakun; Su, Chi; Hu, Weihao

2015-01-01

To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps is ado....... The proposed statistical modeling framework is compatible with the sequential power system reliability analysis. A case study on optimal sizing and location of fast-response regulation sources is presented.......To accommodate the increasing wind energy with stochastic nature becomes a major issue on power system reliability. This paper proposes a methodology to characterize the spatiotemporal correlation of multiple wind farms. First, a hierarchical clustering method based on self-organizing maps...... is adopted to categorize the similar output patterns of several wind farms into joint states. Then the hidden Markov model (HMM) is then designed to describe the temporal correlations among these joint states. Unlike the conventional Markov chain model, the accumulated wind power is taken into consideration...

Predictive model of Amorphophallus muelleri growth in some agroforestry in East Java by multiple regression analysis

Directory of Open Access Journals (Sweden)

BUDIMAN

2012-01-01

Full Text Available Budiman, Arisoesilaningsih E. 2012. Predictive model of Amorphophallus muelleri growth in some agroforestry in East Java by multiple regression analysis. Biodiversitas 13: 18-22. The aims of this research was to determine the multiple regression models of vegetative and corm growth of Amorphophallus muelleri Blume in some age variations and habitat conditions of agroforestry in East Java. Descriptive exploratory research method was conducted by systematic random sampling at five agroforestries on four plantations in East Java: Saradan, Bojonegoro, Nganjuk and Blitar. In each agroforestry, we observed A. muelleri vegetative and corm growth on four growing age (1, 2, 3 and 4 years old respectively as well as environmental variables such as altitude, vegetation, climate and soil conditions. Data were analyzed using descriptive statistics to compare A. muelleri habitat in five agroforestries. Meanwhile, the influence and contribution of each environmental variable to the growth of A. muelleri vegetative and corm were determined using multiple regression analysis of SPSS 17.0. The multiple regression models of A. muelleri vegetative and corm growth were generated based on some characteristics of agroforestries and age showed high validity with R2 = 88-99%. Regression model showed that age, monthly temperatures, percentage of radiation and soil calcium (Ca content either simultaneously or partially determined the growth of A. muelleri vegetative and corm. Based on these models, the A. muelleri corm reached the optimal growth after four years of cultivation and they will be ready to be harvested. Additionally, the soil Ca content should reach 25.3 me.hg-1 as Sugihwaras agroforestry, with the maximal radiation of 60%.

The biophysical model for accuracy of cellular sensing spatial gradients of multiple chemoattractants

International Nuclear Information System (INIS)

Chang, Qiang; Zuo, Li

2013-01-01

Spatial gradients of surrounding chemoattractants are the key factors in determining the directionality of eukaryotic cell movement. Thus, it is important for cells to accurately measure the spatial gradients of surrounding chemoattractants. Here, we study the precision of sensing the spatial gradients of multiple chemoattractants using cooperative receptor clusters. Cooperative receptors on cells are modeled as an Ising chain of Monod–Wyman–Changeux clusters subject to multiple chemical-gradient fields to study the physical limits of multiple chemoattractants spatial gradients sensing. We found that eukaryotic cells cannot sense each chemoattractant gradient individually. Instead, cells can only sense a weighted sum of surrounding chemical gradients. Moreover, the precision of sensing one chemical gradient is signicantly affected by coexisting chemoattractant concentrations. These findings can provide a further insight into the role of chemoattractants in immune response and help develop novel treatments for inflammatory diseases. (paper)

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

Science.gov (United States)

Tokuda, Tomoki; Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions.

Directory of Open Access Journals (Sweden)

Tomoki Tokuda

Full Text Available We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

Science.gov (United States)

Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

Stability Properties of Network Diversity Multiple Access with Multiple-Antenna Reception and Imperfect Collision Multiplicity Estimation

Directory of Open Access Journals (Sweden)

Ramiro Samano-Robles

2013-01-01

Full Text Available In NDMA (network diversity multiple access, protocol-controlled retransmissions are used to create a virtual MIMO (multiple-input multiple-output system, where collisions can be resolved via source separation. By using this retransmission diversity approach for collision resolution, NDMA is the family of random access protocols with the highest potential throughput. However, several issues remain open today in the modeling and design of this type of protocol, particularly in terms of dynamic stable performance and backlog delay. This paper attempts to partially fill this gap by proposing a Markov model for the study of the dynamic-stable performance of a symmetrical and non-blind NDMA protocol assisted by a multiple-antenna receiver. The model is useful in the study of stability aspects in terms of the backlog-user distribution and average backlog delay. It also allows for the investigation of the different states of the system and the transition probabilities between them. Unlike previous works, the proposed approach considers the imperfect estimation of the collision multiplicity, which is a crucial process to the performance of NDMA. The results suggest that NDMA improves not only the throughput performance over previous solutions, but also the average number of backlogged users, the average backlog delay and, in general, the stability of random access protocols. It is also shown that when multiuser detection conditions degrade, ALOHA-type backlog retransmission becomes relevant to the stable operation of NDMA.

Multiple attractors and dynamics in an OLG model with productive environment

Science.gov (United States)

Caravaggio, Andrea; Sodini, Mauro

2018-05-01

This work analyses an overlapping generations model in which economic activity depends on the exploitation of a free-access natural resource. In addition, public expenditures for environmental maintenance are assumed. By characterising some properties of the map and performing numerical simulations, we investigate consequences of the interplay between environmental public expenditure and private sector. In particular, we identify different scenarios in which multiple equilibria as well as complex dynamics may arise.

Specification and testing of Multiplicative Time-Varying GARCH models with applications

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

2017-01-01

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smooth...... is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns....

On the representability of complete genomes by multiple competing finite-context (Markov models.

Directory of Open Access Journals (Sweden)

Armando J Pinho

Full Text Available A finite-context (Markov model of order k yields the probability distribution of the next symbol in a sequence of symbols, given the recent past up to depth k. Markov modeling has long been applied to DNA sequences, for example to find gene-coding regions. With the first studies came the discovery that DNA sequences are non-stationary: distinct regions require distinct model orders. Since then, Markov and hidden Markov models have been extensively used to describe the gene structure of prokaryotes and eukaryotes. However, to our knowledge, a comprehensive study about the potential of Markov models to describe complete genomes is still lacking. We address this gap in this paper. Our approach relies on (i multiple competing Markov models of different orders (ii careful programming techniques that allow orders as large as sixteen (iii adequate inverted repeat handling (iv probability estimates suited to the wide range of context depths used. To measure how well a model fits the data at a particular position in the sequence we use the negative logarithm of the probability estimate at that position. The measure yields information profiles of the sequence, which are of independent interest. The average over the entire sequence, which amounts to the average number of bits per base needed to describe the sequence, is used as a global performance measure. Our main conclusion is that, from the probabilistic or information theoretic point of view and according to this performance measure, multiple competing Markov models explain entire genomes almost as well or even better than state-of-the-art DNA compression methods, such as XM, which rely on very different statistical models. This is surprising, because Markov models are local (short-range, contrasting with the statistical models underlying other methods, where the extensive data repetitions in DNA sequences is explored, and therefore have a non-local character.

Choice experiments versus revealed choice models : a before-after study of consumer spatial shopping behavior

NARCIS (Netherlands)

Timmermans, H.J.P.; Borgers, A.W.J.; Waerden, van der P.J.H.J.

1992-01-01

The purpose of this article is to compare a set of multinomial logit models derived from revealed choice data and a decompositional choice model derived from experimental data in terms of predictive success in the context of consumer spatial shopping behavior. Data on consumer shopping choice

Neural correlates reveal sub-lexical orthography and phonology during reading aloud: A review

Directory of Open Access Journals (Sweden)

Kalinka eTimmer

2014-08-01

Full Text Available The sub-lexical conversion of graphemes-to-phonemes (GPC during reading has been investigated extensively with behavioral measures, as well as event-related potentials (ERPs. Most research utilizes silent reading (e.g., lexical decision task for which phonological activation is not a necessity. However, recent research employed reading aloud to capture sub-lexical GPC. The masked priming paradigm avoids strategic processing and is therefore well suitable for capturing sub-lexical processing instead of lexical effects. By employing ERPs, the on-line time course of sub-lexical GPC can be observed before the overt response. ERPs have revealed that besides phonological activation, as revealed by behavioral studies, there is also early orthographic activation. This review describes studies in one’s native language, in one’s second language, and in a cross-language situation. We discuss the implications the ERP results have on different (computational models. First, the ERP results show that computational models should assume an early locus of the grapheme-to-phoneme-conversion (GPC. Second, cross-language studies reveal that the phonological representations from both languages of a bilingual become activated automatically and the phonology belonging to the context is selected rapidly. Therefore, it is important to extend the scope of computational models of reading (aloud to multiple lexicons.

Covariance approximation for large multivariate spatial data sets with an application to multiple climate model errors

KAUST Repository

Sang, Huiyan

2011-12-01

This paper investigates the cross-correlations across multiple climate model errors. We build a Bayesian hierarchical model that accounts for the spatial dependence of individual models as well as cross-covariances across different climate models. Our method allows for a nonseparable and nonstationary cross-covariance structure. We also present a covariance approximation approach to facilitate the computation in the modeling and analysis of very large multivariate spatial data sets. The covariance approximation consists of two parts: a reduced-rank part to capture the large-scale spatial dependence, and a sparse covariance matrix to correct the small-scale dependence error induced by the reduced rank approximation. We pay special attention to the case that the second part of the approximation has a block-diagonal structure. Simulation results of model fitting and prediction show substantial improvement of the proposed approximation over the predictive process approximation and the independent blocks analysis. We then apply our computational approach to the joint statistical modeling of multiple climate model errors. © 2012 Institute of Mathematical Statistics.

Inference regarding multiple structural changes in linear models with endogenous regressors☆

Science.gov (United States)

Hall, Alastair R.; Han, Sanggohn; Boldea, Otilia

2012-01-01

This paper considers the linear model with endogenous regressors and multiple changes in the parameters at unknown times. It is shown that minimization of a Generalized Method of Moments criterion yields inconsistent estimators of the break fractions, but minimization of the Two Stage Least Squares (2SLS) criterion yields consistent estimators of these parameters. We develop a methodology for estimation and inference of the parameters of the model based on 2SLS. The analysis covers the cases where the reduced form is either stable or unstable. The methodology is illustrated via an application to the New Keynesian Phillips Curve for the US. PMID:23805021

Adjustment modes in the trajectory of progressive multiple sclerosis: a qualitative study and conceptual model.

Science.gov (United States)

Bogosian, Angeliki; Morgan, Myfanwy; Bishop, Felicity L; Day, Fern; Moss-Morris, Rona

2017-03-01

We examined cognitive and behavioural challenges and adaptations for people with progressive multiple sclerosis (MS) and developed a preliminary conceptual model of changes in adjustment over time. Using theoretical sampling, 34 semi-structured interviews were conducted with people with MS. Participants were between 41 and 77 years of age. Thirteen were diagnosed with primary progressive MS and 21 with secondary progressive MS. Data were analysed using a grounded theory approach. Participants described initially bracketing the illness off and carrying on their usual activities but this became problematic as the condition progressed and they employed different adjustment modes to cope with increased disabilities. Some scaled back their activities to live a more comfortable life, others identified new activities or adapted old ones, whereas at times, people disengaged from the adjustment process altogether and resigned to their condition. Relationships with partners, emotional reactions, environment and perception of the environment influenced adjustment, while people were often flexible and shifted among modes. Adjusting to a progressive condition is a fluid process. Future interventions can be tailored to address modifiable factors at different stages of the condition and may involve addressing emotional reactions concealing/revealing the condition and perceptions of the environment.

Latest Holocene Climate Variability revealed by a high-resolution multiple Proxy Record off Lisbon (Portugal)

Science.gov (United States)

Abrantes, F.; Lebreiro, S.; Ferreira, A.; Gil, I.; Jonsdottir, H.; Rodrigues, T.; Kissel, C.; Grimalt, J.

2003-04-01

The North Atlantic Oscillation (NAO) is known to have a major influence on the wintertime climate of the Atlantic basin and surrounding countries, determining precipitation and wind conditions at mid-latitudes. A comparison of Hurrel's NAO index to the mean winter (January-March) discharge of the Iberian Tagus River reveals a good negative correlation to negative NAO, while the years of largest upwelling anomalies, as referred in the literature, appear to be in good agreement with positive NAO. On this basis, a better understanding of the long-term variability of the NAO and Atlantic climate variability can be gained from high-resolution climate records from the Lisbon area. Climate variability of the last 2,000 years is assessed through a multiple proxy study of sedimentary sequences recovered from the Tagus prodelta deposition center, off Lisbon (Western Iberia). Physical properties, XRF and magnetic properties from core logging, grain size, δ18O, TOC, CaCO3, total alkenones, n-alkanes, alkenone SST, diatoms, benthic and planktonic foraminiferal assemblage compositions and fluxes are the proxies employed. The age model for site D13902 is based on AMS C-14 dates from mollusc and planktonic foraminifera shells, the reservoir correction for which was obtained by dating 3 pre-bomb, mollusc shells from the study area. Preliminary results indicate a Little Ice Age (LIA - 1300 - 1600 AD) alkenone derived SSTs around 15 degC followed by a sharp and rapid increase towards 19 degC. In spite the strong variability observed for most records, this low temperature interval is marked by a general increase in organic carbon, total alkenone concentration, diatom and foraminiferal abundances, as well as an increase in the sediment fine fraction and XRF determined Fe content, pointing to important river input and higher productivity. The Medieval Warm Period (1080 - 1300 AD) is characterized by 17-18 degC SSTs, increased mean grain size, but lower magnetic susceptibility and Fe

Behavioural mapping of a pelagic seabird: combining multiple sensors and a hidden Markov model reveals the distribution of at-sea behaviour

Science.gov (United States)

Dean, Ben; Freeman, Robin; Kirk, Holly; Leonard, Kerry; Phillips, Richard A.; Perrins, Chris M.; Guilford, Tim

2013-01-01

The use of miniature data loggers is rapidly increasing our understanding of the movements and habitat preferences of pelagic seabirds. However, objectively interpreting behavioural information from the large volumes of highly detailed data collected by such devices can be challenging. We combined three biologging technologies—global positioning system (GPS), saltwater immersion and time–depth recorders—to build a detailed picture of the at-sea behaviour of the Manx shearwater (Puffinus puffinus) during the breeding season. We used a hidden Markov model to explore discrete states within the combined GPS and immersion data, and found that behaviour could be organized into three principal activities representing (i) sustained direct flight, (ii) sitting on the sea surface, and (iii) foraging, comprising tortuous flight interspersed with periods of immersion. The additional logger data verified that the foraging activity corresponded well to the occurrence of diving. Applying this approach to a large tracking dataset revealed that birds from two different colonies foraged in local waters that were exclusive, but overlapped in one key area: the Irish Sea Front (ISF). We show that the allocation of time to each activity differed between colonies, with birds breeding furthest from the ISF spending the greatest proportion of time engaged in direct flight and the smallest proportion of time engaged in foraging activity. This type of analysis has considerable potential for application in future biologging studies and in other taxa. PMID:23034356

Dysregulated neuronal activity patterns implicate corticostriatal circuit dysfunction in multiple rodent models of Huntington’s disease

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Benjamin R. Miller

2011-05-01

Full Text Available Huntington’s disease (HD is an autosomal dominant neurodegenerative disorder that targets the corticostriatal system and results in progressive deterioration of cognitive, emotional, and motor skills. Although cortical and striatal neurons are widely studied in animal models of HD, there is little information on neuronal function during expression of the HD behavioral phenotype. To address this knowledge gap, we used chronically implanted micro-wire bundles to record extracellular spikes and local field potentials (LFPs in truncated (R6/1 and R6/2 and full-length (knock-in, KI mouse models as well as in tgHD rats behaving in an open-field arena. Spike activity was recorded in the striatum of all models and in prefrontal cortex (PFC of R6/2 and KI mice, and in primary motor cortex (M1 of R6/2 mice. We also recorded LFP activity in R6/2 striatum. All HD models exhibited altered neuronal activity relative to wild-type (WT controls. Although there was no consistent effect on firing rate across models and brain areas, burst firing was reduced in striatum, PFC, and M1 of R6/2 mice, and in striatum of KI mice. Consistent with a decline in bursting, the interspike-interval coefficient of variation was reduced in all regions of all models, except PFC of KI mice and striatum of tgHD rats. Among simultaneously recorded neuron pairs, correlated firing was reduced in all brain regions of all models, while coincident bursting, which measures the temporal overlap between bursting pairs, was reduced in striatum of all models as well as in M1 of R6/2's. Preliminary analysis of striatal LFPs revealed aberrant behavior-related oscillations in the delta to theta range and in gamma activity. Collectively, our results indicate that disrupted corticostriatal processing occurs across multiple HD models despite differences in the severity of the behavioral phenotype. Efforts aimed at normalizing corticostriatal activity may hold the key to developing new HD

A diagnostic tree model for polytomous responses with multiple strategies.

Science.gov (United States)

Ma, Wenchao

2018-04-23

Constructed-response items have been shown to be appropriate for cognitively diagnostic assessments because students' problem-solving procedures can be observed, providing direct evidence for making inferences about their proficiency. However, multiple strategies used by students make item scoring and psychometric analyses challenging. This study introduces the so-called two-digit scoring scheme into diagnostic assessments to record both students' partial credits and their strategies. This study also proposes a diagnostic tree model (DTM) by integrating the cognitive diagnosis models with the tree model to analyse the items scored using the two-digit rubrics. Both convergent and divergent tree structures are considered to accommodate various scoring rules. The MMLE/EM algorithm is used for item parameter estimation of the DTM, and has been shown to provide good parameter recovery under varied conditions in a simulation study. A set of data from TIMSS 2007 mathematics assessment is analysed to illustrate the use of the two-digit scoring scheme and the DTM. © 2018 The British Psychological Society.

The intergenerational multiple deficit model and the case of dyslexia

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Elsje evan Bergen

2014-06-01

Full Text Available Which children go on to develop dyslexia? Since dyslexia has a multifactorial aetiology, this question can be restated as: What are the factors that put children at high risk for developing dyslexia? It is argued that a useful theoretical framework to address this question is Pennington’s (2006 multiple deficit model (MDM. This model replaces models that attribute dyslexia to a single underlying cause. Subsequently, the generalist genes hypothesis for learning (disabilities (Plomin & Kovas, 2005 is described and integrated with the MDM. Finally, findings are presented from a longitudinal study with children at family risk for dyslexia. Such studies can contribute to testing and specifying the MDM. In this study, risk factors at both the child and family level were investigated. This led to the proposed intergenerational MDM, in which both parents confer liability via intertwined genetic and environmental pathways. Future scientific directions are discussed to investigate parent-offspring resemblance and transmission patterns, which will shed new light on disorder aetiology.

Multiple regression equations modelling of groundwater of Ajmer-Pushkar railway line region, Rajasthan (India).

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Mathur, Praveen; Sharma, Sarita; Soni, Bhupendra

2010-01-01

In the present work, an attempt is made to formulate multiple regression equations using all possible regressions method for groundwater quality assessment of Ajmer-Pushkar railway line region in pre- and post-monsoon seasons. Correlation studies revealed the existence of linear relationships (r 0.7) for electrical conductivity (EC), total hardness (TH) and total dissolved solids (TDS) with other water quality parameters. The highest correlation was found between EC and TDS (r = 0.973). EC showed highly significant positive correlation with Na, K, Cl, TDS and total solids (TS). TH showed highest correlation with Ca and Mg. TDS showed significant correlation with Na, K, SO4, PO4 and Cl. The study indicated that most of the contamination present was water soluble or ionic in nature. Mg was present as MgCl2; K mainly as KCl and K2SO4, and Na was present as the salts of Cl, SO4 and PO4. On the other hand, F and NO3 showed no significant correlations. The r2 values and F values (at 95% confidence limit, alpha = 0.05) for the modelled equations indicated high degree of linearity among independent and dependent variables. Also the error % between calculated and experimental values was contained within +/- 15% limit.

Asymmetric biotic interactions and abiotic niche differences revealed by a dynamic joint species distribution model.

Science.gov (United States)

Lany, Nina K; Zarnetske, Phoebe L; Schliep, Erin M; Schaeffer, Robert N; Orians, Colin M; Orwig, David A; Preisser, Evan L

2018-05-01

A species' distribution and abundance are determined by abiotic conditions and biotic interactions with other species in the community. Most species distribution models correlate the occurrence of a single species with environmental variables only, and leave out biotic interactions. To test the importance of biotic interactions on occurrence and abundance, we compared a multivariate spatiotemporal model of the joint abundance of two invasive insects that share a host plant, hemlock woolly adelgid (HWA; Adelges tsugae) and elongate hemlock scale (EHS; Fiorina externa), to independent models that do not account for dependence among co-occurring species. The joint model revealed that HWA responded more strongly to abiotic conditions than EHS. Additionally, HWA appeared to predispose stands to subsequent increase of EHS, but HWA abundance was not strongly dependent on EHS abundance. This study demonstrates how incorporating spatial and temporal dependence into a species distribution model can reveal the dependence of a species' abundance on other species in the community. Accounting for dependence among co-occurring species with a joint distribution model can also improve estimation of the abiotic niche for species affected by interspecific interactions. © 2018 by the Ecological Society of America.

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

Science.gov (United States)

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Multiple Intelligences and quotient spaces

OpenAIRE

Malatesta, Mike; Quintana, Yamilet

2006-01-01

The Multiple Intelligence Theory (MI) is one of the models that study and describe the cognitive abilities of an individual. In [7] is presented a referential system which allows to identify the Multiple Intelligences of the students of a course and to classify the level of development of such Intelligences. Following this tendency, the purpose of this paper is to describe the model of Multiple Intelligences as a quotient space, and also to study the Multiple Intelligences of an individual in...

Integrating data from multiple sources for insights into demographic processes: Simulation studies and proof of concept for hierarchical change-in-ratio models.

Science.gov (United States)

Nilsen, Erlend B; Strand, Olav

2018-01-01

We developed a model for estimating demographic rates and population abundance based on multiple data sets revealing information about population age- and sex structure. Such models have previously been described in the literature as change-in-ratio models, but we extend the applicability of the models by i) using time series data allowing the full temporal dynamics to be modelled, by ii) casting the model in an explicit hierarchical modelling framework, and by iii) estimating parameters based on Bayesian inference. Based on sensitivity analyses we conclude that the approach developed here is able to obtain estimates of demographic rate with high precision whenever unbiased data of population structure are available. Our simulations revealed that this was true also when data on population abundance are not available or not included in the modelling framework. Nevertheless, when data on population structure are biased due to different observability of different age- and sex categories this will affect estimates of all demographic rates. Estimates of population size is particularly sensitive to such biases, whereas demographic rates can be relatively precisely estimated even with biased observation data as long as the bias is not severe. We then use the models to estimate demographic rates and population abundance for two Norwegian reindeer (Rangifer tarandus) populations where age-sex data were available for all harvested animals, and where population structure surveys were carried out in early summer (after calving) and late fall (after hunting season), and population size is counted in winter. We found that demographic rates were similar regardless whether we include population count data in the modelling, but that the estimated population size is affected by this decision. This suggest that monitoring programs that focus on population age- and sex structure will benefit from collecting additional data that allow estimation of observability for different age- and

A Hybrid Multiple Criteria Decision Making Model for Supplier Selection

Directory of Open Access Journals (Sweden)

Chung-Min Wu

2013-01-01

Full Text Available The sustainable supplier selection would be the vital part in the management of a sustainable supply chain. In this study, a hybrid multiple criteria decision making (MCDM model is applied to select optimal supplier. The fuzzy Delphi method, which can lead to better criteria selection, is used to modify criteria. Considering the interdependence among the selection criteria, analytic network process (ANP is then used to obtain their weights. To avoid calculation and additional pairwise comparisons of ANP, a technique for order preference by similarity to ideal solution (TOPSIS is used to rank the alternatives. The use of a combination of the fuzzy Delphi method, ANP, and TOPSIS, proposing an MCDM model for supplier selection, and applying these to a real case are the unique features of this study.

Design and selection of load control strategies using a multiple objective model and evolutionary algorithms

International Nuclear Information System (INIS)

Gomes, Alvaro; Antunes, Carlos Henggeler; Martins, Antonio Gomes

2005-01-01

This paper aims at presenting a multiple objective model to evaluate the attractiveness of the use of demand resources (through load management control actions) by different stakeholders and in diverse structure scenarios in electricity systems. For the sake of model flexibility, the multiple (and conflicting) objective functions of technical, economical and quality of service nature are able to capture distinct market scenarios and operating entities that may be interested in promoting load management activities. The computation of compromise solutions is made by resorting to evolutionary algorithms, which are well suited to tackle multiobjective problems of combinatorial nature herein involving the identification and selection of control actions to be applied to groups of loads. (Author)

LAI inversion from optical reflectance using a neural network trained with a multiple scattering model

Science.gov (United States)

Smith, James A.

1992-01-01

The inversion of the leaf area index (LAI) canopy parameter from optical spectral reflectance measurements is obtained using a backpropagation artificial neural network trained using input-output pairs generated by a multiple scattering reflectance model. The problem of LAI estimation over sparse canopies (LAI 1000 percent for low LAI. Minimization methods applied to merit functions constructed from differences between measured reflectances and predicted reflectances using multiple-scattering models are unacceptably sensitive to a good initial guess for the desired parameter. In contrast, the neural network reported generally yields absolute percentage errors of <30 percent when weighting coefficients trained on one soil type were applied to predicted canopy reflectance at a different soil background.

Estimating Ambiguity Preferences and Perceptions in Multiple Prior Models: Evidence from the Field

NARCIS (Netherlands)

S.G. Dimmock (Stephen); R.R.P. Kouwenberg (Roy); O.S. Mitchell (Olivia); K. Peijnenburg (Kim)

2015-01-01

markdownabstractWe develop a tractable method to estimate multiple prior models of decision-making under ambiguity. In a representative sample of the U.S. population, we measure ambiguity attitudes in the gain and loss domains. We find that ambiguity aversion is common for uncertain events of

Modeling transport pricing with multiple stakeholders. Working paper : Methodology and a case study

NARCIS (Netherlands)

Smits, E.

2012-01-01

Pricing measures (e.g., a kilometre charge or cordon toll) are used to improve the external effects of transportation (e.g., congestion or emissions). This working paper presents a planning model for pricing while taking the preferences and interactions of multiple stakeholders (e.g., governments or

Risk estimation of multiple recurrence and progression of non muscle invasive bladder carcinoma using new mathematical models.

Science.gov (United States)

Luján, S; Santamaría, C; Pontones, J L; Ruiz-Cerdá, J L; Trassierra, M; Vera-Donoso, C D; Solsona, E; Jiménez-Cruz, F

2014-12-01

To apply new mathematical models according to Non Muscle Invasive Bladder Carcinoma (NMIBC) biological characteristics and enabling an accurate risk estimation of multiple recurrences and tumor progression. The classical Cox model is not valid for the assessment of this kind of events becausethe time betweenrecurrencesin the same patientmay be stronglycorrelated. These new models for risk estimation of recurrence/progression lead to individualized monitoring and treatment plan. 960 patients with primary NMIBC were enrolled. The median follow-up was 48.1 (3-160) months. Results obtained were validated in 240 patients from other center. Transurethral resection of the bladder (TURB) and random bladder biopsy were performed. Subsequently, adjuvant localized chemotherapy was performed. The variables analyzed were: number and tumor size, age, chemotherapy and histopathology. The endpoints were time to recurrence and time to progression. Cox model and its extensions were used as joint frailty model for multiple recurrence and progression. Model accuracy was calculated using Harrell's concordance index (c-index). 468 (48.8%) patients developed at least one tumor recurrence and tumor progression was reported in 52 (5.4%) patients. Variables for multiple-recurrence risk are: age, grade, number, size, treatment and the number of prior recurrences. All these together with age, stage and grade are the variables for progression risk. Concordance index was 0.64 and 0.85 for multiple recurrence and progression respectively. the high concordance reported besides to the validation process in external source, allow accurate multi-recurrence/progression risk estimation. As consequence, it is possible to schedule a follow-up and treatment individualized plan in new and recurrent NMCB cases. Copyright © 2014 AEU. Published by Elsevier Espana. All rights reserved.

Multiple player tracking in sports video: a dual-mode two-way bayesian inference approach with progressive observation modeling.

Science.gov (United States)

Xing, Junliang; Ai, Haizhou; Liu, Liwei; Lao, Shihong

2011-06-01

Multiple object tracking (MOT) is a very challenging task yet of fundamental importance for many practical applications. In this paper, we focus on the problem of tracking multiple players in sports video which is even more difficult due to the abrupt movements of players and their complex interactions. To handle the difficulties in this problem, we present a new MOT algorithm which contributes both in the observation modeling level and in the tracking strategy level. For the observation modeling, we develop a progressive observation modeling process that is able to provide strong tracking observations and greatly facilitate the tracking task. For the tracking strategy, we propose a dual-mode two-way Bayesian inference approach which dynamically switches between an offline general model and an online dedicated model to deal with single isolated object tracking and multiple occluded object tracking integrally by forward filtering and backward smoothing. Extensive experiments on different kinds of sports videos, including football, basketball, as well as hockey, demonstrate the effectiveness and efficiency of the proposed method.

Cerebral metastases from multiple myeloma

International Nuclear Information System (INIS)

Norum, J.; Wist, E.; Dahl, I.M.; University Hospital, Tromsoe

1991-01-01

The authors report a patient with multiple intracerebral lesions from myeloma. The case also demonstrates that myeloma is a radiosensitive tumour and that radiotherapy is important to keep in mind when intracranial lesions are revealed. (orig.)

Analysis of the cartilage proteome from three different mouse models of genetic skeletal diseases reveals common and discrete disease signatures

Directory of Open Access Journals (Sweden)

Peter A. Bell

2013-06-01

Pseudoachondroplasia and multiple epiphyseal dysplasia are genetic skeletal diseases resulting from mutations in cartilage structural proteins. Electron microscopy and immunohistochemistry previously showed that the appearance of the cartilage extracellular matrix (ECM in targeted mouse models of these diseases is disrupted; however, the precise changes in ECM organization and the pathological consequences remain unknown. Our aim was to determine the effects of matrilin-3 and COMP mutations on the composition and extractability of ECM components to inform how these detrimental changes might influence cartilage organization and degeneration. Cartilage was sequentially extracted using increasing denaturants and the extraction profiles of specific proteins determined using SDS-PAGE/Western blotting. Furthermore, the relative composition of protein pools was determined using mass spectrometry for a non-biased semi-quantitative analysis. Western blotting revealed changes in the extraction of matrilins, COMP and collagen IX in mutant cartilage. Mass spectrometry confirmed quantitative changes in the extraction of structural and non-structural ECM proteins, including proteins with roles in cellular processes such as protein folding and trafficking. In particular, genotype-specific differences in the extraction of collagens XII and XIV and tenascins C and X were identified; interestingly, increased expression of several of these genes has recently been implicated in susceptibility and/or progression of murine osteoarthritis. We demonstrated that mutation of matrilin-3 and COMP caused changes in the extractability of other cartilage proteins and that proteomic analyses of Matn3 V194D, Comp T585M and Comp DelD469 mouse models revealed both common and discrete disease signatures that provide novel insight into skeletal disease mechanisms and cartilage degradation.

Efficacy and immunological actions of FAHF-2 in a murine model of multiple food allergies.

Science.gov (United States)

Srivastava, Kamal D; Bardina, Ludmilla; Sampson, Hugh A; Li, Xiu-Min

2012-05-01

Food Allergy Herbal Formula-2 (FAHF-2) prevents anaphylaxis in a murine model of peanut allergy. Multiple food allergies (MFA) are common and associated with a higher risk of anaphylaxis. No well-characterized murine model of sensitization to multiple food allergens exists, and no satisfactory therapy for MFA is currently available. To determine the effect of FAHF-2 in a murine model of MFA. C3H/HeJ mice were orally sensitized to peanut, codfish, and egg concurrently. Oral FAHF-2 treatment commenced 1 day after completing sensitization and continued daily for 7 weeks. Mice were subsequently orally challenged with each allergen. Antibodies in sera from mice simultaneously sensitized with peanut, codfish, and egg recognized major allergens of all 3 foods, demonstrating sensitization to multiple unrelated food allergens (MFA mice). Sham-treated MFA mice exhibited anaphylactic symptoms accompanied by elevation of plasma histamine and hypothermia. In contrast, FAHF-2-treated MFA mice showed no anaphylactic symptoms, normal body temperature, and histamine levels after challenge with each allergen. Protection was accompanied by reduction in allergen-specific immunoglobulin E levels. Allergen-stimulated Th2 cytokine interleukin-4 and interleukin-13 production levels decreased, whereas the Th1 cytokine interferon-γ levels were elevated in cultured splenocytes and mesenteric lymph node cells in FAHF-2-treated mice. We established the first murine model of MFA. FAHF-2 prevents peanut, egg, and fish-induced anaphylactic reactions in this model, suggesting that FAHF-2 may have potential for treating human MFA. Copyright © 2012 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Existence, Multiplicity, and Stability of Positive Solutions of a Predator-Prey Model with Dinosaur Functional Response

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Xiaozhou Feng

2017-01-01

Full Text Available We investigate the property of positive solutions of a predator-prey model with Dinosaur functional response under Dirichlet boundary conditions. Firstly, using the comparison principle and fixed point index theory, the sufficient conditions and necessary conditions on coexistence of positive solutions of a predator-prey model with Dinosaur functional response are established. Secondly, by virtue of bifurcation theory, perturbation theory of eigenvalues, and the fixed point index theory, we establish the bifurcation of positive solutions of the model and obtain the stability and multiplicity of the positive solution under certain conditions. Furthermore, the local uniqueness result is studied when b and d are small enough. Finally, we investigate the multiplicity, uniqueness, and stability of positive solutions when k>0 is sufficiently large.

Attributional Style and Depression in Multiple Sclerosis: The Learned Helplessness Model

OpenAIRE

Vargas, Gray A.; Arnett, Peter A.

2013-01-01

Several etiologic theories have been proposed to explain depression in the general population. Studying these models and modifying them for use in the multiple sclerosis (MS) population may allow us to better understand depression in MS. According to the reformulated learned helplessness (LH) theory, individuals who attribute negative events to internal, stable, and global causes are more vulnerable to depression. This study differentiated attributional style that was or was not related to MS...

Hybrid Multiple Soft-Sensor Models of Grinding Granularity Based on Cuckoo Searching Algorithm and Hysteresis Switching Strategy

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Jie-Sheng Wang

2015-01-01

Full Text Available According to the characteristics of grinding process and accuracy requirements of technical indicators, a hybrid multiple soft-sensor modeling method of grinding granularity is proposed based on cuckoo searching (CS algorithm and hysteresis switching (HS strategy. Firstly, a mechanism soft-sensor model of grinding granularity is deduced based on the technique characteristics and a lot of experimental data of grinding process. Meanwhile, the BP neural network soft-sensor model and wavelet neural network (WNN soft-sensor model are set up. Then, the hybrid multiple soft-sensor model based on the hysteresis switching strategy is realized. That is to say, the optimum model is selected as the current predictive model according to the switching performance index at each sampling instant. Finally the cuckoo searching algorithm is adopted to optimize the performance parameters of hysteresis switching strategy. Simulation results show that the proposed model has better generalization results and prediction precision, which can satisfy the real-time control requirements of grinding classification process.

Multiple-relaxation-time lattice Boltzmann model for incompressible miscible flow with large viscosity ratio and high Péclet number

Science.gov (United States)

Meng, Xuhui; Guo, Zhaoli

2015-10-01

A lattice Boltzmann model with a multiple-relaxation-time (MRT) collision operator is proposed for incompressible miscible flow with a large viscosity ratio as well as a high Péclet number in this paper. The equilibria in the present model are motivated by the lattice kinetic scheme previously developed by Inamuro et al. [Philos. Trans. R. Soc. London, Ser. A 360, 477 (2002), 10.1098/rsta.2001.0942]. The fluid viscosity and diffusion coefficient depend on both the corresponding relaxation times and additional adjustable parameters in this model. As a result, the corresponding relaxation times can be adjusted in proper ranges to enhance the performance of the model. Numerical validations of the Poiseuille flow and a diffusion-reaction problem demonstrate that the proposed model has second-order accuracy in space. Thereafter, the model is used to simulate flow through a porous medium, and the results show that the proposed model has the advantage to obtain a viscosity-independent permeability, which makes it a robust method for simulating flow in porous media. Finally, a set of simulations are conducted on the viscous miscible displacement between two parallel plates. The results reveal that the present model can be used to simulate, to a high level of accuracy, flows with large viscosity ratios and/or high Péclet numbers. Moreover, the present model is shown to provide superior stability in the limit of high kinematic viscosity. In summary, the numerical results indicate that the present lattice Boltzmann model is an ideal numerical tool for simulating flow with a large viscosity ratio and/or a high Péclet number.

Degenerate ground states and multiple bifurcations in a two-dimensional q-state quantum Potts model.

Science.gov (United States)

Dai, Yan-Wei; Cho, Sam Young; Batchelor, Murray T; Zhou, Huan-Qiang

2014-06-01

We numerically investigate the two-dimensional q-state quantum Potts model on the infinite square lattice by using the infinite projected entangled-pair state (iPEPS) algorithm. We show that the quantum fidelity, defined as an overlap measurement between an arbitrary reference state and the iPEPS ground state of the system, can detect q-fold degenerate ground states for the Z_{q} broken-symmetry phase. Accordingly, a multiple bifurcation of the quantum ground-state fidelity is shown to occur as the transverse magnetic field varies from the symmetry phase to the broken-symmetry phase, which means that a multiple-bifurcation point corresponds to a critical point. A (dis)continuous behavior of quantum fidelity at phase transition points characterizes a (dis)continuous phase transition. Similar to the characteristic behavior of the quantum fidelity, the magnetizations, as order parameters, obtained from the degenerate ground states exhibit multiple bifurcation at critical points. Each order parameter is also explicitly demonstrated to transform under the Z_{q} subgroup of the symmetry group of the Hamiltonian. We find that the q-state quantum Potts model on the square lattice undergoes a discontinuous (first-order) phase transition for q=3 and q=4 and a continuous phase transition for q=2 (the two-dimensional quantum transverse Ising model).

Dependence of Xmax and multiplicity of electron and muon on different high energy interaction models

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G Rastegarzadeh

2010-06-01

Full Text Available Different high energy interaction models are the applied in CORSIKA code to simulate Extensive Air Showers (EAS generated by Cosmic Rays (CR. In this work the effects of QGSJET01, QGSJETII, DPMJET, SIBYLL models on Xmax and multiplicity of secondary electrons and muons at observation level are studied.

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

Directory of Open Access Journals (Sweden)

Rui Xue

2015-01-01

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

Optogenetic dissection reveals multiple rhythmogenic modules underlying locomotion

DEFF Research Database (Denmark)

Hägglund, Martin; Dougherty, Kimberly J.; Borgius, Lotta

2013-01-01

flexor motor neuron pools can be recruited into bursting without any activity in other nearby flexor motor neuron pools. Our experiments differentiate among several proposed models for rhythm generation in the vertebrates and show that the basic structure underlying the locomotor network has...

Towards single embryo transfer? Modelling clinical outcomes of potential treatment choices using multiple data sources: predictive models and patient perspectives.

Science.gov (United States)

Roberts, Sa; McGowan, L; Hirst, Wm; Brison, Dr; Vail, A; Lieberman, Ba

2010-07-01

In vitro fertilisation (IVF) treatments involve an egg retrieval process, fertilisation and culture of the resultant embryos in the laboratory, and the transfer of embryos back to the mother over one or more transfer cycles. The first transfer is usually of fresh embryos and the remainder may be cryopreserved for future frozen cycles. Most commonly in UK practice two embryos are transferred (double embryo transfer, DET). IVF techniques have led to an increase in the number of multiple births, carrying an increased risk of maternal and infant morbidity. The UK Human Fertilisation and Embryology Authority (HFEA) has adopted a multiple birth minimisation strategy. One way of achieving this would be by increased use of single embryo transfer (SET). To collate cohort data from treatment centres and the HFEA; to develop predictive models for live birth and twinning probabilities from fresh and frozen embryo transfers and predict outcomes from treatment scenarios; to understand patients' perspectives and use the modelling results to investigate the acceptability of twin reduction policies. A multidisciplinary approach was adopted, combining statistical modelling with qualitative exploration of patients' perspectives: interviews were conducted with 27 couples at various stages of IVF treatment at both UK NHS and private clinics; datasets were collated of over 90,000 patients from the HFEA registry and nearly 9000 patients from five clinics, both over the period 2000-5; models were developed to determine live birth and twin outcomes and predict the outcomes of policies for selecting patients for SET or DET in the fresh cycle following egg retrieval and fertilisation, and the predictions were used in simulations of treatments; two focus groups were convened, one NHS and one web based on a patient organisation's website, to present the results of the statistical analyses and explore potential treatment policies. The statistical analysis revealed no characteristics that

Within- and across-trial dynamics of human EEG reveal cooperative interplay between reinforcement learning and working memory.

Science.gov (United States)

Collins, Anne G E; Frank, Michael J

2018-03-06

Learning from rewards and punishments is essential to survival and facilitates flexible human behavior. It is widely appreciated that multiple cognitive and reinforcement learning systems contribute to decision-making, but the nature of their interactions is elusive. Here, we leverage methods for extracting trial-by-trial indices of reinforcement learning (RL) and working memory (WM) in human electro-encephalography to reveal single-trial computations beyond that afforded by behavior alone. Neural dynamics confirmed that increases in neural expectation were predictive of reduced neural surprise in the following feedback period, supporting central tenets of RL models. Within- and cross-trial dynamics revealed a cooperative interplay between systems for learning, in which WM contributes expectations to guide RL, despite competition between systems during choice. Together, these results provide a deeper understanding of how multiple neural systems interact for learning and decision-making and facilitate analysis of their disruption in clinical populations.

Rank-based model selection for multiple ions quantum tomography

International Nuclear Information System (INIS)

Guţă, Mădălin; Kypraios, Theodore; Dryden, Ian

2012-01-01

The statistical analysis of measurement data has become a key component of many quantum engineering experiments. As standard full state tomography becomes unfeasible for large dimensional quantum systems, one needs to exploit prior information and the ‘sparsity’ properties of the experimental state in order to reduce the dimensionality of the estimation problem. In this paper we propose model selection as a general principle for finding the simplest, or most parsimonious explanation of the data, by fitting different models and choosing the estimator with the best trade-off between likelihood fit and model complexity. We apply two well established model selection methods—the Akaike information criterion (AIC) and the Bayesian information criterion (BIC)—two models consisting of states of fixed rank and datasets such as are currently produced in multiple ions experiments. We test the performance of AIC and BIC on randomly chosen low rank states of four ions, and study the dependence of the selected rank with the number of measurement repetitions for one ion states. We then apply the methods to real data from a four ions experiment aimed at creating a Smolin state of rank 4. By applying the two methods together with the Pearson χ 2 test we conclude that the data can be suitably described with a model whose rank is between 7 and 9. Additionally we find that the mean square error of the maximum likelihood estimator for pure states is close to that of the optimal over all possible measurements. (paper)

Modeling spatial variability of sand-lenses in clay till settings using transition probability and multiple-point geostatistics

DEFF Research Database (Denmark)

Kessler, Timo Christian; Nilsson, Bertel; Klint, Knud Erik

2010-01-01

(TPROGS) of alternating geological facies. The second method, multiple-point statistics, uses training images to estimate the conditional probability of sand-lenses at a certain location. Both methods respect field observations such as local stratigraphy, however, only the multiple-point statistics can...... of sand-lenses in clay till. Sand-lenses mainly account for horizontal transport and are prioritised in this study. Based on field observations, the distribution has been modeled using two different geostatistical approaches. One method uses a Markov chain model calculating the transition probabilities...

Testing Mediation Using Multiple Regression and Structural Equation Modeling Analyses in Secondary Data

Science.gov (United States)

Li, Spencer D.

2011-01-01

Mediation analysis in child and adolescent development research is possible using large secondary data sets. This article provides an overview of two statistical methods commonly used to test mediated effects in secondary analysis: multiple regression and structural equation modeling (SEM). Two empirical studies are presented to illustrate the…

Analyzing Multiple-Choice Questions by Model Analysis and Item Response Curves

Science.gov (United States)

Wattanakasiwich, P.; Ananta, S.

2010-07-01

In physics education research, the main goal is to improve physics teaching so that most students understand physics conceptually and be able to apply concepts in solving problems. Therefore many multiple-choice instruments were developed to probe students' conceptual understanding in various topics. Two techniques including model analysis and item response curves were used to analyze students' responses from Force and Motion Conceptual Evaluation (FMCE). For this study FMCE data from more than 1000 students at Chiang Mai University were collected over the past three years. With model analysis, we can obtain students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts. The model analysis consists of two algorithms—concentration factor and model estimation. This paper only presents results from using the model estimation algorithm to obtain a model plot. The plot helps to identify a class model state whether it is in the misconception region or not. Item response curve (IRC) derived from item response theory is a plot between percentages of students selecting a particular choice versus their total score. Pros and cons of both techniques are compared and discussed.

A multiple-field coupled resistive transition model for superconducting Nb3Sn

Science.gov (United States)

Yang, Lin; Ding, He; Zhang, Xin; Qiao, Li

2016-12-01

A study on the superconducting transition width as functions of the applied magnetic field and strain is performed in superconducting Nb3Sn. A quantitative, yet universal phenomenological resistivity model is proposed. The numerical simulation by the proposed model shows predicted resistive transition characteristics under variable magnetic fields and strain, which in good agreement with the experimental observations. Furthermore, a temperature-modulated magnetoresistance transition behavior in filamentary Nb3Sn conductors can also be well described by the given model. The multiple-field coupled resistive transition model is helpful for making objective determinations of the high-dimensional critical surface of Nb3Sn in the multi-parameter space, offering some preliminary information about the basic vortex-pinning mechanisms, and guiding the design of the quench protection system of Nb3Sn superconducting magnets.

Dynamical nexus of water supply, hydropower and environment based on the modeling of multiple socio-natural processes: from socio-hydrological perspective

Science.gov (United States)

Liu, D.; Wei, X.; Li, H. Y.; Lin, M.; Tian, F.; Huang, Q.

2017-12-01

In the socio-hydrological system, the ecological functions and environmental services, which are chosen to maintain, are determined by the preference of the society, which is making the trade-off among the values of riparian vegetation, fish, river landscape, water supply, hydropower, navigation and so on. As the society develops, the preference of the value will change and the ecological functions and environmental services which are chosen to maintain will change. The aim of the study is to focus on revealing the feedback relationship of water supply, hydropower and environment and the dynamical feedback mechanism at macro-scale, and to establish socio-hydrological evolution model of the watershed based on the modeling of multiple socio-natural processes. The study will aim at the Han River in China, analyze the impact of the water supply and hydropower on the ecology, hydrology and other environment elements, and study the effect on the water supply and hydropower to ensure the ecological and environmental water of the different level. Water supply and ecology are usually competitive. In some reservoirs, hydropower and ecology are synergic relationship while they are competitive in some reservoirs. The study will analyze the multiple mechanisms to implement the dynamical feedbacks of environment to hydropower, set up the quantitative relationship description of the feedback mechanisms, recognize the dominant processes in the feedback relationships of hydropower and environment and then analyze the positive and negative feedbacks in the feedback networks. The socio-hydrological evolution model at the watershed scale will be built and applied to simulate the long-term evolution processes of the watershed of the current situation. Dynamical nexus of water supply, hydropower and environment will be investigated.

Multiplicative properties of quantum channels

Science.gov (United States)

Rahaman, Mizanur

2017-08-01

In this paper, we study the multiplicative behaviour of quantum channels, mathematically described by trace preserving, completely positive maps on matrix algebras. It turns out that the multiplicative domain of a unital quantum channel has a close connection to its spectral properties. A structure theorem (theorem 2.5), which reveals the automorphic property of an arbitrary unital quantum channel on a subalgebra, is presented. Various classes of quantum channels (irreducible, primitive, etc) are then analysed in terms of this stabilising subalgebra. The notion of the multiplicative index of a unital quantum channel is introduced, which measures the number of times a unital channel needs to be composed with itself for the multiplicative algebra to stabilise. We show that the maps that have trivial multiplicative domains are dense in completely bounded norm topology in the set of all unital completely positive maps. Some applications in quantum information theory are discussed.

A Multiple Indicators Multiple Causes (MIMIC) model of internal barriers to drug treatment in China.

Science.gov (United States)

Qi, Chang; Kelly, Brian C; Liao, Yanhui; He, Haoyu; Luo, Tao; Deng, Huiqiong; Liu, Tieqiao; Hao, Wei; Wang, Jichuan

2015-03-01

Although evidence exists for distinct barriers to drug abuse treatment (BDATs), investigations of their inter-relationships and the effect of individual characteristics on the barrier factors have been sparse, especially in China. A Multiple Indicators Multiple Causes (MIMIC) model is applied for this target. A sample of 262 drug users were recruited from three drug rehabilitation centers in Hunan Province, China. We applied a MIMIC approach to investigate the effect of gender, age, marital status, education, primary substance use, duration of primary drug use, and drug treatment experience on the internal barrier factors: absence of problem (AP), negative social support (NSS), fear of treatment (FT), and privacy concerns (PC). Drug users of various characteristics were found to report different internal barrier factors. Younger participants were more likely to report NSS (-0.19, p=0.038) and PC (-0.31, p<0.001). Compared to other drug users, ice users were more likely to report AP (0.44, p<0.001) and NSS (0.25, p=0.010). Drug treatment experiences related to AP (0.20, p=0.012). In addition, differential item functioning (DIF) occurred in three items when participant from groups with different duration of drug use, ice use, or marital status. Individual characteristics had significant effects on internal barriers to drug treatment. On this basis, BDAT perceived by different individuals could be assessed before tactics were utilized to successfully remove perceived barriers to drug treatment. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Multiple attractors and crisis route to chaos in a model food-chain

International Nuclear Information System (INIS)

Upadhyay, Ranjit Kumar

2003-01-01

An attempt has been made to identify the mechanism, which is responsible for the existence of chaos in narrow parameter range in a realistic ecological model food-chain. Analytical and numerical studies of a three species food-chain model similar to a situation likely to be seen in terrestrial ecosystems has been carried out. The study of the model food chain suggests that the existence of chaos in narrow parameter ranges is caused by the crisis-induced sudden death of chaotic attractors. Varying one of the critical parameters in its range while keeping all the others constant, one can monitor the changes in the dynamical behaviour of the system, thereby fixing the regimes in which the system exhibits chaotic dynamics. The computed bifurcation diagrams and basin boundary calculations indicate that crisis is the underlying factor which generates chaotic dynamics in this model food-chain. We investigate sudden qualitative changes in chaotic dynamical behaviour, which occur at a parameter value a 1 =1.7804 at which the chaotic attractor destroyed by boundary crisis with an unstable periodic orbit created by the saddle-node bifurcation. Multiple attractors with riddled basins and fractal boundaries are also observed. If ecological systems of interacting species do indeed exhibit multiple attractors etc., the long term dynamics of such systems may undergo vast qualitative changes following epidemics or environmental catastrophes due to the system being pushed into the basin of a new attractor by the perturbation. Coupled with stochasticity, such complex behaviours may render such systems practically unpredictable

An explanation for the multiplicative and the additive dose-effect relationship with the single-hit model

International Nuclear Information System (INIS)

Kottbauer, M.M.; Fleck, C.M.; Schoellnberger, H.

1997-01-01

For solid tumors and for leukemia the excess cancer rate after a single radiation dose D is different. The multiplicative model describes the excess solid tumor probability rate which is proportional to the background rate of cancer and dependent on dose D. The additive model describes the excess probability rate for leukaemia which is proportional to the dose D but unrelated to the spontaneous rate of cancer. A second great difference between the two models is the duration of the increased cancer probability rate. The multiplicative mode predicts that the additional cancer risk persist the whole lifetime after exposure and the additive model predicts excess risk over a period of time. With the Single-hit model (SHM) which is a multistage cancer model both dose-response relationships can be described. It will be shown that only small differences in the derivation will lead to the different relationships. We then analyze the incidence data of leukemia (1950-1987) and of all solid tumors (1958-1987) of the atomic bomb survivors. (author)

Model for CO2 leakage including multiple geological layers and multiple leaky wells.

Science.gov (United States)

Nordbotten, Jan M; Kavetski, Dmitri; Celia, Michael A; Bachu, Stefan

2009-02-01

Geological storage of carbon dioxide (CO2) is likely to be an integral component of any realistic plan to reduce anthropogenic greenhouse gas emissions. In conjunction with large-scale deployment of carbon storage as a technology, there is an urgent need for tools which provide reliable and quick assessments of aquifer storage performance. Previously, abandoned wells from over a century of oil and gas exploration and production have been identified as critical potential leakage paths. The practical importance of abandoned wells is emphasized by the correlation of heavy CO2 emitters (typically associated with industrialized areas) to oil and gas producing regions in North America. Herein, we describe a novel framework for predicting the leakage from large numbers of abandoned wells, forming leakage paths connecting multiple subsurface permeable formations. The framework is designed to exploit analytical solutions to various components of the problem and, ultimately, leads to a grid-free approximation to CO2 and brine leakage rates, as well as fluid distributions. We apply our model in a comparison to an established numerical solverforthe underlying governing equations. Thereafter, we demonstrate the capabilities of the model on typical field data taken from the vicinity of Edmonton, Alberta. This data set consists of over 500 wells and 7 permeable formations. Results show the flexibility and utility of the solution methods, and highlight the role that analytical and semianalytical solutions can play in this important problem.

By which name should I call thee? The consequences of having multiple names.

Science.gov (United States)

Stevenage, Sarah V; Lewis, Hugh G

2005-11-01

The nominal competitor effect suggests that, when a person has two names associated with them, recall of either name is more difficult than if they just had one name. Drawing on a connectionist framework, this effect could arise either if multiple names were represented as being connected to a single person identity node (PIN), or if multiple names were represented as being connected via one-to-one links to multiple PINs. Whilst the latter has intuitive appeal, results from two experiments support the former architecture. Having two names connected to a single PIN not only gives rise to a nominal competitor effect (Experiment 1), but also gives rise to a familiarity enhancement effect (Experiment 2). These empirical results are simulated using an extension of Brédart, Valentine, Calder, and Gassi's (1995) connectionist architecture, which reveals that both effects hold even when the association of both names to the PIN is unequal. These results are presented in terms of a more complete model for person recognition, and the representation of semantic information within such a model is examined.

Analysis of Brassica oleracea early stage abiotic stress responses reveals tolerance in multiple crop types and for multiple sources of stress.

Science.gov (United States)

Beacham, Andrew M; Hand, Paul; Pink, David Ac; Monaghan, James M

2017-12-01

Brassica oleracea includes a number of important crop types such as cabbage, cauliflower, broccoli and kale. Current climate conditions and weather patterns are causing significant losses in these crops, meaning that new cultivars with improved tolerance of one or more abiotic stress types must be sought. In this study, genetically fixed B. oleracea lines belonging to a Diversity Fixed Foundation Set (DFFS) were assayed for their response to seedling stage-imposed drought, flood, salinity, heat and cold stress. Significant (P ≤ 0.05) variation in stress tolerance response was found for each stress, for each of four measured variables (relative fresh weight, relative dry weight, relative leaf number and relative plant height). Lines tolerant to multiple stresses were found to belong to several different crop types. There was no overall correlation between the responses to the different stresses. Abiotic stress tolerance was identified in multiple B. oleracea crop types, with some lines exhibiting resistance to multiple stresses. For each stress, no one crop type appeared significantly more or less tolerant than others. The results are promising for the development of more environmentally robust lines of different B. oleracea crops by identifying tolerant material and highlighting the relationship between responses to different stresses. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

On an efficient multiple time step Monte Carlo simulation of the SABR model

NARCIS (Netherlands)

Leitao Rodriguez, A.; Grzelak, L.A.; Oosterlee, C.W.

2017-01-01

In this paper, we will present a multiple time step Monte Carlo simulation technique for pricing options under the Stochastic Alpha Beta Rho model. The proposed method is an extension of the one time step Monte Carlo method that we proposed in an accompanying paper Leitao et al. [Appl. Math.

Comprehension of Multiple Documents with Conflicting Information: A Two-Step Model of Validation

Science.gov (United States)

Richter, Tobias; Maier, Johanna

2017-01-01

In this article, we examine the cognitive processes that are involved when readers comprehend conflicting information in multiple texts. Starting from the notion of routine validation during comprehension, we argue that readers' prior beliefs may lead to a biased processing of conflicting information and a one-sided mental model of controversial…

Performance modeling and optimization of sparse matrix-vector multiplication on NVIDIA CUDA platform

NARCIS (Netherlands)

Xu, S.; Xue, W.; Lin, H.X.

2011-01-01

In this article, we discuss the performance modeling and optimization of Sparse Matrix-Vector Multiplication (SpMV) on NVIDIA GPUs using CUDA. SpMV has a very low computation-data ratio and its performance is mainly bound by the memory bandwidth. We propose optimization of SpMV based on ELLPACK from

Fuzzy linear model for production optimization of mining systems with multiple entities

Science.gov (United States)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Canonical correlation analysis of multiple sensory directed metabolomics data blocks reveals corresponding parts between data blocks.

NARCIS (Netherlands)

Doeswijk, T. G.; Hageman, J.A.; Westerhuis, J.A.; Tikunov, Y.; Bovy, A.; van Eeuwijk, F.A.

2011-01-01

Multiple analytical platforms are frequently used in metabolomics studies. The resulting multiple data blocks contain, in general, similar parts of information which can be disclosed by chemometric methods. The metabolites of interest, however, are usually just a minor part of the complete data

Gardner syndrome associated with multiple osteomas, intestinal polyposis, and epidermoid cysts

Energy Technology Data Exchange (ETDEWEB)

Koh, Kwang Joon; Park, Ha Na; Kim, Kyoung A [Dept. of Oral and Maxillofacial Radiology, School of Dentistry and Institute of Oral Bioscience, Chonbuk National University, Jeonju (Korea, Republic of)

2016-12-15

Gardner syndrome is known as a variant of familial adenomatous polyposis. This syndrome is characterized by multiple intestinal polyposes, osteomas, and epidermoid cysts. In addition, dental abnormalities include an increased frequency of multiple odontomas, as well as supernumerary and impacted teeth. The authors report the case of a 7-year-old male patient with Gardner syndrome. Radiographic findings revealed multiple osteomas in both sides of the maxilla, multiple diffuse enostoses in both jaws, and a complex odontoma in the left mandibular body. Two years later, multiple epidermoid cysts on the scalp were found. Since this patient was suspected to have Gardner syndrome, the authors recommended gastrointestinal endoscopy to check for intestinal polyposis. Gastrointestinal endoscopic examination revealed multiple polyposes in the upper gastrointestinal tract and fundus of the stomach. As a result, the final diagnosis was Gardner syndrome.

A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering

Energy Technology Data Exchange (ETDEWEB)

Cui, Xiaohui [ORNL; Potok, Thomas E [ORNL

2006-01-01

The Flocking model, first proposed by Craig Reynolds, is one of the first bio-inspired computational collective behavior models that has many popular applications, such as animation. Our early research has resulted in a flock clustering algorithm that can achieve better performance than the Kmeans or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a given set of data through the embedding of the highdimensional data items on a two-dimensional grid for efficient clustering result retrieval and visualization. In this paper, we propose a bio-inspired clustering model, the Multiple Species Flocking clustering model (MSF), and present a distributed multi-agent MSF approach for document clustering.

A multi-fuel management model for a community-level district heating system under multiple uncertainties

International Nuclear Information System (INIS)

Fu, D.Z.; Zheng, Z.Y.; Shi, H.B.; Xiao, Rui; Huang, G.H.; Li, Y.P.

2017-01-01

In this study, an interval two-stage double-stochastic single-sided fuzzy chance-constrained programming model is developed for supporting fuel management of a community-level district heating system (DHS) fed with both traditional fossil fuels and renewable biofuels under multiple uncertainties. The proposed model is based on the integration of interval parameter programming and single-sided fuzzy chance-constrained programming within an improved stochastic programming framework to tackle the uncertainties expressed as crisp intervals, fuzzy relationship, and probability distributions. Through transforming and solving the model, the related fuzzy and stochastic information can be effectively reflected in the generated solutions. A real fuel management case of a DHS located in Junpu New District of Dalian is utilized to demonstrate the model applicability. The obtained solutions provides an effective linkage in terms of both ‘‘quality’’ and ‘‘quantity’’ aspects for fuel management under various scenarios associated with multiple factors, and thus can help the decision makers to identify desired fuel allotment patterns. Moreover, this study is also useful for decision makers to address the other challenges (e.g. the imbalance between fuel supply and demand, the contradiction between air-pollution emission and environmental protection, as well as the tradeoff between the total heating cost and system satisfaction degree) generated in the fuel management processes. - Highlights: • A feasible two-stage stochastic programming method is improved. • A multi-fuel management model is developed under multiple uncertainties. • The fuel supply pattern for a district heating system can be obtained. • The variation tendencies of the pollutant emissions are examined. • Tradeoff analyses between system satisfaction degree and cost are carried out.

Aviation Safety Risk Modeling: Lessons Learned From Multiple Knowledge Elicitation Sessions

Science.gov (United States)

Luxhoj, J. T.; Ancel, E.; Green, L. L.; Shih, A. T.; Jones, S. M.; Reveley, M. S.

2014-01-01

Aviation safety risk modeling has elements of both art and science. In a complex domain, such as the National Airspace System (NAS), it is essential that knowledge elicitation (KE) sessions with domain experts be performed to facilitate the making of plausible inferences about the possible impacts of future technologies and procedures. This study discusses lessons learned throughout the multiple KE sessions held with domain experts to construct probabilistic safety risk models for a Loss of Control Accident Framework (LOCAF), FLightdeck Automation Problems (FLAP), and Runway Incursion (RI) mishap scenarios. The intent of these safety risk models is to support a portfolio analysis of NASA's Aviation Safety Program (AvSP). These models use the flexible, probabilistic approach of Bayesian Belief Networks (BBNs) and influence diagrams to model the complex interactions of aviation system risk factors. Each KE session had a different set of experts with diverse expertise, such as pilot, air traffic controller, certification, and/or human factors knowledge that was elicited to construct a composite, systems-level risk model. There were numerous "lessons learned" from these KE sessions that deal with behavioral aggregation, conditional probability modeling, object-oriented construction, interpretation of the safety risk results, and model verification/validation that are presented in this paper.

Cyclic AMP induces apoptosis in multiple myeloma cells and inhibits tumor development in a mouse myeloma model

International Nuclear Information System (INIS)

Follin-Arbelet, Virginie; Hofgaard, Peter O; Hauglin, Harald; Naderi, Soheil; Sundan, Anders; Blomhoff, Rune; Bogen, Bjarne; Blomhoff, Heidi K

2011-01-01

Multiple myeloma is an incurable disease requiring the development of effective therapies which can be used clinically. We have elucidated the potential for manipulating the cAMP signaling pathway as a target for inhibiting the growth of multiple myeloma cells. As a model system, we primarily used the murine multiple myeloma cell line MOPC315 which can be grown both in vivo and in vitro. Human multiple myeloma cell lines U266, INA-6 and the B-cell precursor acute lymphoblastic leukemia cell line Reh were used only for in vitro studies. Cell death was assessed by flow cytometry and western blot analysis after treatment with cAMP elevating agents (forskolin, prostaglandin E2 and rolipram) and cAMP analogs. We followed tumor growth in vivo after forskolin treatment by imaging DsRed-labelled MOPC315 cells transplanted subcutaneously in BALB/c nude mice. In contrast to the effect on Reh cells, 50 μM forskolin more than tripled the death of MOPC315 cells after 24 h in vitro. Forskolin induced cell death to a similar extent in the human myeloma cell lines U266 and INA-6. cAMP-mediated cell death had all the typical hallmarks of apoptosis, including changes in the mitochondrial membrane potential and cleavage of caspase 3, caspase 9 and PARP. Forskolin also inhibited the growth of multiple myeloma cells in a mouse model in vivo. Elevation of intracellular levels of cAMP kills multiple myeloma cells in vitro and inhibits development of multiple myeloma in vivo. This strongly suggests that compounds activating the cAMP signaling pathway may be useful in the field of multiple myeloma

Multiplicity distributions in the dual parton model

International Nuclear Information System (INIS)

Batunin, A.V.; Tolstenkov, A.N.

1985-01-01

Multiplicity distributions are calculated by means of a new mechanism of production of hadrons in a string, which was proposed previously by the authors and takes into account explicitly the valence character of the ends of the string. It is shown that allowance for this greatly improves the description of the low-energy multiplicity distributions. At superhigh energies, the contribution of the ends of the strings becomes negligibly small, but in this case multi-Pomeron contributions must be taken into account

Density dependence governs when population responses to multiple stressors are magnified or mitigated.

Science.gov (United States)

Hodgson, Emma E; Essington, Timothy E; Halpern, Benjamin S

2017-10-01

Population endangerment typically arises from multiple, potentially interacting anthropogenic stressors. Extensive research has investigated the consequences of multiple stressors on organisms, frequently focusing on individual life stages. Less is known about population-level consequences of exposure to multiple stressors, especially when exposure varies through life. We provide the first theoretical basis for identifying species at risk of magnified effects from multiple stressors across life history. By applying a population modeling framework, we reveal conditions under which population responses from stressors applied to distinct life stages are either magnified (synergistic) or mitigated. We find that magnification or mitigation critically depends on the shape of density dependence, but not the life stage in which it occurs. Stressors are always magnified when density dependence is linear or concave, and magnified or mitigated when it is convex. Using Bayesian numerical methods, we estimated the shape of density dependence for eight species across diverse taxa, finding support for all three shapes. © 2017 by the Ecological Society of America.

Sensitivity Analysis of Multiple Informant Models When Data Are Not Missing at Random

Science.gov (United States)

Blozis, Shelley A.; Ge, Xiaojia; Xu, Shu; Natsuaki, Misaki N.; Shaw, Daniel S.; Neiderhiser, Jenae M.; Scaramella, Laura V.; Leve, Leslie D.; Reiss, David

2013-01-01

Missing data are common in studies that rely on multiple informant data to evaluate relationships among variables for distinguishable individuals clustered within groups. Estimation of structural equation models using raw data allows for incomplete data, and so all groups can be retained for analysis even if only 1 member of a group contributes…

Negative binomial models for abundance estimation of multiple closed populations

Science.gov (United States)

Boyce, Mark S.; MacKenzie, Darry I.; Manly, Bryan F.J.; Haroldson, Mark A.; Moody, David W.

2001-01-01

Counts of uniquely identified individuals in a population offer opportunities to estimate abundance. However, for various reasons such counts may be burdened by heterogeneity in the probability of being detected. Theoretical arguments and empirical evidence demonstrate that the negative binomial distribution (NBD) is a useful characterization for counts from biological populations with heterogeneity. We propose a method that focuses on estimating multiple populations by simultaneously using a suite of models derived from the NBD. We used this approach to estimate the number of female grizzly bears (Ursus arctos) with cubs-of-the-year in the Yellowstone ecosystem, for each year, 1986-1998. Akaike's Information Criteria (AIC) indicated that a negative binomial model with a constant level of heterogeneity across all years was best for characterizing the sighting frequencies of female grizzly bears. A lack-of-fit test indicated the model adequately described the collected data. Bootstrap techniques were used to estimate standard errors and 95% confidence intervals. We provide a Monte Carlo technique, which confirms that the Yellowstone ecosystem grizzly bear population increased during the period 1986-1998.

Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

NARCIS (Netherlands)

Eekhout, I.; Wiel, M.A. van de; Heymans, M.W.

2017-01-01

Background. Multiple imputation is a recommended method to handle missing data. For significance testing after multiple imputation, Rubin’s Rules (RR) are easily applied to pool parameter estimates. In a logistic regression model, to consider whether a categorical covariate with more than two levels

A multiple-field coupled resistive transition model for superconducting Nb3Sn

Directory of Open Access Journals (Sweden)

Lin Yang

2016-12-01

Full Text Available A study on the superconducting transition width as functions of the applied magnetic field and strain is performed in superconducting Nb3Sn. A quantitative, yet universal phenomenological resistivity model is proposed. The numerical simulation by the proposed model shows predicted resistive transition characteristics under variable magnetic fields and strain, which in good agreement with the experimental observations. Furthermore, a temperature-modulated magnetoresistance transition behavior in filamentary Nb3Sn conductors can also be well described by the given model. The multiple-field coupled resistive transition model is helpful for making objective determinations of the high-dimensional critical surface of Nb3Sn in the multi-parameter space, offering some preliminary information about the basic vortex-pinning mechanisms, and guiding the design of the quench protection system of Nb3Sn superconducting magnets.

On the thermoluminescent interactive multiple-trap system (IMTS) model: is it a simple model?

International Nuclear Information System (INIS)

Gil T, M. I.; Perez C, L.; Cruz Z, E.; Furetta, C.; Roman L, J.

2016-10-01

In the thermally stimulated luminescence phenomenon, named thermoluminescence (Tl), the electrons and holes generated by the radiation-matter interaction can be trapped by the metastable levels in the band gap of the solid. Following, the electron can be thermally releases into the conduction band and a radiatively recombination with hole close to the recombination center occurred and the glow curve is emitted. However, the complex mechanism of trapping and thermally releases occurred in the band gap of solid. Some models, such as; first, second and general-order kinetics, have been well established to explain the behaviour of the glow curves and their defects recombination mechanism. In this work, expressions for and Interactive Multiple-Trap System model (IMTS) was obtained assuming: a set of discrete electron traps (active traps At), another set of thermally disconnected trap (TDT) and a recombination center (Rc) too. A numerical analysis based on the Levenberg-Marquardt method in conjunction with an implicit Rosenbrock method was taken into account to simulate the glow curve. The numerical method was tested through synthetic Tl glow curves for a wide range of trap parameters. The activation energy and kinetics order were determined using values from the General Order Kinetics (GOK) model as entry data to IMTS model. This model was tested using the experimental glow curves obtained from Ce or Eu-doped MgF 2 (LiF) polycrystals samples. Results shown that the IMTS model can predict more accurately the behavior of the Tl glow curves that those obtained by the GOK modified by Rasheedy and by the Mixed Order Kinetics model. (Author)

A general framework for the evaluation of genetic association studies using multiple marginal models

DEFF Research Database (Denmark)

Kitsche, Andreas; Ritz, Christian; Hothorn, Ludwig A.

2016-01-01

OBJECTIVE: In this study, we present a simultaneous inference procedure as a unified analysis framework for genetic association studies. METHODS: The method is based on the formulation of multiple marginal models that reflect different modes of inheritance. The basic advantage of this methodology...

Clinical trials: odds ratios and multiple regression models--why and how to assess them

NARCIS (Netherlands)

Sobh, Mohamad; Cleophas, Ton J.; Hadj-Chaib, Amel; Zwinderman, Aeilko H.

2008-01-01

Odds ratios (ORs), unlike chi2 tests, provide direct insight into the strength of the relationship between treatment modalities and treatment effects. Multiple regression models can reduce the data spread due to certain patient characteristics and thus improve the precision of the treatment

Natural killer cell lines preferentially kill clonogenic multiple myeloma cells and decrease myeloma engraftment in a bioluminescent xenograft mouse model.

Science.gov (United States)

Swift, Brenna E; Williams, Brent A; Kosaka, Yoko; Wang, Xing-Hua; Medin, Jeffrey A; Viswanathan, Sowmya; Martinez-Lopez, Joaquin; Keating, Armand

2012-07-01

Novel therapies capable of targeting drug resistant clonogenic MM cells are required for more effective treatment of multiple myeloma. This study investigates the cytotoxicity of natural killer cell lines against bulk and clonogenic multiple myeloma and evaluates the tumor burden after NK cell therapy in a bioluminescent xenograft mouse model. The cytotoxicity of natural killer cell lines was evaluated against bulk multiple myeloma cell lines using chromium release and flow cytometry cytotoxicity assays. Selected activating receptors on natural killer cells were blocked to determine their role in multiple myeloma recognition. Growth inhibition of clonogenic multiple myeloma cells was assessed in a methylcellulose clonogenic assay in combination with secondary replating to evaluate the self-renewal of residual progenitors after natural killer cell treatment. A bioluminescent mouse model was developed using the human U266 cell line transduced to express green fluorescent protein and luciferase (U266eGFPluc) to monitor disease progression in vivo and assess bone marrow engraftment after intravenous NK-92 cell therapy. Three multiple myeloma cell lines were sensitive to NK-92 and KHYG-1 cytotoxicity mediated by NKp30, NKp46, NKG2D and DNAM-1 activating receptors. NK-92 and KHYG-1 demonstrated 2- to 3-fold greater inhibition of clonogenic multiple myeloma growth, compared with killing of the bulk tumor population. In addition, the residual colonies after treatment formed significantly fewer colonies compared to the control in a secondary replating for a cumulative clonogenic inhibition of 89-99% at the 20:1 effector to target ratio. Multiple myeloma tumor burden was reduced by NK-92 in a xenograft mouse model as measured by bioluminescence imaging and reduction in bone marrow engraftment of U266eGFPluc cells by flow cytometry. This study demonstrates that NK-92 and KHYG-1 are capable of killing clonogenic and bulk multiple myeloma cells. In addition, multiple myeloma

Detection of Extramedullary Multiple Myeloma in Liver by FDG-PET/CT

International Nuclear Information System (INIS)

Kim, Daeweung; Kim, Woo Hyoung; Kim, Myoung Hyoun; Choi, Keum Ha; Kim, Chang Guhn

2014-01-01

We present the case of a 42-year-old man with a painful mass lesion in the right shoulder that was detected by contrast-enhanced computed tomography (CT) and 18 F-fluoro-2-deoxyglucose ( 18 F-FDG) positron emission tomography (PET)/CT. Excisional biopsy revealed infiltration of plasma cells with anaplastic features, consistent with solitary plasmacytoma (PC). Serum analysis showed elevation of serum free lambda light chain levels (27.78 mg/l), with an abnormally high kappa:lambda ratio (2.33) and high total proteins (10.4 g/dl). Serum protein electrophoresis revealed an M spike in the gamma-globulin region (56.1 %=5.8 g/dl). Subsequently, 18 F-FDG PET/CT revealed another hypermetabolic mass in the right lobe of the liver. CT-guided biopsy of the liver lesion revealed plasma cell myeloma, consistent with multiple myeloma. Multiple myeloma presenting as nodular liver masses is very rare in clinical practice. In a retrospective review of more than 2,000 patients, Talamo et al. reported only nine cases where there was nodular involvement of the liver by multiple myeloma. The organ most commonly involved was the liver, followed by pancreas, stomach, peritoneum with malignant ascites, colon, rectum, duodenum and ileum. Therefore, the literature published thus far has been limited to a few reports and case series. Among these reports, some had demonstrated the PET or PET/CT findings of nodular liver involvement of multiple myeloma. About 10 % of the solitary myelomas appeared as extramedullary PC or solitary PC of bone. In spite of the advances in therapy, the treatment of multiple myeloma is still palliative. However, solitary PC could be cured by resection or radiation therapy. Thus, differentiation between PC and multiple myeloma is essential in making a decision for the appropriate therapeutic regimen. 18 F-FDG PET/CT has the unique ability to detect and characterize malignant lesions in one single examination. Schirrmeister et al. reported that 18 F-FDG PET revealed

Unified thalamic model generates multiple distinct oscillations with state-dependent entrainment by stimulation.

Directory of Open Access Journals (Sweden)

Guoshi Li

2017-10-01

Full Text Available The thalamus plays a critical role in the genesis of thalamocortical oscillations, yet the underlying mechanisms remain elusive. To understand whether the isolated thalamus can generate multiple distinct oscillations, we developed a biophysical thalamic model to test the hypothesis that generation of and transition between distinct thalamic oscillations can be explained as a function of neuromodulation by acetylcholine (ACh and norepinephrine (NE and afferent synaptic excitation. Indeed, the model exhibited four distinct thalamic rhythms (delta, sleep spindle, alpha and gamma oscillations that span the physiological states corresponding to different arousal levels from deep sleep to focused attention. Our simulation results indicate that generation of these distinct thalamic oscillations is a result of both intrinsic oscillatory cellular properties and specific network connectivity patterns. We then systematically varied the ACh/NE and input levels to generate a complete map of the different oscillatory states and their transitions. Lastly, we applied periodic stimulation to the thalamic network and found that entrainment of thalamic oscillations is highly state-dependent. Our results support the hypothesis that ACh/NE modulation and afferent excitation define thalamic oscillatory states and their response to brain stimulation. Our model proposes a broader and more central role of the thalamus in the genesis of multiple distinct thalamo-cortical rhythms than previously assumed.

Towards an Iterated Game Model with Multiple Adversaries in Smart-World Systems †

Science.gov (United States)

Yang, Xinyu; Yu, Wei; Lin, Jie; Yang, Qingyu

2018-01-01

Diverse and varied cyber-attacks challenge the operation of the smart-world system that is supported by Internet-of-Things (IoT) (smart cities, smart grid, smart transportation, etc.) and must be carefully and thoughtfully addressed before widespread adoption of the smart-world system can be fully realized. Although a number of research efforts have been devoted to defending against these threats, a majority of existing schemes focus on the development of a specific defensive strategy to deal with specific, often singular threats. In this paper, we address the issue of coalitional attacks, which can be launched by multiple adversaries cooperatively against the smart-world system such as smart cities. Particularly, we propose a game-theory based model to capture the interaction among multiple adversaries, and quantify the capacity of the defender based on the extended Iterated Public Goods Game (IPGG) model. In the formalized game model, in each round of the attack, a participant can either cooperate by participating in the coalitional attack, or defect by standing aside. In our work, we consider the generic defensive strategy that has a probability to detect the coalitional attack. When the coalitional attack is detected, all participating adversaries are penalized. The expected payoff of each participant is derived through the equalizer strategy that provides participants with competitive benefits. The multiple adversaries with the collusive strategy are also considered. Via a combination of theoretical analysis and experimentation, our results show that no matter which strategies the adversaries choose (random strategy, win-stay-lose-shift strategy, or even the adaptive equalizer strategy), our formalized game model is capable of enabling the defender to greatly reduce the maximum value of the expected average payoff to the adversaries via provisioning sufficient defensive resources, which is reflected by setting a proper penalty factor against the adversaries

Multiple Model-Based Synchronization Approaches for Time Delayed Slaving Data in a Space Launch Vehicle Tracking System

Directory of Open Access Journals (Sweden)

Haryong Song

2016-01-01

Full Text Available Due to the inherent characteristics of the flight mission of a space launch vehicle (SLV, which is required to fly over very large distances and have very high fault tolerances, in general, SLV tracking systems (TSs comprise multiple heterogeneous sensors such as radars, GPS, INS, and electrooptical targeting systems installed over widespread areas. To track an SLV without interruption and to hand over the measurement coverage between TSs properly, the mission control system (MCS transfers slaving data to each TS through mission networks. When serious network delays occur, however, the slaving data from the MCS can lead to the failure of the TS. To address this problem, in this paper, we propose multiple model-based synchronization (MMS approaches, which take advantage of the multiple motion models of an SLV. Cubic spline extrapolation, prediction through an α-β-γ filter, and a single model Kalman filter are presented as benchmark approaches. We demonstrate the synchronization accuracy and effectiveness of the proposed MMS approaches using the Monte Carlo simulation with the nominal trajectory data of Korea Space Launch Vehicle-I.

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

Science.gov (United States)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Interesting images: Multiple coronary artery aneurysms.

Science.gov (United States)

Howard, Jonathon M; Viswanath, Omar; Armas, Alfredo; Santana, Orlando; Rosen, Gerald P

2017-01-01

We present the case of a 65-year-old male who presented with stable angina and dyspnea on exertion. His initial workup yielded a positive treadmill stress test for reversible apical ischemia, and transthoracic echocardiogram demonstrated impaired systolic function. Cardiac catheterization was then performed, revealing severe atherosclerotic disease including multiple coronary artery aneurysms. As a result, the patient was advised to and subsequently underwent a coronary artery bypass graft. This case highlights the presence of multiple coronary artery aneurysms and the ability to appreciate these pathologic findings on multiple imaging modalities, including coronary angiogram, transesophageal echocardiography, and direct visualization through the surgical field.

Noise-induced coherence in bistable systems with multiple time delays

International Nuclear Information System (INIS)

Jiang Yu; Dong, Shi-Hai; Lozada-Cassou, M.

2004-01-01

We study the correlation properties of noise-driven bistable systems with multiple time-delay feedbacks. For small noisy perturbation and feedback magnitude, we derive the autocorrelation function and the power spectrum based on the two-state model with transition rates depending on the earlier states of the system. A comparison between the single and double time delays reveals that the auto correlation functions exhibit exponential decay with small undulation for the double time delays, in contrast with the remarkable oscillatory behavior at small time lags for the single time delay

Treatment of a multiple sclerosis animal model by a novel nanodrop formulation of a natural antioxidant.

Science.gov (United States)

Binyamin, Orli; Larush, Liraz; Frid, Kati; Keller, Guy; Friedman-Levi, Yael; Ovadia, Haim; Abramsky, Oded; Magdassi, Shlomo; Gabizon, Ruth

2015-01-01

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system and is associated with demyelination, neurodegeneration, and sensitivity to oxidative stress. In this work, we administered a nanodroplet formulation of pomegranate seed oil (PSO), denominated Nano-PSO, to mice induced for experimental autoimmune encephalomyelitis (EAE), an established model of MS. PSO comprises high levels of punicic acid, a unique polyunsaturated fatty acid considered as one of the strongest natural antioxidants. We show here that while EAE-induced mice treated with natural PSO presented some reduction in disease burden, this beneficial effect increased significantly when EAE mice were treated with Nano-PSO of specific size nanodroplets at much lower concentrations of the oil. Pathological examinations revealed that Nano-PSO administration dramatically reduced demyelination and oxidation of lipids in the brains of the affected animals, which are hallmarks of this severe neurological disease. We propose that novel formulations of natural antioxidants such as Nano-PSO may be considered for the treatment of patients suffering from demyelinating diseases. On the mechanistic side, our results demonstrate that lipid oxidation may be a seminal feature in both demyelination and neurodegeneration.

Bayesian models and meta analysis for multiple tissue gene expression data following corticosteroid administration

Directory of Open Access Journals (Sweden)

Kelemen Arpad

2008-08-01

Full Text Available Abstract Background This paper addresses key biological problems and statistical issues in the analysis of large gene expression data sets that describe systemic temporal response cascades to therapeutic doses in multiple tissues such as liver, skeletal muscle, and kidney from the same animals. Affymetrix time course gene expression data U34A are obtained from three different tissues including kidney, liver and muscle. Our goal is not only to find the concordance of gene in different tissues, identify the common differentially expressed genes over time and also examine the reproducibility of the findings by integrating the results through meta analysis from multiple tissues in order to gain a significant increase in the power of detecting differentially expressed genes over time and to find the differential differences of three tissues responding to the drug. Results and conclusion Bayesian categorical model for estimating the proportion of the 'call' are used for pre-screening genes. Hierarchical Bayesian Mixture Model is further developed for the identifications of differentially expressed genes across time and dynamic clusters. Deviance information criterion is applied to determine the number of components for model comparisons and selections. Bayesian mixture model produces the gene-specific posterior probability of differential/non-differential expression and the 95% credible interval, which is the basis for our further Bayesian meta-inference. Meta-analysis is performed in order to identify commonly expressed genes from multiple tissues that may serve as ideal targets for novel treatment strategies and to integrate the results across separate studies. We have found the common expressed genes in the three tissues. However, the up/down/no regulations of these common genes are different at different time points. Moreover, the most differentially expressed genes were found in the liver, then in kidney, and then in muscle.

Human mast cell tryptase: Multiple cDNAs and genes reveal a multigene serine protease family

International Nuclear Information System (INIS)

Vanderslice, P.; Ballinger, S.M.; Tam, E.K.; Goldstein, S.M.; Craik, C.S.; Caughey, G.H.

1990-01-01

Three different cDNAs and a gene encoding human skin mast cell tryptase have been cloned and sequenced in their entirety. The deduced amino acid sequences reveal a 30-amino acid prepropeptide followed by a 245-amino acid catalytic domain. The C-terminal undecapeptide of the human preprosequence is identical in dog tryptase and appears to be part of a prosequence unique among serine proteases. The differences among the three human tryptase catalytic domains include the loss of a consensus N-glycosylation site in one cDNA, which may explain some of the heterogeneity in size and susceptibility to deglycosylation seen in tryptase preparations. All three tryptase cDNAs are distinct from a recently reported cDNA obtained from a human lung mast cell library. A skin tryptase cDNA was used to isolate a human tryptase gene, the exons of which match one of the skin-derived cDNAs. The organization of the ∼1.8-kilobase-pair tryptase gene is unique and is not closely related to that of any other mast cell or leukocyte serine protease. The 5' regulatory regions of the gene share features with those of other serine proteases, including mast cell chymase, but are unusual in being separated from the protein-coding sequence by an intron. High-stringency hybridization of a human genomic DNA blot with a fragment of the tryptase gene confirms the presence of multiple tryptase genes. These findings provide genetic evidence that human mast cell tryptases are the products of a multigene family

Multiple Realizability and Biological Laws

NARCIS (Netherlands)

Raerinne, Jani P.; Eronen, Markus I.

2012-01-01

We critically analyze Alexander Rosenberg's argument based on the multiple realizability of biological properties that there are no biological laws. The argument is intuitive and suggestive. Nevertheless, a closer analysis reveals that the argument rests on dubious assumptions about the nature of

Multiple periodic solutions for a discrete time model of plankton allelopathy

OpenAIRE

Zhang Jianbao; Fang Hui

2006-01-01

We study a discrete time model of the growth of two species of plankton with competitive and allelopathic effects on each other N1(k+1) = N1(k)exp{r1(k)-a11(k)N1(k)-a12(k)N2(k)-b1(k)N1(k)N2(k)}, N2(k+1) = N2(k)exp{r2(k)-a21(k)N2(k)-b2(k)N1(k)N1(k)N2(k)}. A set of sufficient conditions is obtained for the existence of multiple positive periodic solutions for this model. The approach is based on Mawhin's continuation theorem of coincidence degree theory as well as some a priori estimates. Some...

Probability distributions in conservative energy exchange models of multiple interacting agents

International Nuclear Information System (INIS)

Scafetta, Nicola; West, Bruce J

2007-01-01

Herein we study energy exchange models of multiple interacting agents that conserve energy in each interaction. The models differ regarding the rules that regulate the energy exchange and boundary effects. We find a variety of stochastic behaviours that manifest energy equilibrium probability distributions of different types and interaction rules that yield not only the exponential distributions such as the familiar Maxwell-Boltzmann-Gibbs distribution of an elastically colliding ideal particle gas, but also uniform distributions, truncated exponential distributions, Gaussian distributions, Gamma distributions, inverse power law distributions, mixed exponential and inverse power law distributions, and evolving distributions. This wide variety of distributions should be of value in determining the underlying mechanisms generating the statistical properties of complex phenomena including those to be found in complex chemical reactions

Ship Detection Based on Multiple Features in Random Forest Model for Hyperspectral Images

Science.gov (United States)

Li, N.; Ding, L.; Zhao, H.; Shi, J.; Wang, D.; Gong, X.

2018-04-01

A novel method for detecting ships which aim to make full use of both the spatial and spectral information from hyperspectral images is proposed. Firstly, the band which is high signal-noise ratio in the range of near infrared or short-wave infrared spectrum, is used to segment land and sea on Otsu threshold segmentation method. Secondly, multiple features that include spectral and texture features are extracted from hyperspectral images. Principal components analysis (PCA) is used to extract spectral features, the Grey Level Co-occurrence Matrix (GLCM) is used to extract texture features. Finally, Random Forest (RF) model is introduced to detect ships based on the extracted features. To illustrate the effectiveness of the method, we carry out experiments over the EO-1 data by comparing single feature and different multiple features. Compared with the traditional single feature method and Support Vector Machine (SVM) model, the proposed method can stably achieve the target detection of ships under complex background and can effectively improve the detection accuracy of ships.

Multiple cracks initiation and propagation behavior of stainless steel in high temperature water environment

International Nuclear Information System (INIS)

Kamaya, Masayuki; Chiba, Goro; Nakajima, Nobuo; Totsuka, Nobuo

2001-01-01

Environmentally assisted crack initiation behavior is greatly affected by applied stress and environmental factors, such as water temperature, contained impurities and so on. On the other hand, crack initiation behavior also influences crack propagation. A typical example of this influence can be observed as the interference effects of multiple cracks, such as the coalescence of approaching crack tips or the arrest phenomena in the relaxation zone of an adjacent crack. To understand these effects of crack initiation on crack propagation behavior is very important to predict the lifetime of components, in which quite a few cracks tend to occur. This study aimed at revealing the crack initiation behavior and the influence of this behavior on propagation. At first, to evaluate the effect of applied stress on crack initiation behavior, sensitized stainless steel was subjected to a four-point bending test in a high temperature water environment at the constant potentials of ECP +50 mV and ECP +150 mV. Secondly, a crack initiation and growth simulation model was developed, in which the interference effect of multiple cracks is evaluated by the finite element method, based on the experimental results. Using this model, the relationship between crack initiation and propagation was studied. From the model, it was revealed that the increasing number of the cracks accelerates crack propagation and reduces life. (author)

An economic production model for time dependent demand with rework and multiple production setups

Directory of Open Access Journals (Sweden)

S.R. Singh

2014-04-01

Full Text Available In this paper, we present a model for time dependent demand with multiple productions and rework setups. Production is demand dependent and greater than the demand rate. Production facility produces items in m production setups and one rework setup (m, 1 policy. The major reason of reverse logistic and green supply chain is rework, so it reduces the cost of production and other ecological problems. Most of the researchers developed a rework model without deteriorating items. A numerical example and sensitivity analysis is shown to describe the model.

Adapting and applying a multiple domain model of condom use to Chinese college students.

Science.gov (United States)

Xiao, Zhiwen; Palmgreen, Philip; Zimmerman, Rick; Noar, Seth

2010-03-01

This study adapts a multiple domain model (MDM) to explain condom use among a sample of sexually active Chinese college students. A cross-sectional survey was conducted and structural equation modeling was used to test the proposed model. Preparatory behaviors, theory of reasoned action (TRA)/theory of planned behavior variables, impulsivity, length of relationship, and alcohol use were significant direct predictors of condom use. The results suggest that MDM can provide a better understanding of heterosexual condom use among Chinese youth, and help in the design of HIV-preventive and safer sex interventions in China.

Estimation of Causal Mediation Effects for a Dichotomous Outcome in Multiple-Mediator Models using the Mediation Formula

OpenAIRE

Wang, Wei; Nelson, Suchitra; Albert, Jeffrey M.

2013-01-01

Mediators are intermediate variables in the causal pathway between an exposure and an outcome. Mediation analysis investigates the extent to which exposure effects occur through these variables, thus revealing causal mechanisms. In this paper, we consider the estimation of the mediation effect when the outcome is binary and multiple mediators of different types exist. We give a precise definition of the total mediation effect as well as decomposed mediation effects through individual or sets ...

Global and 3D Spatial Assessment of Neuroinflammation in Rodent Models of Multiple Sclerosis

DEFF Research Database (Denmark)

Gupta, Shashank; Utoft, Regine Egeholm; Hasseldam, Henrik

2013-01-01

Multiple Sclerosis (MS) is a progressive autoimmune inflammatory and demyelinating disease of the central nervous system (CNS). T cells play a key role in the progression of neuroinflammation in MS and also in the experimental autoimmune encephalomyelitis (EAE) animal models for the disease. A te...

Use of multiple-trait animal models for genetic evaluation of milk, fat and protein lactation yields of dairy cattle in Belgium

Directory of Open Access Journals (Sweden)

Pierre Coenraets

1997-01-01

Full Text Available Comparison of computation time between single-trait and multiple-trait evaluations showed that with the use of the canonicat transformation associated with multiple diagonalization of (covariance matrices, multiple-trait analysis for milk, fat and protein yields is not more expensive than three single-trait analyzes. Rank correlations between breeding values for 54,820 cows with records (for their 1,406 sires estimated with the single-trait and multiple-trait models were over .98 (.99 in fat yield and over .99 (.99 in milk and protein yields. The relative gain expressed as reduction in mean prediction error variance was 3% (1% in milk yield, 6% (3% in fat yield, and .4% (.2% in protein yield for cows (for sires. Relative genetic gains were 3% (1%, 6% (2% and .5% (.2% respectively in milk, fat and protein yields for cows (for sires. The use of multiple-trait models bas therefore the advantages of improved precision and reduced selection bics. Multiple-trait analysis could be extended for the analyzes of test-day records. Results show that this or similar multiple-trait animal model could be implemented immediately in Belgium at low computing cost, using the proposed algorithme and could be the first step to new, more advanced evaluation methods.

Group Targets Tracking Using Multiple Models GGIW-CPHD Based on Best-Fitting Gaussian Approximation and Strong Tracking Filter

Directory of Open Access Journals (Sweden)

Yun Wang

2016-01-01

Full Text Available Gamma Gaussian inverse Wishart cardinalized probability hypothesis density (GGIW-CPHD algorithm was always used to track group targets in the presence of cluttered measurements and missing detections. A multiple models GGIW-CPHD algorithm based on best-fitting Gaussian approximation method (BFG and strong tracking filter (STF is proposed aiming at the defect that the tracking error of GGIW-CPHD algorithm will increase when the group targets are maneuvering. The best-fitting Gaussian approximation method is proposed to implement the fusion of multiple models using the strong tracking filter to correct the predicted covariance matrix of the GGIW component. The corresponding likelihood functions are deduced to update the probability of multiple tracking models. From the simulation results we can see that the proposed tracking algorithm MM-GGIW-CPHD can effectively deal with the combination/spawning of groups and the tracking error of group targets in the maneuvering stage is decreased.

Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model

DEFF Research Database (Denmark)

Silvennoinen, Annestiina; Terasvirta, Timo

A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations...

SignalSpider: Probabilistic pattern discovery on multiple normalized ChIP-Seq signal profiles

KAUST Repository

Wong, Kachun

2014-09-05

Motivation: Chromatin immunoprecipitation (ChIP) followed by high-throughput sequencing (ChIP-Seq) measures the genome-wide occupancy of transcription factors in vivo. Different combinations of DNA-binding protein occupancies may result in a gene being expressed in different tissues or at different developmental stages. To fully understand the functions of genes, it is essential to develop probabilistic models on multiple ChIP-Seq profiles to decipher the combinatorial regulatory mechanisms by multiple transcription factors. Results: In this work, we describe a probabilistic model (SignalSpider) to decipher the combinatorial binding events of multiple transcription factors. Comparing with similar existing methods, we found SignalSpider performs better in clustering promoter and enhancer regions. Notably, SignalSpider can learn higher-order combinatorial patterns from multiple ChIP-Seq profiles. We have applied SignalSpider on the normalized ChIP-Seq profiles from the ENCODE consortium and learned model instances. We observed different higher-order enrichment and depletion patterns across sets of proteins. Those clustering patterns are supported by Gene Ontology (GO) enrichment, evolutionary conservation and chromatin interaction enrichment, offering biological insights for further focused studies. We also proposed a specific enrichment map visualization method to reveal the genome-wide transcription factor combinatorial patterns from the models built, which extend our existing fine-scale knowledge on gene regulation to a genome-wide level. Availability and implementation: The matrix-algebra-optimized executables and source codes are available at the authors\\' websites: http://www.cs.toronto.edu/∼wkc/SignalSpider. Contact: Supplementary information: Supplementary data are available at Bioinformatics online.

Statistical Analysis of Coherent Ultrashort Light Pulse CDMA With Multiple Optical Amplifiers Using Additive Noise Model

Science.gov (United States)

Jamshidi, Kambiz; Salehi, Jawad A.

2005-05-01

This paper describes a study of the performance of various configurations for placing multiple optical amplifiers in a typical coherent ultrashort light pulse code-division multiple access (CULP-CDMA) communication system using the additive noise model. For this study, a comprehensive performance analysis was developed that takes into account multiple-access noise, noise due to optical amplifiers, and thermal noise using the saddle-point approximation technique. Prior to obtaining the overall system performance, the input/output statistical models for different elements of the system such as encoders/decoders,star coupler, and optical amplifiers were obtained. Performance comparisons between an ideal and lossless quantum-limited case and a typical CULP-CDMA with various losses exhibit more than 30 dB more power requirement to obtain the same bit-error rate (BER). Considering the saturation effect of optical amplifiers, this paper discusses an algorithm for amplifiers' gain setting in various stages of the network in order to overcome the nonlinear effects on signal modulation in optical amplifiers. Finally, using this algorithm,various configurations of multiple optical amplifiers in CULP-CDMA are discussed and the rules for the required optimum number of amplifiers are shown with their corresponding optimum locations to be implemented along the CULP-CDMA system.

Genome sequencing and analysis reveals possible determinants of Staphylococcus aureus nasal carriage

Directory of Open Access Journals (Sweden)

Cole Alexander M

2008-09-01

Full Text Available Abstract Background Nasal carriage of Staphylococcus aureus is a major risk factor in clinical and community settings due to the range of etiologies caused by the organism. We have identified unique immunological and ultrastructural properties associated with nasal carriage isolates denoting a role for bacterial factors in nasal carriage. However, despite extensive molecular level characterizations by several groups suggesting factors necessary for colonization on nasal epithelium, genetic determinants of nasal carriage are unknown. Herein, we have set a genomic foundation for unraveling the bacterial determinants of nasal carriage in S. aureus. Results MLST analysis revealed no lineage specific differences between carrier and non-carrier strains suggesting a role for mobile genetic elements. We completely sequenced a model carrier isolate (D30 and a model non-carrier strain (930918-3 to identify differential gene content. Comparison revealed the presence of 84 genes unique to the carrier strain and strongly suggests a role for Type VII secretion systems in nasal carriage. These genes, along with a putative pathogenicity island (SaPIBov present uniquely in the carrier strains are likely important in affecting carriage. Further, PCR-based genotyping of other clinical isolates for a specific subset of these 84 genes raise the possibility of nasal carriage being caused by multiple gene sets. Conclusion Our data suggest that carriage is likely a heterogeneic phenotypic trait and implies a role for nucleotide level polymorphism in carriage. Complete genome level analyses of multiple carriage strains of S. aureus will be important in clarifying molecular determinants of S. aureus nasal carriage.

Barcoding against a paradox? Combined molecular species delineations reveal multiple cryptic lineages in elusive meiofaunal sea slugs

Directory of Open Access Journals (Sweden)

Jörger Katharina M

2012-12-01

Full Text Available Abstract Background Many marine meiofaunal species are reported to have wide distributions, which creates a paradox considering their hypothesized low dispersal abilities. Correlated with this paradox is an especially high taxonomic deficit for meiofauna, partly related to a lower taxonomic effort and partly to a high number of putative cryptic species. Molecular-based species delineation and barcoding approaches have been advocated for meiofaunal biodiversity assessments to speed up description processes and uncover cryptic lineages. However, these approaches show sensitivity to sampling coverage (taxonomic and geographic and the success rate has never been explored on mesopsammic Mollusca. Results We collected the meiofaunal sea-slug Pontohedyle (Acochlidia, Heterobranchia from 28 localities worldwide. With a traditional morphological approach, all specimens fall into two morphospecies. However, with a multi-marker genetic approach, we reveal multiple lineages that are reciprocally monophyletic on single and concatenated gene trees in phylogenetic analyses. These lineages are largely concordant with geographical and oceanographic parameters, leading to our primary species hypothesis (PSH. In parallel, we apply four independent methods of molecular based species delineation: General Mixed Yule Coalescent model (GMYC, statistical parsimony, Bayesian Species Delineation (BPP and Automatic Barcode Gap Discovery (ABGD. The secondary species hypothesis (SSH is gained by relying only on uncontradicted results of the different approaches (‘minimum consensus approach’, resulting in the discovery of a radiation of (at least 12 mainly cryptic species, 9 of them new to science, some sympatric and some allopatric with respect to ocean boundaries. However, the meiofaunal paradox still persists in some Pontohedyle species identified here with wide coastal and trans-archipelago distributions. Conclusions Our study confirms extensive, morphologically

In vivo diagnosis of skin cancer using polarized and multiple scattered light spectroscopy

Science.gov (United States)

Bartlett, Matthew Allen

This thesis research presents the development of a non-invasive diagnostic technique for distinguishing between skin cancer, moles, and normal skin using polarized and multiple scattered light spectroscopy. Polarized light incident on the skin is single scattered by the epidermal layer and multiple scattered by the dermal layer. The epidermal light maintains its initial polarization while the light from the dermal layer becomes randomized and multiple scattered. Mie theory was used to model the epidermal light as the scattering from the intercellular organelles. The dermal signal was modeled as the diffusion of light through a localized semi-homogeneous volume. These models were confirmed using skin phantom experiments, studied with in vitro cell cultures, and applied to human skin for in vivo testing. A CCD-based spectroscopy system was developed to perform all these experiments. The probe and the theory were tested on skin phantoms of latex spheres on top of a solid phantom. We next extended our phantom study to include in vitro cells on top of the solid phantom. Optical fluorescent microscope images revealed at least four distinct scatterers including mitochondria, nucleoli, nuclei, and cell membranes. Single scattering measurements on the mammalian cells consistently produced PSD's in the size range of the mitochondria. The clinical portion of the study consisted of in vivo measurements on cancer, mole, and normal skin spots. The clinical study combined the single scattering model from the phantom and in vitro cell studies with the diffusion model for multiple scattered light. When parameters from both layers were combined, we found that a sensitivity of 100% and 77% can be obtained for detecting cancers and moles, respectively, given the number of lesions examined.

The blackboard model - A framework for integrating multiple cooperating expert systems

Science.gov (United States)

Erickson, W. K.

1985-01-01

The use of an artificial intelligence (AI) architecture known as the blackboard model is examined as a framework for designing and building distributed systems requiring the integration of multiple cooperating expert systems (MCXS). Aerospace vehicles provide many examples of potential systems, ranging from commercial and military aircraft to spacecraft such as satellites, the Space Shuttle, and the Space Station. One such system, free-flying, spaceborne telerobots to be used in construction, servicing, inspection, and repair tasks around NASA's Space Station, is examined. The major difficulties found in designing and integrating the individual expert system components necessary to implement such a robot are outlined. The blackboard model, a general expert system architecture which seems to address many of the problems found in designing and building such a system, is discussed. A progress report on a prototype system under development called DBB (Distributed BlackBoard model) is given. The prototype will act as a testbed for investigating the feasibility, utility, and efficiency of MCXS-based designs developed under the blackboard model.