The Abelian Sandpile Model on a Random Binary Tree
Redig, F.; Ruszel, W.M.; Saada, E.
2012-01-01
We study the abelian sandpile model on a random binary tree. Using a transfer matrix approach introduced by Dhar and Majumdar, we prove exponential decay of correlations, and in a small supercritical region (i.e., where the branching process survives with positive probability) exponential decay of
DEFF Research Database (Denmark)
Brodal, Gerth Stølting; Moruz, Gabriel
2006-01-01
It is well-known that to minimize the number of comparisons a binary search tree should be perfectly balanced. Previous work has shown that a dominating factor over the running time for a search is the number of cache faults performed, and that an appropriate memory layout of a binary search tree...... can reduce the number of cache faults by several hundred percent. Motivated by the fact that during a search branching to the left or right at a node does not necessarily have the same cost, e.g. because of branch prediction schemes, we in this paper study the class of skewed binary search trees....... For all nodes in a skewed binary search tree the ratio between the size of the left subtree and the size of the tree is a fixed constant (a ratio of 1/2 gives perfect balanced trees). In this paper we present an experimental study of various memory layouts of static skewed binary search trees, where each...
Multiobjective Optimization for the Forecasting Models on the Base of the Strictly Binary Trees
Nadezhda Astakhova; Liliya Demidova; Evgeny Nikulchev
2016-01-01
The optimization problem dealing with the development of the forecasting models on the base of strictly binary trees has been considered. The aim of paper is the comparative analysis of two optimization variants which are applied for the development of the forecasting models. Herewith the first optimization variant assumes the application of one quality indicator of the forecasting model named as the affinity indicator and the second variant realizes the application of two quality indicators ...
Binary trees equipped with semivaluations | Pajoohesh ...
African Journals Online (AJOL)
Our interest in this lattice stems from its application to binary decision trees. Binary decision trees form a crucial tool for algorithmic time analysis. The lattice properties of Tn are studied and we show that every Tn has a sublattice isomorphic to Tn-1 and prove that Tn is generated by Tn-1. Also we show that the distance from ...
Topological and categorical properties of binary trees
Directory of Open Access Journals (Sweden)
H. Pajoohesh
2008-04-01
Full Text Available Binary trees are very useful tools in computer science for estimating the running time of so-called comparison based algorithms, algorithms in which every action is ultimately based on a prior comparison between two elements. For two given algorithms A and B where the decision tree of A is more balanced than that of B, it is known that the average and worst case times of A will be better than those of B, i.e., ₸A(n ≤₸B(n and TWA (n≤TWB (n. Thus the most balanced and the most imbalanced binary trees play a main role. Here we consider them as semilattices and characterize the most balanced and the most imbalanced binary trees by topological and categorical properties. Also we define the composition of binary trees as a commutative binary operation, *, such that for binary trees A and B, A * B is the binary tree obtained by attaching a copy of B to any leaf of A. We show that (T,* is a commutative po-monoid and investigate its properties.
A coinductive calculus of binary trees
A.M. Silva (Alexandra); J.J.M.M. Rutten (Jan)
2007-01-01
htmlabstractWe study the set T_A of infinite binary trees with nodes labelled in a semiring A from a coalgebraic perspective. We present coinductive definition and proof principles based on the fact that T_A carries a final coalgebra structure. By viewing trees as formal power series, we develop a
Tree asymmetry--a sensitive and practical measure for binary topological trees.
Van Pelt, J; Uylings, H B; Verwer, R W; Pentney, R J; Woldenberg, M J
1992-09-01
The topological structure of a binary tree is characterized by a measure called tree asymmetry, defined as the mean value of the asymmetry of its partitions. The statistical properties of this tree-asymmetry measure have been studied using a growth model for binary trees. The tree-asymmetry measure appears to be sensitive for topological differences and the tree-asymmetry expectation for the growth model that we used appears to be almost independent of the size of the trees. These properties and the simple definition make the measure suitable for practical use, for instance for characterizing, comparing and interpreting sets of branching patterns. Examples are given of the analysis of three sets of neuronal branching patterns. It is shown that the variance in tree-asymmetry values for these observed branching patterns corresponds perfectly with the variance predicted by the used growth model.
Renormalization of QED with planar binary trees
International Nuclear Information System (INIS)
Brouder, C.
2001-01-01
The Dyson relations between renormalized and bare photon and electron propagators Z 3 anti D(q)=D(q) and Z 2 anti S(q)=S(q) are expanded over planar binary trees. This yields explicit recursive relations for the terms of the expansions. When all the trees corresponding to a given power of the electron charge are summed, recursive relations are obtained for the finite coefficients of the renormalized photon and electron propagators. These relations significantly decrease the number of integrals to carry out, as compared to the standard Feynman diagram technique. In the case of massless quantum electrodynamics (QED), the relation between renormalized and bare coefficients of the perturbative expansion is given in terms of a Hopf algebra structure. (orig.)
Collett, David
2002-01-01
INTRODUCTION Some Examples The Scope of this Book Use of Statistical Software STATISTICAL INFERENCE FOR BINARY DATA The Binomial Distribution Inference about the Success Probability Comparison of Two Proportions Comparison of Two or More Proportions MODELS FOR BINARY AND BINOMIAL DATA Statistical Modelling Linear Models Methods of Estimation Fitting Linear Models to Binomial Data Models for Binomial Response Data The Linear Logistic Model Fitting the Linear Logistic Model to Binomial Data Goodness of Fit of a Linear Logistic Model Comparing Linear Logistic Models Linear Trend in Proportions Comparing Stimulus-Response Relationships Non-Convergence and Overfitting Some other Goodness of Fit Statistics Strategy for Model Selection Predicting a Binary Response Probability BIOASSAY AND SOME OTHER APPLICATIONS The Tolerance Distribution Estimating an Effective Dose Relative Potency Natural Response Non-Linear Logistic Regression Models Applications of the Complementary Log-Log Model MODEL CHECKING Definition of Re...
Hyperspectral image representation and processing with binary partition trees
Valero Valbuena, Silvia
2012-01-01
Premi extraordinari doctorat curs 2011-2012, àmbit Enginyeria de les TIC The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. Therefore, under the title Hyperspectral image representation and Processing with Binary Partition Trees, this PhD thesis proposes the construction and the processing of a new region-based hierarchical hyperspectral image representation: the Binary Partition Tree (BPT). This hierarc...
Binary Tree Pricing to Convertible Bonds with Credit Risk under Stochastic Interest Rates
Directory of Open Access Journals (Sweden)
Jianbo Huang
2013-01-01
Full Text Available The convertible bonds usually have multiple additional provisions that make their pricing problem more difficult than straight bonds and options. This paper uses the binary tree method to model the finance market. As the underlying stock prices and the interest rates are important to the convertible bonds, we describe their dynamic processes by different binary tree. Moreover, we consider the influence of the credit risks on the convertible bonds that is described by the default rate and the recovery rate; then the two-factor binary tree model involving the credit risk is established. On the basis of the theoretical analysis, we make numerical simulation and get the pricing results when the stock prices are CRR model and the interest rates follow the constant volatility and the time-varying volatility, respectively. This model can be extended to other financial derivative instruments.
Succinct Representations of Binary Trees for Range Minimum Queries
DEFF Research Database (Denmark)
Davoodi, Pooya; Raman, Rajeev; Satti, Srinivasa
2012-01-01
We provide two succinct representations of binary trees that can be used to represent the Cartesian tree of an array A of size n. Both the representations take the optimal 2n + o(n) bits of space in the worst case and support range minimum queries (RMQs) in O(1) time. The first one is a modificat......We provide two succinct representations of binary trees that can be used to represent the Cartesian tree of an array A of size n. Both the representations take the optimal 2n + o(n) bits of space in the worst case and support range minimum queries (RMQs) in O(1) time. The first one...
Cache-Oblivious Search Trees via Binary Trees of Small Height
DEFF Research Database (Denmark)
Brodal, G.S.; Fagerberg, R.; Jacob, R.
2002-01-01
We propose a version of cache oblivious search trees which is simpler than the previous proposal of Bender, Demaine and Farach-Colton and has the same complexity bounds. In particular, our data structure avoids the use of weight balanced B-trees, and can be implemented as just a single array......, and range queries in worst case O(logB n + k/B) memory transfers, where k is the size of the output.The basic idea of our data structure is to maintain a dynamic binary tree of height log n+O(1) using existing methods, embed this tree in a static binary tree, which in turn is embedded in an array in a cache...... oblivious fashion, using the van Emde Boas layout of Prokop.We also investigate the practicality of cache obliviousness in the area of search trees, by providing an empirical comparison of different methods for laying out a search tree in memory....
E. Gregory McPherson; Paula J. Peper
2012-01-01
This paper describes three long-term tree growth studies conducted to evaluate tree performance because repeated measurements of the same trees produce critical data for growth model calibration and validation. Several empirical and process-based approaches to modeling tree growth are reviewed. Modeling is more advanced in the fields of forestry and...
Decision tree modeling using R.
Zhang, Zhongheng
2016-08-01
In machine learning field, decision tree learner is powerful and easy to interpret. It employs recursive binary partitioning algorithm that splits the sample in partitioning variable with the strongest association with the response variable. The process continues until some stopping criteria are met. In the example I focus on conditional inference tree, which incorporates tree-structured regression models into conditional inference procedures. While growing a single tree is subject to small changes in the training data, random forests procedure is introduced to address this problem. The sources of diversity for random forests come from the random sampling and restricted set of input variables to be selected. Finally, I introduce R functions to perform model based recursive partitioning. This method incorporates recursive partitioning into conventional parametric model building.
Mesoscopic model for binary fluids
Echeverria, C.; Tucci, K.; Alvarez-Llamoza, O.; Orozco-Guillén, E. E.; Morales, M.; Cosenza, M. G.
2017-10-01
We propose a model for studying binary fluids based on the mesoscopic molecular simulation technique known as multiparticle collision, where the space and state variables are continuous, and time is discrete. We include a repulsion rule to simulate segregation processes that does not require calculation of the interaction forces between particles, so binary fluids can be described on a mesoscopic scale. The model is conceptually simple and computationally efficient; it maintains Galilean invariance and conserves the mass and energy in the system at the micro- and macro-scale, whereas momentum is conserved globally. For a wide range of temperatures and densities, the model yields results in good agreement with the known properties of binary fluids, such as the density profile, interface width, phase separation, and phase growth. We also apply the model to the study of binary fluids in crowded environments with consistent results.
Exact Algorithms for Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees.
Kordi, Misagh; Bansal, Mukul S
2017-06-01
Duplication-Transfer-Loss (DTL) reconciliation is a powerful method for studying gene family evolution in the presence of horizontal gene transfer. DTL reconciliation seeks to reconcile gene trees with species trees by postulating speciation, duplication, transfer, and loss events. Efficient algorithms exist for finding optimal DTL reconciliations when the gene tree is binary. In practice, however, gene trees are often non-binary due to uncertainty in the gene tree topologies, and DTL reconciliation with non-binary gene trees is known to be NP-hard. In this paper, we present the first exact algorithms for DTL reconciliation with non-binary gene trees. Specifically, we (i) show that the DTL reconciliation problem for non-binary gene trees is fixed-parameter tractable in the maximum degree of the gene tree, (ii) present an exponential-time, but in-practice efficient, algorithm to track and enumerate all optimal binary resolutions of a non-binary input gene tree, and (iii) apply our algorithms to a large empirical data set of over 4700 gene trees from 100 species to study the impact of gene tree uncertainty on DTL-reconciliation and to demonstrate the applicability and utility of our algorithms. The new techniques and algorithms introduced in this paper will help biologists avoid incorrect evolutionary inferences caused by gene tree uncertainty.
Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2013-01-01
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree…
Misclassification in binary choice models
Czech Academy of Sciences Publication Activity Database
Meyer, B. D.; Mittag, Nikolas
2017-01-01
Roč. 200, č. 2 (2017), s. 295-311 ISSN 0304-4076 R&D Projects: GA ČR(CZ) GJ16-07603Y Institutional support: Progres-Q24 Keywords : measurement error * binary choice models * program take-up Subject RIV: AH - Economics OBOR OECD: Economic Theory Impact factor: 1.633, year: 2016
Misclassification in binary choice models
Czech Academy of Sciences Publication Activity Database
Meyer, B. D.; Mittag, Nikolas
2017-01-01
Roč. 200, č. 2 (2017), s. 295-311 ISSN 0304-4076 Institutional support: RVO:67985998 Keywords : measurement error * binary choice models * program take-up Subject RIV: AH - Economics OBOR OECD: Economic Theory Impact factor: 1.633, year: 2016
Using Binary Trees to Synchronize Events in Heterogeneous Datastreams
Directory of Open Access Journals (Sweden)
Stefan-Szalai Dragos
2012-06-01
Full Text Available In the context of growing ubiquity of sensors, surveillance equipment and other mobile devices, a shift in the data processing paradigm was necessary. New systems are required to be capable of processing data streams of infinite length, having a high throughput, that cannot be stored and processed using classical Database Management Systems (DBMSs. These are called Data Stream Management Systems (DSMSs within the scientific community. A first step performed by them is time synchronization between events arriving on different timestamped data streams. Within this paper an event synchronization method that makes use of binary trees to achieve its task is introduced and compared with other approaches in order to emphasize its strengths. Furthermore the integration with DSCPE (our Data Stream Continuous Processing Engine is proposed.
Structural Equation Model Trees
Brandmaier, Andreas M.; von Oertzen, Timo; McArdle, John J.; Lindenberger, Ulman
2015-01-01
In the behavioral and social sciences, structural equation models (SEMs) have become widely accepted as a modeling tool for the relation between latent and observed variables. SEMs can be seen as a unification of several multivariate analysis techniques. SEM Trees combine the strengths of SEMs and the decision tree paradigm by building tree structures that separate a data set recursively into subsets with significantly different parameter estimates in a SEM. SEM Trees provide means for finding covariates and covariate interactions that predict differences in structural parameters in observed as well as in latent space and facilitate theory-guided exploration of empirical data. We describe the methodology, discuss theoretical and practical implications, and demonstrate applications to a factor model and a linear growth curve model. PMID:22984789
Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa
2017-03-01
Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.
New binary polymorphisms reshape and increase resolution of the human Y chromosomal haplogroup tree.
Karafet, Tatiana M; Mendez, Fernando L; Meilerman, Monica B; Underhill, Peter A; Zegura, Stephen L; Hammer, Michael F
2008-05-01
Markers on the non-recombining portion of the human Y chromosome continue to have applications in many fields including evolutionary biology, forensics, medical genetics, and genealogical reconstruction. In 2002, the Y Chromosome Consortium published a single parsimony tree showing the relationships among 153 haplogroups based on 243 binary markers and devised a standardized nomenclature system to name lineages nested within this tree. Here we present an extensively revised Y chromosome tree containing 311 distinct haplogroups, including two new major haplogroups (S and T), and incorporating approximately 600 binary markers. We describe major changes in the topology of the parsimony tree and provide names for new and rearranged lineages within the tree following the rules presented by the Y Chromosome Consortium in 2002. Several changes in the tree topology have important implications for studies of human ancestry. We also present demography-independent age estimates for 11 of the major clades in the new Y chromosome tree.
A Markovian Growth Dynamics on Rooted Binary Trees Evolving According to the Gompertz Curve
Landim, C.; Portugal, R. D.; Svaiter, B. F.
2012-08-01
Inspired by biological dynamics, we consider a growth Markov process taking values on the space of rooted binary trees, similar to the Aldous-Shields (Probab. Theory Relat. Fields 79(4):509-542, 1988) model. Fix n≥1 and β>0. We start at time 0 with the tree composed of a root only. At any time, each node with no descendants, independently from the other nodes, produces two successors at rate β( n- k)/ n, where k is the distance from the node to the root. Denote by Z n ( t) the number of nodes with no descendants at time t and let T n = β -1 nln( n/ln4)+(ln2)/(2 β). We prove that 2- n Z n ( T n + nτ), τ∈ℝ, converges to the Gompertz curve exp(-(ln2) e - βτ ). We also prove a central limit theorem for the martingale associated to Z n ( t).
Comprehensive decision tree models in bioinformatics.
Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter
2012-01-01
Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly
Comprehensive decision tree models in bioinformatics.
Directory of Open Access Journals (Sweden)
Gregor Stiglic
Full Text Available PURPOSE: Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. METHODS: This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. RESULTS: The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. CONCLUSIONS: The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets
Directory of Open Access Journals (Sweden)
Tran Hoai Linh
2014-09-01
Full Text Available The paper presents a new system for ECG (ElectroCardioGraphy signal recognition using different neural classifiers and a binary decision tree to provide one more processing stage to give the final recognition result. As the base classifiers, the three classical neural models, i.e., the MLP (Multi Layer Perceptron, modified TSK (Takagi-Sugeno-Kang and the SVM (Support Vector Machine, will be applied. The coefficients in ECG signal decomposition using Hermite basis functions and the peak-to-peak periods of the ECG signals will be used as features for the classifiers. Numerical experiments will be performed for the recognition of different types of arrhythmia in the ECG signals taken from the MIT-BIH (Massachusetts Institute of Technology and Boston’s Beth Israel Hospital Arrhythmia Database. The results will be compared with individual base classifiers’ performances and with other integration methods to show the high quality of the proposed solution
Chang, Chi-Yung (Inventor); Fang, Wai-Chi (Inventor); Curlander, John C. (Inventor)
1995-01-01
A system for data compression utilizing systolic array architecture for Vector Quantization (VQ) is disclosed for both full-searched and tree-searched. For a tree-searched VQ, the special case of a Binary Tree-Search VQ (BTSVQ) is disclosed with identical Processing Elements (PE) in the array for both a Raw-Codebook VQ (RCVQ) and a Difference-Codebook VQ (DCVQ) algorithm. A fault tolerant system is disclosed which allows a PE that has developed a fault to be bypassed in the array and replaced by a spare at the end of the array, with codebook memory assignment shifted one PE past the faulty PE of the array.
A simple model for binary star evolution
International Nuclear Information System (INIS)
Whyte, C.A.; Eggleton, P.P.
1985-01-01
A simple model for calculating the evolution of binary stars is presented. Detailed stellar evolution calculations of stars undergoing mass and energy transfer at various rates are reported and used to identify the dominant physical processes which determine the type of evolution. These detailed calculations are used to calibrate the simple model and a comparison of calculations using the detailed stellar evolution equations and the simple model is made. Results of the evolution of a few binary systems are reported and compared with previously published calculations using normal stellar evolution programs. (author)
Modelling tree biomasses in Finland
Energy Technology Data Exchange (ETDEWEB)
Repola, J.
2013-06-01
Biomass equations for above- and below-ground tree components of Scots pine (Pinus sylvestris L), Norway spruce (Picea abies [L.] Karst) and birch (Betula pendula Roth and Betula pubescens Ehrh.) were compiled using empirical material from a total of 102 stands. These stands (44 Scots pine, 34 Norway spruce and 24 birch stands) were located mainly on mineral soil sites representing a large part of Finland. The biomass models were based on data measured from 1648 sample trees, comprising 908 pine, 613 spruce and 127 birch trees. Biomass equations were derived for the total above-ground biomass and for the individual tree components: stem wood, stem bark, living and dead branches, needles, stump, and roots, as dependent variables. Three multivariate models with different numbers of independent variables for above-ground biomass and one for below-ground biomass were constructed. Variables that are normally measured in forest inventories were used as independent variables. The simplest model formulations, multivariate models (1) were mainly based on tree diameter and height as independent variables. In more elaborated multivariate models, (2) and (3), additional commonly measured tree variables such as age, crown length, bark thickness and radial growth rate were added. Tree biomass modelling includes consecutive phases, which cause unreliability in the prediction of biomass. First, biomasses of sample trees should be determined reliably to decrease the statistical errors caused by sub-sampling. In this study, methods to improve the accuracy of stem biomass estimates of the sample trees were developed. In addition, the reliability of the method applied to estimate sample-tree crown biomass was tested, and no systematic error was detected. Second, the whole information content of data should be utilized in order to achieve reliable parameter estimates and applicable and flexible model structure. In the modelling approach, the basic assumption was that the biomasses of
Energy Technology Data Exchange (ETDEWEB)
Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay, Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)
2010-12-15
Over the last two decades binary decision diagrams have been applied successfully to improve Boolean reliability models. Conversely to the classical approach based on the computation of the MCS, the BDD approach involves no approximation in the quantification of the model and is able to handle correctly negative logic. However, when models are sufficiently large and complex, as for example the ones coming from the PSA studies of the nuclear industry, it begins to be unfeasible to compute the BDD within a reasonable amount of time and computer memory. Therefore, simplification or reduction of the full model has to be considered in some way to adapt the application of the BDD technology to the assessment of such models in practice. This paper proposes a reduction process based on using information provided by the set of the most relevant minimal cutsets of the model in order to perform the reduction directly on it. This allows controlling the degree of reduction and therefore the impact of such simplification on the final quantification results. This reduction is integrated in an incremental procedure that is compatible with the dynamic generation of the event trees and therefore adaptable to the recent dynamic developments and extensions of the PSA studies. The proposed method has been applied to a real case study, and the results obtained confirm that the reduction enables the BDD computation while maintaining accuracy.
Eclipsing binary stars modeling and analysis
Kallrath, Josef
1999-01-01
This book focuses on the formulation of mathematical models for the light curves of eclipsing binary stars, and on the algorithms for generating such models Since information gained from binary systems provides much of what we know of the masses, luminosities, and radii of stars, such models are acquiring increasing importance in studies of stellar structure and evolution As in other areas of science, the computer revolution has given many astronomers tools that previously only specialists could use; anyone with access to a set of data can now expect to be able to model it This book will provide astronomers, both amateur and professional, with a guide for - specifying an astrophysical model for a set of observations - selecting an algorithm to determine the parameters of the model - estimating the errors of the parameters It is written for readers with knowledge of basic calculus and linear algebra; appendices cover mathematical details on such matters as optimization, coordinate systems, and specific models ...
An ordering heuristic for building Binary Decision Diagrams for fault-trees
Energy Technology Data Exchange (ETDEWEB)
Bouissou, M. [Electricite de France (EDF), 75 - Paris (France)
1997-12-31
Binary Decision Diagrams (BDD) have recently made a noticeable entry in the RAMS field. This kind of representation for boolean functions makes possible the assessment of complex fault-trees, both qualitatively (minimal cut-sets search) and quantitatively (exact calculation of top event probability). The object of the paper is to present a pre-processing of the fault-tree which ensures that the results given by different heuristics on the `optimized` fault-tree are not too sensitive to the way the tree is written. This property is based on a theoretical proof. In contrast with some well known heuristics, the method proposed is not based only on intuition and practical experiments. (author) 12 refs.
An ordering heuristic for building Binary Decision Diagrams for fault-trees
International Nuclear Information System (INIS)
Bouissou, M.
1997-01-01
Binary Decision Diagrams (BDD) have recently made a noticeable entry in the RAMS field. This kind of representation for boolean functions makes possible the assessment of complex fault-trees, both qualitatively (minimal cut-sets search) and quantitatively (exact calculation of top event probability). The object of the paper is to present a pre-processing of the fault-tree which ensures that the results given by different heuristics on the 'optimized' fault-tree are not too sensitive to the way the tree is written. This property is based on a theoretical proof. In contrast with some well known heuristics, the method proposed is not based only on intuition and practical experiments. (author)
On the Ising model with competing interactions on a Cayley tree: Gibbs measures, free energy
International Nuclear Information System (INIS)
Mukhamedov, Farruh; Rozikov, Utkir
2003-05-01
In the present paper the Ising model with competing binary J and J 1 interactions with spin values ± 1, on a Cayley tree is considered. We study translation-invariant Gibbs measures and corresponding free energies ones. (author)
EXACT LOGISTIC MODELS FOR NESTED BINARY DATA
TROXLER, STEVEN; LALONDE, TRENT; WILSON, JEFFREY R.
2011-01-01
The use of logistic models for independent binary data has relied first on asymptotic theory and later on exact distributions for small samples. However, the use of logistic models for dependent analysis based on exact analysis is not as common. Moreover attention is usually given to one-stage clustering. In this paper we extend the exact techniques to address hypothesis testing (estimation is not addressed) for data with second-stage and probably higher levels of clustering. The methods are ...
A Beta-splitting model for evolutionary trees.
Sainudiin, Raazesh; Véber, Amandine
2016-05-01
In this article, we construct a generalization of the Blum-François Beta-splitting model for evolutionary trees, which was itself inspired by Aldous' Beta-splitting model on cladograms. The novelty of our approach allows for asymmetric shares of diversification rates (or diversification 'potential') between two sister species in an evolutionarily interpretable manner, as well as the addition of extinction to the model in a natural way. We describe the incremental evolutionary construction of a tree with n leaves by splitting or freezing extant lineages through the generating, organizing and deleting processes. We then give the probability of any (binary rooted) tree under this model with no extinction, at several resolutions: ranked planar trees giving asymmetric roles to the first and second offspring species of a given species and keeping track of the order of the speciation events occurring during the creation of the tree, unranked planar trees, ranked non-planar trees and finally (unranked non-planar) trees. We also describe a continuous-time equivalent of the generating, organizing and deleting processes where tree topology and branch lengths are jointly modelled and provide code in SageMath/Python for these algorithms.
Behzadi, Naghi; Ahansaz, Bahram
2018-04-01
We propose a mechanism for quantum state transfer (QST) over a binary tree spin network on the basis of incomplete collapsing measurements. To this aim, we perform initially a weak measurement (WM) on the central qubit of the binary tree network where the state of our concern has been prepared on that qubit. After the time evolution of the whole system, a quantum measurement reversal (QMR) is performed on a chosen target qubit. By taking optimal value for the strength of QMR, it is shown that the QST quality from the sending qubit to any typical target qubit on the binary tree is considerably improved in terms of the WM strength. Also, we show that how high-quality entanglement distribution over the binary tree network is achievable by using this approach.
Asteroseismic modelling of the Binary HD 176465
Directory of Open Access Journals (Sweden)
Nsamba B.
2017-01-01
Full Text Available The detection and analysis of oscillations in binary star systems is critical in understanding stellar structure and evolution. This is partly because such systems have the same initial chemical composition and age. Solar-like oscillations have been detected by Kepler in both components of the asteroseismic binary HD 176465. We present an independent modelling of each star in this binary system. Stellar models generated using MESA (Modules for Experiments in Stellar Astrophysics were fitted to both the observed individual frequencies and complementary spectroscopic parameters. The individual theoretical oscillation frequencies for the corresponding stellar models were obtained using GYRE as the pulsation code. A Bayesian approach was applied to find the probability distribution functions of the stellar parameters using AIMS (Asteroseismic Inference on a Massive Scale as the optimisation code. The ages of HD 176465 A and HD 176465 B were found to be 2.81 ± 0.48 Gyr and 2.52 ± 0.80 Gyr, respectively. These results are in agreement when compared to previous studies carried out using other asteroseismic modelling techniques and gyrochronology.
Binary choice models with endogenous regressors
Christopher Baum; Yingying Dong; Arthur Lewbel; Tao Yang
2012-01-01
Dong and Lewbel have developed the theory of simple estimators for binary choice models with endogenous or mismeasured regressors, depending on a `special regressor' as defined by Lewbel (J. Econometrics, 2000). `Control function' methods such as Stata's ivprobit are generally only valid when endogenous regressors are consistent. The estimators proposed here can be used with limited, censored, continuous or discrete endogenous regressors, and have significant advantages over alternatives such...
ACOUSTIC EFFECTS ON BINARY AEROELASTICITY MODEL
Directory of Open Access Journals (Sweden)
Kok Hwa Yu
2011-10-01
Full Text Available Acoustics is the science concerned with the study of sound. The effects of sound on structures attract overwhelm interests and numerous studies were carried out in this particular area. Many of the preliminary investigations show that acoustic pressure produces significant influences on structures such as thin plate, membrane and also high-impedance medium like water (and other similar fluids. Thus, it is useful to investigate the structure response with the presence of acoustics on aircraft, especially on aircraft wings, tails and control surfaces which are vulnerable to flutter phenomena. The present paper describes the modeling of structural-acoustic interactions to simulate the external acoustic effect on binary flutter model. Here, the binary flutter model which illustrated as a rectangular wing is constructed using strip theory with simplified unsteady aerodynamics involving flap and pitch degree of freedom terms. The external acoustic excitation, on the other hand, is modeled using four-node quadrilateral isoparametric element via finite element approach. Both equations then carefully coupled and solved using eigenvalue solution. The mentioned approach is implemented in MATLAB and the outcome of the simulated result are later described, analyzed and illustrated in this paper.
Modeling and analysis of advanced binary cycles
Energy Technology Data Exchange (ETDEWEB)
Gawlik, K.
1997-12-31
A computer model (Cycle Analysis Simulation Tool, CAST) and a methodology have been developed to perform value analysis for small, low- to moderate-temperature binary geothermal power plants. The value analysis method allows for incremental changes in the levelized electricity cost (LEC) to be determined between a baseline plant and a modified plant. Thermodynamic cycle analyses and component sizing are carried out in the model followed by economic analysis which provides LEC results. The emphasis of the present work is on evaluating the effect of mixed working fluids instead of pure fluids on the LEC of a geothermal binary plant that uses a simple Organic Rankine Cycle. Four resources were studied spanning the range of 265{degrees}F to 375{degrees}F. A variety of isobutane and propane based mixtures, in addition to pure fluids, were used as working fluids. This study shows that the use of propane mixtures at a 265{degrees}F resource can reduce the LEC by 24% when compared to a base case value that utilizes commercial isobutane as its working fluid. The cost savings drop to 6% for a 375{degrees}F resource, where an isobutane mixture is favored. Supercritical cycles were found to have the lowest cost at all resources.
Solitary waves in dimer binary collision model
Ahsan, Zaid; Jayaprakash, K. R.
2017-01-01
Solitary wave propagation in nonlinear diatomic (dimer) chains is a very interesting topic of research in the study of nonlinear lattices. Such waves were recently found to be supported by the essentially nonlinear granular lattice and Toda lattice. An interesting aspect of this discovery is attributed to the realization of a spectrum of the mass ratio (the only system parameter governing the dynamics) that supports the propagation of such waves corresponding to the considered interaction potential. The objective of this exposition is to explore solitary wave propagation in the dimer binary collision (BC) model. Interestingly, the dimer BC model supports solitary wave propagation at a discrete spectrum of mass ratios similar to those observed in granular and Toda dimers. Further, we report a qualitative and one-to-one correspondence between the spectrum of the mass ratio corresponding to the dimer BC model and those corresponding to granular and Toda dimer chains.
A binary electrolyte model of a cylindrical alkaline cell
Kriegsmann, J. J.; Cheh, H. Y.
A cylindrical alkaline cell is modeled as a binary electrolyte system by assuming the direct electrochemical formation of ZnO in the anode. Justifications for replacing the dissolution-precipitation mechanism are provided. Compared to the original model, the binary electrolyte model has a more understandable model formulation, more consistent physical property data, and greater flexibility in certain instances. The binary electrolyte model predicts a longer cell life and higher operating voltage than the ternary electrolyte model for the test case discharge rate. There are no numerical difficulties associated with the zincate ion in the binary electrolyte model, because this species is not considered. The characteristics and advantages of the simplified anode behavior are discussed. An application of the binary electrolyte model is included.
2014-01-01
Background Reticulate events play an important role in determining evolutionary relationships. The problem of computing the minimum number of such events to explain discordance between two phylogenetic trees is a hard computational problem. Even for binary trees, exact solvers struggle to solve instances with reticulation number larger than 40-50. Results Here we present CycleKiller and NonbinaryCycleKiller, the first methods to produce solutions verifiably close to optimality for instances with hundreds or even thousands of reticulations. Conclusions Using simulations, we demonstrate that these algorithms run quickly for large and difficult instances, producing solutions that are very close to optimality. As a spin-off from our simulations we also present TerminusEst, which is the fastest exact method currently available that can handle nonbinary trees: this is used to measure the accuracy of the NonbinaryCycleKiller algorithm. All three methods are based on extensions of previous theoretical work (SIDMA 26(4):1635-1656, TCBB 10(1):18-25, SIDMA 28(1):49-66) and are publicly available. We also apply our methods to real data. PMID:24884964
Anatomical modeling of the bronchial tree
Hentschel, Gerrit; Klinder, Tobias; Blaffert, Thomas; Bülow, Thomas; Wiemker, Rafael; Lorenz, Cristian
2010-02-01
The bronchial tree is of direct clinical importance in the context of respective diseases, such as chronic obstructive pulmonary disease (COPD). It furthermore constitutes a reference structure for object localization in the lungs and it finally provides access to lung tissue in, e.g., bronchoscope based procedures for diagnosis and therapy. This paper presents a comprehensive anatomical model for the bronchial tree, including statistics of position, relative and absolute orientation, length, and radius of 34 bronchial segments, going beyond previously published results. The model has been built from 16 manually annotated CT scans, covering several branching variants. The model is represented as a centerline/tree structure but can also be converted in a surface representation. Possible model applications are either to anatomically label extracted bronchial trees or to improve the tree extraction itself by identifying missing segments or sub-trees, e.g., if located beyond a bronchial stenosis. Bronchial tree labeling is achieved using a naïve Bayesian classifier based on the segment properties contained in the model in combination with tree matching. The tree matching step makes use of branching variations covered by the model. An evaluation of the model has been performed in a leaveone- out manner. In total, 87% of the branches resulting from preceding airway tree segmentation could be correctly labeled. The individualized model enables the detection of missing branches, allowing a targeted search, e.g., a local rerun of the tree-segmentation segmentation.
Star formation history: Modeling of visual binaries
Gebrehiwot, Y. M.; Tessema, S. B.; Malkov, O. Yu.; Kovaleva, D. A.; Sytov, A. Yu.; Tutukov, A. V.
2018-05-01
Most stars form in binary or multiple systems. Their evolution is defined by masses of components, orbital separation and eccentricity. In order to understand star formation and evolutionary processes, it is vital to find distributions of physical parameters of binaries. We have carried out Monte Carlo simulations in which we simulate different pairing scenarios: random pairing, primary-constrained pairing, split-core pairing, and total and primary pairing in order to get distributions of binaries over physical parameters at birth. Next, for comparison with observations, we account for stellar evolution and selection effects. Brightness, radius, temperature, and other parameters of components are assigned or calculated according to approximate relations for stars in different evolutionary stages (main-sequence stars, red giants, white dwarfs, relativistic objects). Evolutionary stage is defined as a function of system age and component masses. We compare our results with the observed IMF, binarity rate, and binary mass-ratio distributions for field visual binaries to find initial distributions and pairing scenarios that produce observed distributions.
The Binary Customer Satisfaction Model in Inventory and Queueing Systems
Azadivar, Justin Sepehr
2010-01-01
This dissertation introduces the Binary Customer Satisfaction Model for addressing logistics issues. In typical logistics problems, the arrival of customers through a demand process is considered external to the management decisions. In practice, it is typically the case that customers will respond to changes is service policy by changing their behavior. The Binary Customer Satisfaction Model provides a simple customer behavior model that directly interacts with the service policy and provide...
Thuillard, Marc; Fraix-Burnet, Didier
2015-01-01
This article presents an innovative approach to phylogenies based on the reduction of multistate characters to binary-state characters. We show that the reduction to binary characters’ approach can be applied to both character- and distance-based phylogenies and provides a unifying framework to explain simply and intuitively the similarities and differences between distance- and character-based phylogenies. Building on these results, this article gives a possible explanation on why phylogenetic trees obtained from a distance matrix or a set of characters are often quite reasonable despite lateral transfers of genetic material between taxa. In the presence of lateral transfers, outer planar networks furnish a better description of evolution than phylogenetic trees. We present a polynomial-time reconstruction algorithm for perfect outer planar networks with a fixed number of states, characters, and lateral transfers. PMID:26508826
Interactive wood combustion for botanical tree models
Pirk, Sören
2017-11-22
We present a novel method for the combustion of botanical tree models. Tree models are represented as connected particles for the branching structure and a polygonal surface mesh for the combustion. Each particle stores biological and physical attributes that drive the kinetic behavior of a plant and the exothermic reaction of the combustion. Coupled with realistic physics for rods, the particles enable dynamic branch motions. We model material properties, such as moisture and charring behavior, and associate them with individual particles. The combustion is efficiently processed in the surface domain of the tree model on a polygonal mesh. A user can dynamically interact with the model by initiating fires and by inducing stress on branches. The flames realistically propagate through the tree model by consuming the available resources. Our method runs at interactive rates and supports multiple tree instances in parallel. We demonstrate the effectiveness of our approach through numerous examples and evaluate its plausibility against the combustion of real wood samples.
2012-01-01
Background There are several common ways to encode a tree as a matrix, such as the adjacency matrix, the Laplacian matrix (that is, the infinitesimal generator of the natural random walk), and the matrix of pairwise distances between leaves. Such representations involve a specific labeling of the vertices or at least the leaves, and so it is natural to attempt to identify trees by some feature of the associated matrices that is invariant under relabeling. An obvious candidate is the spectrum of eigenvalues (or, equivalently, the characteristic polynomial). Results We show for any of these choices of matrix that the fraction of binary trees with a unique spectrum goes to zero as the number of leaves goes to infinity. We investigate the rate of convergence of the above fraction to zero using numerical methods. For the adjacency and Laplacian matrices, we show that the a priori more informative immanantal polynomials have no greater power to distinguish between trees. Conclusion Our results show that a generic large binary tree is highly unlikely to be identified uniquely by common spectral invariants. PMID:22613173
Combining binary classifiers to improve tree species discrimination at leaf level
CSIR Research Space (South Africa)
Dastile, X
2012-11-01
Full Text Available , direct 7-class prediction results in high misclassification rates. We therefore construct binary classifiers for all possible binary classification problems and combine them using Error Correcting Output Codes (ECOC) to form a 7-class predictor. ECOC...
International Nuclear Information System (INIS)
Nusbaumer, O. P. M.
2007-01-01
This study is concerned with the quantification of Probabilistic Risk Assessment (PRA) using linked Fault Tree (FT) models. Probabilistic Risk assessment (PRA) of Nuclear Power Plants (NPPs) complements traditional deterministic analysis; it is widely recognized as a comprehensive and structured approach to identify accident scenarios and to derive numerical estimates of the associated risk levels. PRA models as found in the nuclear industry have evolved rapidly. Increasingly, they have been broadly applied to support numerous applications on various operational and regulatory matters. Regulatory bodies in many countries require that a PRA be performed for licensing purposes. PRA has reached the point where it can considerably influence the design and operation of nuclear power plants. However, most of the tools available for quantifying large PRA models are unable to produce analytically correct results. The algorithms of such quantifiers are designed to neglect sequences when their likelihood decreases below a predefined cutoff limit. In addition, the rare event approximation (e.g. Moivre's equation) is typically implemented for the first order, ignoring the success paths and the possibility that two or more events can occur simultaneously. This is only justified in assessments where the probabilities of the basic events are low. When the events in question are failures, the first order rare event approximation is always conservative, resulting in wrong interpretation of risk importance measures. Advanced NPP PRA models typically include human errors, common cause failure groups, seismic and phenomenological basic events, where the failure probabilities may approach unity, leading to questionable results. It is accepted that current quantification tools have reached their limits, and that new quantification techniques should be investigated. A novel approach using the mathematical concept of Binary Decision Diagram (BDD) is proposed to overcome these deficiencies
International Nuclear Information System (INIS)
Jerebko, Anna K.; Summers, Ronald M.; Malley, James D.; Franaszek, Marek; Johnson, C. Daniel
2003-01-01
Detection of colonic polyps in CT colonography is problematic due to complexities of polyp shape and the surface of the normal colon. Published results indicate the feasibility of computer-aided detection of polyps but better classifiers are needed to improve specificity. In this paper we compare the classification results of two approaches: neural networks and recursive binary trees. As our starting point we collect surface geometry information from three-dimensional reconstruction of the colon, followed by a filter based on selected variables such as region density, Gaussian and average curvature and sphericity. The filter returns sites that are candidate polyps, based on earlier work using detection thresholds, to which the neural nets or the binary trees are applied. A data set of 39 polyps from 3 to 25 mm in size was used in our investigation. For both neural net and binary trees we use tenfold cross-validation to better estimate the true error rates. The backpropagation neural net with one hidden layer trained with Levenberg-Marquardt algorithm achieved the best results: sensitivity 90% and specificity 95% with 16 false positives per study
Cell lineage tree models of neurogenesis.
Slater, Jennifer L; Landman, Kerry A; Hughes, Barry D; Shen, Qin; Temple, Sally
2009-01-21
The production of neurons to form the mammalian cortex, known as embryonic cortical neurogenesis, is a complex developmental process. Insight into the process of cell division during neurogenesis is provided by murine cortical cell lineage trees, recorded through experimental observation. Recurring patterns within cell lineage trees may be indicative of predetermined cell behaviour. The application of mathematical modelling to this process requires careful consideration and identification of the key features to be incorporated into the model. A biologically plausible stochastic model of evolution of cell lineage trees is developed, based on the most important known features of neurogenesis. Tractable means of measuring lineage tree shape are discussed. Symmetry is identified as a significant feature of shape and is measured using Colless's Index of Imbalance. Distributions of tree size and imbalance for large tree sizes are computed and results compared to experimental data. Several refinements to the model are investigated, when the cell division probabilities are weighted according to cell generation. Two models involving generation-dependent cell division probabilities produce imbalance distributions which are the most consistent with the available experimental results. The results indicate that a stochastic cell division mechanism is a plausible basis of mammalian neurogenesis.
Algorithms for Computing the Triplet and Quartet Distances for Binary and General Trees
DEFF Research Database (Denmark)
Sand, Andreas; Holt, Morten Kragelund; Johansen, Jens
2013-01-01
Distance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves, respecti......Distance measures between trees are useful for comparing trees in a systematic manner, and several different distance measures have been proposed. The triplet and quartet distances, for rooted and unrooted trees, respectively, are defined as the number of subsets of three or four leaves...
Currency Arbitrage Detection Using a Binary Integer Programming Model
Soon, Wanmei; Ye, Heng-Qing
2011-01-01
In this article, we examine the use of a new binary integer programming (BIP) model to detect arbitrage opportunities in currency exchanges. This model showcases an excellent application of mathematics to the real world. The concepts involved are easily accessible to undergraduate students with basic knowledge in Operations Research. Through this…
Evolutionary model of the subdwarf binary system LB3459
International Nuclear Information System (INIS)
Paczynski, B.; Dearborn, D.S.
1980-01-01
An evolutionary model is proposed for the eclipsing binary system LB 3459 (=CPD-60 0 389 = HDE 269696). The two stars are hot subdwarfs with degenerate helium cores, hydrogen burning shell sources and low mass hydrogen rich envelopes. The system probably evolved through two common envelope phases. After the first such phase it might look like the semi-detached binary AS Eri. Soon after the second common envelope phase the system might look like UU Sge, an eclipsing binary nucleus of a planetary nebula. The present mass of the optical (spectroscopic) primary is probably close to 0.24 solar mass, and the predicted radial velocity amplitude of the primary is about 150 km/s. The optical secondary should be hotter and bolometrically brighter, with a mass of 0.32 solar mass. The primary eclipse is an occultation. (author)
a comparative study of models for correlated binary data with ...
African Journals Online (AJOL)
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significance. Next, several subsets of predictors are compared through the AIC criterion, whenever applicable. Key words/phrases: Beta-binomial, bootstrap, correlated binary data, model selection, overdispersion. *. Current address: University of Hannover, Bioinformatic Unit, Herrenhauser Strasse 2, D-30419 Hannover, ...
A comparative study of models for correlated binary data with ...
African Journals Online (AJOL)
Various methods of modeling correlated binary data are compared as applied to data from health services research. The methods include the standard logistic regression, a simple adjustment of the standard errors of logistic regression by a single inflator, the weighted logistic regression, the generalized estimating equation ...
PHYSICS OF ECLIPSING BINARIES. II. TOWARD THE INCREASED MODEL FIDELITY
Energy Technology Data Exchange (ETDEWEB)
Prša, A.; Conroy, K. E.; Horvat, M.; Kochoska, A.; Hambleton, K. M. [Villanova University, Dept. of Astrophysics and Planetary Sciences, 800 E Lancaster Avenue, Villanova PA 19085 (United States); Pablo, H. [Université de Montréal, Pavillon Roger-Gaudry, 2900, boul. Édouard-Montpetit Montréal QC H3T 1J4 (Canada); Bloemen, S. [Radboud University Nijmegen, Department of Astrophysics, IMAPP, P.O. Box 9010, 6500 GL, Nijmegen (Netherlands); Giammarco, J. [Eastern University, Dept. of Astronomy and Physics, 1300 Eagle Road, St. Davids, PA 19087 (United States); Degroote, P. [KU Leuven, Instituut voor Sterrenkunde, Celestijnenlaan 200D, B-3001 Heverlee (Belgium)
2016-12-01
The precision of photometric and spectroscopic observations has been systematically improved in the last decade, mostly thanks to space-borne photometric missions and ground-based spectrographs dedicated to finding exoplanets. The field of eclipsing binary stars strongly benefited from this development. Eclipsing binaries serve as critical tools for determining fundamental stellar properties (masses, radii, temperatures, and luminosities), yet the models are not capable of reproducing observed data well, either because of the missing physics or because of insufficient precision. This led to a predicament where radiative and dynamical effects, insofar buried in noise, started showing up routinely in the data, but were not accounted for in the models. PHOEBE (PHysics Of Eclipsing BinariEs; http://phoebe-project.org) is an open source modeling code for computing theoretical light and radial velocity curves that addresses both problems by incorporating missing physics and by increasing the computational fidelity. In particular, we discuss triangulation as a superior surface discretization algorithm, meshing of rotating single stars, light travel time effects, advanced phase computation, volume conservation in eccentric orbits, and improved computation of local intensity across the stellar surfaces that includes the photon-weighted mode, the enhanced limb darkening treatment, the better reflection treatment, and Doppler boosting. Here we present the concepts on which PHOEBE is built and proofs of concept that demonstrate the increased model fidelity.
A binary logistic regression model with complex sampling design of ...
African Journals Online (AJOL)
A binary logistic regression model with complex sampling design of unmet need for family planning among all women aged (15-49) in Ethiopia. ... Conclusion: The key determinants of unmet need family planning in Ethiopia were residence, age, marital-status, education, household members, birth-events and number of ...
Binary Model for the Heartbeat Star System KIC 4142768
Manuel, Joseph; Hambleton, Kelly
2018-01-01
Heartbeat stars are a class of eccentric (e > 0.2) binary systems that undergo strong tidal forces. These tidal forces cause the shape of each star and the temperature across the stellar surfaces to change. This effect also generates variations in the light curve in the form of tidally-induced pulsations, which are theorized to have a significant effect on the circularization of eccentric orbits (Zahn, 1975). Using the binary modeling software PHOEBE (Prša & Zwitter 2005) on the Kepler photometric data and Keck radial velocity data for the eclipsing, heartbeat star KIC 4142768, we have determined the fundamental parameters including masses and radii. The frequency analysis of the residual data has surprisingly revealed approximately 29 pulsations with 8 being Delta Scuti pulsations, 10 being Gamma Doradus pulsations, and 11 being tidally-induced pulsations. After subtracting an initial binary model from the original, detrended photometric data, we analyzed the pulsation frequencies in the residual data. We then were able to disentangle the identified pulsations from the original data in order to conduct subsequent binary modeling. We plan to continue this study by applying asteroseismology to KIC 4142768. Through our continued investigation, we hope to extract information about the star’s internal structure and expect this will yield additional, interesting results.
Latent Classification Models for Binary Data
DEFF Research Database (Denmark)
Langseth, Helge; Nielsen, Thomas Dyhre
2009-01-01
the class of that instance. To relax this independence assumption, we have in previous work proposed a family of models, called latent classification models (LCMs). LCMs are defined for continuous domains and generalize the naive Bayes model by using latent variables to model class-conditional dependencies...... between the attributes. In addition to providing good classification accuracy, the LCM model has several appealing properties, including a relatively small parameter space making it less susceptible to over-fitting. In this paper we take a first-step towards generalizing LCMs to hybrid domains...... of different domains, including the problem of recognizing symbols in black and white images....
Guideliness for system modeling: fault tree [analysis
Energy Technology Data Exchange (ETDEWEB)
Lee, Yoon Hwan; Yang, Joon Eon; Kang, Dae Il; Hwang, Mee Jeong
2004-07-01
This document, the guidelines for system modeling related to Fault Tree Analysis(FTA), is intended to provide the guidelines with the analyzer to construct the fault trees in the level of the capability category II of ASME PRA standard. Especially, they are to provide the essential and basic guidelines and the related contents to be used in support of revising the Ulchin 3 and 4 PSA model for risk monitor within the capability category II of ASME PRA standard. Normally the main objective of system analysis is to assess the reliability of system modeled by Event Tree Analysis (ETA). A variety of analytical techniques can be used for the system analysis, however, FTA method is used in this procedures guide. FTA is the method used for representing the failure logic of plant systems deductively using AND, OR or NOT gates. The fault tree should reflect all possible failure modes that may contribute to the system unavailability. This should include contributions due to the mechanical failures of the components, Common Cause Failures (CCFs), human errors and outages for testing and maintenance. This document identifies and describes the definitions and the general procedures of FTA and the essential and basic guidelines for reving the fault trees. Accordingly, the guidelines for FTA will be capable to guide the FTA to the level of the capability category II of ASME PRA standard.
Golzari, Fahimeh; Jalili, Saeed
2015-07-21
In protein function prediction (PFP) problem, the goal is to predict function of numerous well-sequenced known proteins whose function is not still known precisely. PFP is one of the special and complex problems in machine learning domain in which a protein (regarded as instance) may have more than one function simultaneously. Furthermore, the functions (regarded as classes) are dependent and also are organized in a hierarchical structure in the form of a tree or directed acyclic graph. One of the common learning methods proposed for solving this problem is decision trees in which, by partitioning data into sharp boundaries sets, small changes in the attribute values of a new instance may cause incorrect change in predicted label of the instance and finally misclassification. In this paper, a Variance Reduction based Binary Fuzzy Decision Tree (VR-BFDT) algorithm is proposed to predict functions of the proteins. This algorithm just fuzzifies the decision boundaries instead of converting the numeric attributes into fuzzy linguistic terms. It has the ability of assigning multiple functions to each protein simultaneously and preserves the hierarchy consistency between functional classes. It uses the label variance reduction as splitting criterion to select the best "attribute-value" at each node of the decision tree. The experimental results show that the overall performance of the proposed algorithm is promising. Copyright © 2015 Elsevier Ltd. All rights reserved.
Random trinomial tree models and vanilla options
Ganikhodjaev, Nasir; Bayram, Kamola
2013-09-01
In this paper we introduce and study random trinomial model. The usual trinomial model is prescribed by triple of numbers (u, d, m). We call the triple (u, d, m) an environment of the trinomial model. A triple (Un, Dn, Mn), where {Un}, {Dn} and {Mn} are the sequences of independent, identically distributed random variables with 0 < Dn < 1 < Un and Mn = 1 for all n, is called a random environment and trinomial tree model with random environment is called random trinomial model. The random trinomial model is considered to produce more accurate results than the random binomial model or usual trinomial model.
Directory of Open Access Journals (Sweden)
Liran Carmel
2010-01-01
Full Text Available Evolutionary binary characters are features of species or genes, indicating the absence (value zero or presence (value one of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus, gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes and events (gain and loss events along branches.
Carmel, Liran; Wolf, Yuri I; Rogozin, Igor B; Koonin, Eugene V
2010-01-01
Evolutionary binary characters are features of species or genes, indicating the absence (value zero) or presence (value one) of some property. Examples include eukaryotic gene architecture (the presence or absence of an intron in a particular locus), gene content, and morphological characters. In many studies, the acquisition of such binary characters is assumed to represent a rare evolutionary event, and consequently, their evolution is analyzed using various flavors of parsimony. However, when gain and loss of the character are not rare enough, a probabilistic analysis becomes essential. Here, we present a comprehensive probabilistic model to describe the evolution of binary characters on a bifurcating phylogenetic tree. A fast software tool, EREM, is provided, using maximum likelihood to estimate the parameters of the model and to reconstruct ancestral states (presence and absence in internal nodes) and events (gain and loss events along branches).
Confounding of three binary-variables counterfactual model
Liu, Jingwei; Hu, Shuang
2011-01-01
Confounding of three binary-variables counterfactual model is discussed in this paper. According to the effect between the control variable and the covariate variable, we investigate three counterfactual models: the control variable is independent of the covariate variable, the control variable has the effect on the covariate variable and the covariate variable affects the control variable. Using the ancillary information based on conditional independence hypotheses, the sufficient conditions...
Tree taper models for Cupressus lusitanica plantations in Ethiopia ...
African Journals Online (AJOL)
... found to vary from tree to tree and also appear to depend on tree size. The results from both the Monte Carlo and mixed effects modeling study seem to indicate the need to estimate p from the data. Keywords: Cupressus lusitanica; mixed effects modeling; Monte Carlo; tree taper. Southern Forests 2008, 70(3): 193–203 ...
Models for the formation of binary and millisecond radio pulsars
International Nuclear Information System (INIS)
van den Heuvel, E.P.J.
1984-01-01
The peculiar combination of a relatively short pulse period and a relatively weak surface dipole magnetic field strength of binary radio pulsars finds a consistent explanation in terms of: (i) decay of the surface dipole component of neutron star magnetic fields on a timescale of (2-5).10 6 yrs, in combination with: (ii) spin up of the rotation of the neutron star during a subsequent mass-transfer phase. The two observed classes of binary radio pulsars (very close and very wide systems, respectively) are expected to have been formed by the later evolution of binaries consisting of a neutron star and a normal companion star, in which the companion was (considerably) more massive than the neutron star, or less massive than the neutron star, respectively. In the first case the companion of the neutron star in the final system will be a fairly massive white dwarf, in a circular orbit, or a neutron star in an eccentric orbit. In the second case the final companion to the neutron star will be a low-mass (approx. 0.3 Msub solar) helium white dwarf in a wide and nearly circular orbit. In systems of the second type the neutron star was most probably formed by the accretion-induced collapse of a white dwarf. This explains why PSR 1953+29 has a millisecond rotation period and why PSR 0820+02 has not. Binary coalescence models for the formation of the 1.5 millisecond pulsar appear to be viable. The companion to the neutron star may have been a low-mass red dwarf, a neutron star, or a massive (> 0.7 Msub solar) white dwarf. In the red-dwarf case the progenitor system probably was a CV binary in which the white dwarf collapsed by accretion. 66 references, 6 figures, 1 table
The use of hyperspectral data for tree species discrimination: Combining binary classifiers
CSIR Research Space (South Africa)
Dastile, X
2010-11-01
Full Text Available ). A review on the combination of binary classifiers in multiclass problems. Springer science and Business Media B.V [7] Dietterich T.G and Bakiri G.(1995). Solving Multiclass Learning Problem via Error-Correcting Output Codes. AI Access Foundation...
Workflow Fault Tree Generation Through Model Checking
DEFF Research Database (Denmark)
Herbert, Luke Thomas; Sharp, Robin
2014-01-01
We present a framework for the automated generation of fault trees from models of realworld process workflows, expressed in a formalised subset of the popular Business Process Modelling and Notation (BPMN) language. To capture uncertainty and unreliability in workflows, we extend this formalism...... to calculate the probabilities of reaching each non-error system state. Each generated error state is assigned a variable indicating its individual probability of occurrence. Our method can determine the probability of combined faults occurring, while accounting for the basic probabilistic structure...... of the system being modelled. From these calculations, a comprehensive fault tree is generated. Further, we show that annotating the model with rewards (data) allows the expected mean values of reward structures to be calculated at points of failure....
Intermediate mass fragments emission in binary fragmentation model
International Nuclear Information System (INIS)
Bhattacharya, C.; Bhattacharya, S.
1991-01-01
Intermediate mass fragments emission in intermediate-energy nucleus-nucleus collisions has been studied in the framework of a generalized model where the fragments are assumed to be emitted from binary fissionlike decay of the fully equilibrated compound nucleus. The present formulation, with a schematic exit channel shape configuration and simple rotating liquid-drop nuclear potential, has been found to explain most of the intermediate mass fragments emission cross sections reasonably well without incorporating any free parameters in the calculation
Binary system parameters and the hibernation model of cataclysmic variables
International Nuclear Information System (INIS)
Livio, M.; Shara, M.M.; Space Telescope Science Institute, Baltimore, MD)
1987-01-01
The hibernation model, in which nova systems spend most of the time between eruptions in a state of low mass transfer rate, is examined. The binary systems more likely to undergo hibernation are determined. The predictions of the hibernation scenario are shown to be consistent with available observational data. It is shown how the hibernation scenario provides links between classical novae, dwarf novae, and novalike variables, all of which represent different stages in the cyclic evolution of the same systems. 72 references
Simple model of surface roughness for binary collision sputtering simulations
International Nuclear Information System (INIS)
Lindsey, Sloan J.; Hobler, Gerhard; Maciążek, Dawid; Postawa, Zbigniew
2017-01-01
Highlights: • A simple model of surface roughness is proposed. • Its key feature is a linearly varying target density at the surface. • The model can be used in 1D/2D/3D Monte Carlo binary collision simulations. • The model fits well experimental glancing incidence sputtering yield data. - Abstract: It has been shown that surface roughness can strongly influence the sputtering yield – especially at glancing incidence angles where the inclusion of surface roughness leads to an increase in sputtering yields. In this work, we propose a simple one-parameter model (the “density gradient model”) which imitates surface roughness effects. In the model, the target’s atomic density is assumed to vary linearly between the actual material density and zero. The layer width is the sole model parameter. The model has been implemented in the binary collision simulator IMSIL and has been evaluated against various geometric surface models for 5 keV Ga ions impinging an amorphous Si target. To aid the construction of a realistic rough surface topography, we have performed MD simulations of sequential 5 keV Ga impacts on an initially crystalline Si target. We show that our new model effectively reproduces the sputtering yield, with only minor variations in the energy and angular distributions of sputtered particles. The success of the density gradient model is attributed to a reduction of the reflection coefficient – leading to increased sputtering yields, similar in effect to surface roughness.
Luo, Jia; Zhang, Min; Zhou, Xiaoling; Chen, Jianhua; Tian, Yuxin
2018-01-01
Taken 4 main tree species in the Wuling mountain small watershed as research objects, 57 typical sample plots were set up according to the stand type, site conditions and community structure. 311 goal diameter-class sample trees were selected according to diameter-class groups of different tree-height grades, and the optimal fitting models of tree height and DBH growth of main tree species were obtained by stem analysis using Richard, Logistic, Korf, Mitscherlich, Schumacher, Weibull theoretical growth equations, and the correlation coefficient of all optimal fitting models reached above 0.9. Through the evaluation and test, the optimal fitting models possessed rather good fitting precision and forecast dependability.
Modeling binary correlated responses using SAS, SPSS and R
Wilson, Jeffrey R
2015-01-01
Statistical tools to analyze correlated binary data are spread out in the existing literature. This book makes these tools accessible to practitioners in a single volume. Chapters cover recently developed statistical tools and statistical packages that are tailored to analyzing correlated binary data. The authors showcase both traditional and new methods for application to health-related research. Data and computer programs will be publicly available in order for readers to replicate model development, but learning a new statistical language is not necessary with this book. The inclusion of code for R, SAS, and SPSS allows for easy implementation by readers. For readers interested in learning more about the languages, though, there are short tutorials in the appendix. Accompanying data sets are available for download through the book s website. Data analysis presented in each chapter will provide step-by-step instructions so these new methods can be readily applied to projects. Researchers and graduate stu...
General Model for Light Curves of Chromospherically Active Binary Stars
Jetsu, L.; Henry, G. W.; Lehtinen, J.
2017-04-01
The starspots on the surface of many chromospherically active binary stars concentrate on long-lived active longitudes separated by 180°. Shifts in activity between these two longitudes, the “flip-flop” events, have been observed in single stars like FK Comae and binary stars like σ Geminorum. Recently, interferometry has revealed that ellipticity may at least partly explain the flip-flop events in σ Geminorum. This idea was supported by the double-peaked shape of the long-term mean light curve of this star. Here we show that the long-term mean light curves of 14 chromospherically active binaries follow a general model that explains the connection between orbital motion, changes in starspot distribution, ellipticity, and flip-flop events. Surface differential rotation is probably weak in these stars, because the interference of two constant period waves may explain the observed light curve changes. These two constant periods are the active longitude period ({P}{act}) and the orbital period ({P}{orb}). We also show how to apply the same model to single stars, where only the value of P act is known. Finally, we present a tentative interference hypothesis about the origin of magnetic fields in all spectral types of stars. The CPS results are available electronically at the Vizier database.
Marginal and Random Intercepts Models for Longitudinal Binary Data with Examples from Criminology
Long, Jeffrey D.; Loeber, Rolf; Farrington, David P.
2009-01-01
Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides…
An extended topological model for binary phosphate glasses
DEFF Research Database (Denmark)
Hermansen, Christian; Rodrigues, B.P.; Wondraczek, L.
2014-01-01
We present a topological model for binary phosphate glasses that builds on the previously introduced concepts of the modifying ion sub-network and the strength of modifier constraints. The validity of the model is confirmed by the correct prediction of Tg(x) for covalent polyphosphoric acids where......, but for larger ions a significant fraction is broken. By accounting for the fraction of intact modifying ion related constraints, qγ, the Tg(x) of alkali phosphate glasses is predicted. By examining alkali, alkaline earth and rare earth metaphosphate glasses we find that the effective number of intact...
Hybrid approach for the assessment of PSA models by means of binary decision diagrams
Energy Technology Data Exchange (ETDEWEB)
Ibanez-Llano, Cristina, E-mail: cristina.ibanez@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain); Rauzy, Antoine, E-mail: Antoine.RAUZY@3ds.co [Dassault Systemes, 10 rue Marcel Dassault CS 40501, 78946 Velizy Villacoublay Cedex (France); Melendez, Enrique, E-mail: ema@csn.e [Consejo de Seguridad Nuclear (CSN), C/Justo Dorado 11, 28040 Madrid (Spain); Nieto, Francisco, E-mail: nieto@iit.upcomillas.e [Instituto de Investigacion Tecnologica (IIT), Escuela Tecnica Superior de Ingenieria ICAI, Universidad Pontificia Comillas, C/Santa Cruz de Marcenado 26, 28015 Madrid (Spain)
2010-10-15
Binary decision diagrams are a well-known alternative to the minimal cutsets approach to assess the reliability Boolean models. They have been applied successfully to improve the fault trees models assessment. However, its application to solve large models, and in particular the event trees coming from the PSA studies of the nuclear industry, remains to date out of reach of an exact evaluation. For many real PSA models it may be not possible to compute the BDD within reasonable amount of time and memory without considering the truncation or simplification of the model. This paper presents a new approach to estimate the exact probabilistic quantification results (probability/frequency) based on combining the calculation of the MCS and the truncation limits, with the BDD approach, in order to have a better control on the reduction of the model and to properly account for the success branches. The added value of this methodology is that it is possible to ensure a real confidence interval of the exact value and therefore an explicit knowledge of the error bound. Moreover, it can be used to measure the acceptability of the results obtained with traditional techniques. The new method was applied to a real life PSA study and the results obtained confirm the applicability of the methodology and open a new viewpoint for further developments.
Roeloffzen, C.G.H.; Horst, F.; Horst, F.; Offrein, B.J.; Offrein, B.J.; Germann, R.; Bona, G.L.; Salemink, H.W.M.; de Ridder, R.M.
2000-01-01
A tunable, flat-passband, 1-from-16 add/drop multiplexer for wavelength-division-multiplexing networks is presented. The device is realized in high-index-contrast silicon-oxynitride waveguide technology and is based on cascaded resonant coupler alters in the form of a mirrored binary tree.
Constructing Dynamic Event Trees from Markov Models
International Nuclear Information System (INIS)
Paolo Bucci; Jason Kirschenbaum; Tunc Aldemir; Curtis Smith; Ted Wood
2006-01-01
In the probabilistic risk assessment (PRA) of process plants, Markov models can be used to model accurately the complex dynamic interactions between plant physical process variables (e.g., temperature, pressure, etc.) and the instrumentation and control system that monitors and manages the process. One limitation of this approach that has prevented its use in nuclear power plant PRAs is the difficulty of integrating the results of a Markov analysis into an existing PRA. In this paper, we explore a new approach to the generation of failure scenarios and their compilation into dynamic event trees from a Markov model of the system. These event trees can be integrated into an existing PRA using software tools such as SAPHIRE. To implement our approach, we first construct a discrete-time Markov chain modeling the system of interest by: (a) partitioning the process variable state space into magnitude intervals (cells), (b) using analytical equations or a system simulator to determine the transition probabilities between the cells through the cell-to-cell mapping technique, and, (c) using given failure/repair data for all the components of interest. The Markov transition matrix thus generated can be thought of as a process model describing the stochastic dynamic behavior of the finite-state system. We can therefore search the state space starting from a set of initial states to explore all possible paths to failure (scenarios) with associated probabilities. We can also construct event trees of arbitrary depth by tracing paths from a chosen initiating event and recording the following events while keeping track of the probabilities associated with each branch in the tree. As an example of our approach, we use the simple level control system often used as benchmark in the literature with one process variable (liquid level in a tank), and three control units: a drain unit and two supply units. Each unit includes a separate level sensor to observe the liquid level in the tank
Multiset-based Tree Model for Membrane Computing
Directory of Open Access Journals (Sweden)
D. Singh
2011-06-01
Full Text Available In this paper, we introduce a new paradigm - multiset-based tree model. We show that trees can be represented in the form of wellfounded multisets. We also show that the conventional approach for this representation is not injective from a set of trees to the class of multisets representing such trees. We establish a one-to-one correspondence between trees and suitable permutations of a wellfounded multiset, which we call \\textit{tree structures}. We give formal definitions of a \\textit{tree structure} and a \\textit{subtree structure} of a tree structure. Finally, we represent membrane structures in the form of tree structures - a form in which membrane structures can suitably be represented at programming level.
Modeling adsorption of binary and ternary mixtures on microporous media
DEFF Research Database (Denmark)
Monsalvo, Matias Alfonso; Shapiro, Alexander
2007-01-01
The goal of this work is to analyze the adsorption of binary and ternary mixtures on the basis of the multicomponent potential theory of adsorption (MPTA). In the MPTA, the adsorbate is considered as a segregated mixture in the external potential field emitted by the solid adsorbent. This makes...... it possible using the same equation of state to describe the thermodynamic properties of the segregated and the bulk phases. For comparison, we also used the ideal adsorbed solution theory (IAST) to describe adsorption equilibria. The main advantage of these two models is their capabilities to predict...... multicomponent adsorption equilibria on the basis of single-component adsorption data. We compare the MPTA and IAST models to a large set of experimental data, obtaining reasonable good agreement with experimental data and high degree of predictability. Some limitations of both models are also discussed....
Pruning Chinese trees : an experimental and modelling approach
Zeng, Bo
2001-01-01
Pruning of trees, in which some branches are removed from the lower crown of a tree, has been extensively used in China in silvicultural management for many purposes. With an experimental and modelling approach, the effects of pruning on tree growth and on the harvest of plant material were studied.
Dynamic logistic regression and dynamic model averaging for binary classification.
McCormick, Tyler H; Raftery, Adrian E; Madigan, David; Burd, Randall S
2012-03-01
We propose an online binary classification procedure for cases when there is uncertainty about the model to use and parameters within a model change over time. We account for model uncertainty through dynamic model averaging, a dynamic extension of Bayesian model averaging in which posterior model probabilities may also change with time. We apply a state-space model to the parameters of each model and we allow the data-generating model to change over time according to a Markov chain. Calibrating a "forgetting" factor accommodates different levels of change in the data-generating mechanism. We propose an algorithm that adjusts the level of forgetting in an online fashion using the posterior predictive distribution, and so accommodates various levels of change at different times. We apply our method to data from children with appendicitis who receive either a traditional (open) appendectomy or a laparoscopic procedure. Factors associated with which children receive a particular type of procedure changed substantially over the 7 years of data collection, a feature that is not captured using standard regression modeling. Because our procedure can be implemented completely online, future data collection for similar studies would require storing sensitive patient information only temporarily, reducing the risk of a breach of confidentiality. © 2011, The International Biometric Society.
Phalla, Thuch; Ota, Tetsuji; Mizoue, Nobuya; Kajisa, Tsuyoshi; Yoshida, Shigejiro; Vuthy, Ma; Heng, Sokh
2018-01-01
This study evaluated the uncertainty of individual tree biomass estimated by allometric models by both including and excluding tree height independently. Using two independent sets of measurements on the same trees, the errors in the measurement of diameter at breast height and tree height were quantified, and the uncertainty of individual tree biomass estimation caused by errors in measurement was calculated. For both allometric models, the uncertainties of the individual tree biomass estima...
Shavit Grievink, Liat; Penny, David; Hendy, Michael D; Holland, Barbara R
2010-05-01
Commonly used phylogenetic models assume a homogeneous process through time in all parts of the tree. However, it is known that these models can be too simplistic as they do not account for nonhomogeneous lineage-specific properties. In particular, it is now widely recognized that as constraints on sequences evolve, the proportion and positions of variable sites can vary between lineages causing heterotachy. The extent to which this model misspecification affects tree reconstruction is still unknown. Here, we evaluate the effect of changes in the proportions and positions of variable sites on model fit and tree estimation. We consider 5 current models of nucleotide sequence evolution in a Bayesian Markov chain Monte Carlo framework as well as maximum parsimony (MP). We show that for a tree with 4 lineages where 2 nonsister taxa undergo a change in the proportion of variable sites tree reconstruction under the best-fitting model, which is chosen using a relative test, often results in the wrong tree. In this case, we found that an absolute test of model fit is a better predictor of tree estimation accuracy. We also found further evidence that MP is not immune to heterotachy. In addition, we show that increased sampling of taxa that have undergone a change in proportion and positions of variable sites is critical for accurate tree reconstruction.
Lubrication model for evaporation of binary sessile drops
Williams, Adam; Sáenz, Pedro; Karapetsas, George; Matar, Omar; Sefiane, Khellil; Valluri, Prashant
2017-11-01
Evaporation of a binary mixture sessile drop from a solid substrate is a highly dynamic and complex process with flow driven both thermal and solutal Marangoni stresses. Experiments on ethanol/water drops have identified chaotic regimes on both the surface and interior of the droplet, while mixture composition has also been seen to govern drop wettability. Using a lubrication-type approach, we present a finite element model for the evaporation of an axisymmetric binary drop deposited on a heated substrate. We consider a thin drop with a moving contact line, taking also into account the commonly ignored effects of inertia which drives interfacial instability. We derive evolution equations for the film height, the temperature and the concentration field considering that the mixture comprises two ideally mixed volatile components with a surface tension linearly dependent on both temperature and concentration. The properties of the mixture such as viscosity also vary locally with concentration. We explore the parameter space to examine the resultant effects on wetting and evaporation where we find qualitative agreement with experiments in both these areas. This enables us to understand the nature of the instabilities that spontaneously emerge over the drop lifetime. EPSRC - EP/K00963X/1.
Simple model of surface roughness for binary collision sputtering simulations
Lindsey, Sloan J.; Hobler, Gerhard; Maciążek, Dawid; Postawa, Zbigniew
2017-02-01
It has been shown that surface roughness can strongly influence the sputtering yield - especially at glancing incidence angles where the inclusion of surface roughness leads to an increase in sputtering yields. In this work, we propose a simple one-parameter model (the "density gradient model") which imitates surface roughness effects. In the model, the target's atomic density is assumed to vary linearly between the actual material density and zero. The layer width is the sole model parameter. The model has been implemented in the binary collision simulator IMSIL and has been evaluated against various geometric surface models for 5 keV Ga ions impinging an amorphous Si target. To aid the construction of a realistic rough surface topography, we have performed MD simulations of sequential 5 keV Ga impacts on an initially crystalline Si target. We show that our new model effectively reproduces the sputtering yield, with only minor variations in the energy and angular distributions of sputtered particles. The success of the density gradient model is attributed to a reduction of the reflection coefficient - leading to increased sputtering yields, similar in effect to surface roughness.
Growth models for tree stems and vines
Bressan, Alberto; Palladino, Michele; Shen, Wen
2017-08-01
The paper introduces a PDE model for the growth of a tree stem or a vine. The equations describe the elongation due to cell growth, and the response to gravity and to external obstacles. An additional term accounts for the tendency of a vine to curl around branches of other plants. When obstacles are present, the model takes the form of a differential inclusion with state constraints. At each time t, a cone of admissible reactions is determined by the minimization of an elastic deformation energy. The main theorem shows that local solutions exist and can be prolonged globally in time, except when a specific ;breakdown configuration; is reached. Approximate solutions are constructed by an operator-splitting technique. Some numerical simulations are provided at the end of the paper.
Hellmuth, Marc; Stadler, Peter F; Wieseke, Nicolas
2017-07-01
The concepts of orthology, paralogy, and xenology play a key role in molecular evolution. Orthology and paralogy distinguish whether a pair of genes originated by speciation or duplication. The corresponding binary relations on a set of genes form complementary cographs. Allowing more than two types of ancestral event types leads to symmetric symbolic ultrametrics. Horizontal gene transfer, which leads to xenologous gene pairs, however, is inherent asymmetric since one offspring copy "jumps" into another genome, while the other continues to be inherited vertically. We therefore explore here the mathematical structure of the non-symmetric generalization of symbolic ultrametrics. Our main results tie non-symmetric ultrametrics together with di-cographs (the directed generalization of cographs), so-called uniformly non-prime ([Formula: see text]) 2-structures, and hierarchical structures on the set of strong modules. This yields a characterization of relation structures that can be explained in terms of trees and types of ancestral events. This framework accommodates a horizontal-transfer relation in terms of an ancestral event and thus, is slightly different from the the most commonly used definition of xenology. As a first step towards a practical use, we present a simple polynomial-time recognition algorithm of [Formula: see text] 2-structures and investigate the computational complexity of several types of editing problems for [Formula: see text] 2-structures. We show, finally that these NP-complete problems can be solved exactly as Integer Linear Programs.
A spatial model of tree α-diversity and tree density for the Amazon
ter Steege, H.; Pitman, N.C.A.; Sabatier, D.; Castellanos, H.; van der Hout, P.; Daly, D.C.; Silveira, M.; Phillips, O.; Vasquez, R.; van Andel, T.; Duivenvoorden, J.; de Oliveira, A.A.; Ek, R.; Lilwah, R.; Thomas, R.; van Essen, J.; Baider, C.; Maas, P.; Mori, S.; Terborgh, J.; Nuñez-Vargas, P.; Mogollón, H.; Morawetz, W.
2003-01-01
Large-scale patterns of Amazonian biodiversity have until now been obscured by a sparse and scattered inventory record. Here we present the first comprehensive spatial model of tree α-diversity and tree density in Amazonian rainforests, based on the largest-yet compilation of forest inventories and
Inferring gene regression networks with model trees
Directory of Open Access Journals (Sweden)
Aguilar-Ruiz Jesus S
2010-10-01
Full Text Available Abstract Background Novel strategies are required in order to handle the huge amount of data produced by microarray technologies. To infer gene regulatory networks, the first step is to find direct regulatory relationships between genes building the so-called gene co-expression networks. They are typically generated using correlation statistics as pairwise similarity measures. Correlation-based methods are very useful in order to determine whether two genes have a strong global similarity but do not detect local similarities. Results We propose model trees as a method to identify gene interaction networks. While correlation-based methods analyze each pair of genes, in our approach we generate a single regression tree for each gene from the remaining genes. Finally, a graph from all the relationships among output and input genes is built taking into account whether the pair of genes is statistically significant. For this reason we apply a statistical procedure to control the false discovery rate. The performance of our approach, named REGNET, is experimentally tested on two well-known data sets: Saccharomyces Cerevisiae and E.coli data set. First, the biological coherence of the results are tested. Second the E.coli transcriptional network (in the Regulon database is used as control to compare the results to that of a correlation-based method. This experiment shows that REGNET performs more accurately at detecting true gene associations than the Pearson and Spearman zeroth and first-order correlation-based methods. Conclusions REGNET generates gene association networks from gene expression data, and differs from correlation-based methods in that the relationship between one gene and others is calculated simultaneously. Model trees are very useful techniques to estimate the numerical values for the target genes by linear regression functions. They are very often more precise than linear regression models because they can add just different linear
Testing stellar evolution models with detached eclipsing binaries
Higl, J.; Weiss, A.
2017-12-01
Stellar evolution codes, as all other numerical tools, need to be verified. One of the standard stellar objects that allow stringent tests of stellar evolution theory and models, are detached eclipsing binaries. We have used 19 such objects to test our stellar evolution code, in order to see whether standard methods and assumptions suffice to reproduce the observed global properties. In this paper we concentrate on three effects that contain a specific uncertainty: atomic diffusion as used for standard solar model calculations, overshooting from convective regions, and a simple model for the effect of stellar spots on stellar radius, which is one of the possible solutions for the radius problem of M dwarfs. We find that in general old systems need diffusion to allow for, or at least improve, an acceptable fit, and that systems with convective cores indeed need overshooting. Only one system (AI Phe) requires the absence of it for a successful fit. To match stellar radii for very low-mass stars, the spot model proved to be an effective approach, but depending on model details, requires a high percentage of the surface being covered by spots. We briefly discuss improvements needed to further reduce the freedom in modelling and to allow an even more restrictive test by using these objects.
Energy Technology Data Exchange (ETDEWEB)
Nusbaumer, O. P. M
2007-07-01
This study is concerned with the quantification of Probabilistic Risk Assessment (PRA) using linked Fault Tree (FT) models. Probabilistic Risk assessment (PRA) of Nuclear Power Plants (NPPs) complements traditional deterministic analysis; it is widely recognized as a comprehensive and structured approach to identify accident scenarios and to derive numerical estimates of the associated risk levels. PRA models as found in the nuclear industry have evolved rapidly. Increasingly, they have been broadly applied to support numerous applications on various operational and regulatory matters. Regulatory bodies in many countries require that a PRA be performed for licensing purposes. PRA has reached the point where it can considerably influence the design and operation of nuclear power plants. However, most of the tools available for quantifying large PRA models are unable to produce analytically correct results. The algorithms of such quantifiers are designed to neglect sequences when their likelihood decreases below a predefined cutoff limit. In addition, the rare event approximation (e.g. Moivre's equation) is typically implemented for the first order, ignoring the success paths and the possibility that two or more events can occur simultaneously. This is only justified in assessments where the probabilities of the basic events are low. When the events in question are failures, the first order rare event approximation is always conservative, resulting in wrong interpretation of risk importance measures. Advanced NPP PRA models typically include human errors, common cause failure groups, seismic and phenomenological basic events, where the failure probabilities may approach unity, leading to questionable results. It is accepted that current quantification tools have reached their limits, and that new quantification techniques should be investigated. A novel approach using the mathematical concept of Binary Decision Diagram (BDD) is proposed to overcome these
Progenitor models of Wolf-Rayet+O binary systems
Petrovic, J.; Langer, N.
2007-01-01
Since close WR+O binaries are the result of a strong interaction of both stars in massive close binary systems, they can be used to constrain the highly uncertain mass and angular momentum budget during the major mass- transfer phase. We explore the progenitor evolution of the three best suited WR+O
Simple Prediction of Type 2 Diabetes Mellitus via Decision Tree Modeling
Directory of Open Access Journals (Sweden)
Mehrab Sayadi
2017-06-01
Full Text Available Background: Type 2 Diabetes Mellitus (T2DM is one of the most important risk factors in cardiovascular disorders considered as a common clinical and public health problem. Early diagnosis can reduce the burden of the disease. Decision tree, as an advanced data mining method, can be used as a reliable tool to predict T2DM. Objectives: This study aimed to present a simple model for predicting T2DM using decision tree modeling. Materials and Methods: This analytical model-based study used a part of the cohort data obtained from a database in Healthy Heart House of Shiraz, Iran. The data included routine information, such as age, gender, Body Mass Index (BMI, family history of diabetes, and systolic and diastolic blood pressure, which were obtained from the individuals referred for gathering baseline data in Shiraz cohort study from 2014 to 2015. Diabetes diagnosis was used as binary datum. Decision tree technique and J48 algorithm were applied using the WEKA software (version 3.7.5, New Zealand. Additionally, Receiver Operator Characteristic (ROC curve and Area Under Curve (AUC were used for checking the goodness of fit. Results: The age of the 11302 cases obtained after data preparation ranged from 18 to 89 years with the mean age of 48.1 ± 11.4 years. Additionally, 51.1% of the cases were male. In the tree structure, blood pressure and age were placed where most information was gained. In our model, however, gender was not important and was placed on the final branch of the tree. Total precision and AUC were 87% and 89%, respectively. This indicated that the model had good accuracy for distinguishing patients from normal individuals. Conclusions: The results showed that T2DM could be predicted via decision tree model without laboratory tests. Thus, this model can be used in pre-clinical and public health screening programs.
Computational model of a whole tree combustor
Energy Technology Data Exchange (ETDEWEB)
Bryden, K.M.; Ragland, K.W. [Univ. of Wisconsin, Madison, WI (United States)
1993-12-31
A preliminary computational model has been developed for the whole tree combustor and compared to test results. In the simulation model presented hardwood logs, 15 cm in diameter are burned in a 4 m deep fuel bed. Solid and gas temperature, solid and gas velocity, CO, CO{sub 2}, H{sub 2}O, HC and O{sub 2} profiles are calculated. This deep, fixed bed combustor obtains high energy release rates per unit area due to the high inlet air velocity and extended reaction zone. The lowest portion of the overall bed is an oxidizing region and the remainder of the bed acts as a gasification and drying region. The overfire air region completes the combustion. Approximately 40% of the energy is released in the lower oxidizing region. The wood consumption rate obtained from the computational model is 4,110 kg/m{sup 2}-hr which matches well the consumption rate of 3,770 kg/m{sup 2}-hr observed during the peak test period of the Aurora, MN test. The predicted heat release rate is 16 MW/m{sup 2} (5.0*10{sup 6} Btu/hr-ft{sup 2}).
Modeling Caribbean tree stem diameters from tree height and crown width measurements
Thomas Brandeis; KaDonna Randolph; Mike Strub
2009-01-01
Regression models to predict diameter at breast height (DBH) as a function of tree height and maximum crown radius were developed for Caribbean forests based on data collected by the U.S. Forest Service in the Commonwealth of Puerto Rico and Territory of the U.S. Virgin Islands. The model predicting DBH from tree height fit reasonably well (R2 = 0.7110), with...
Modelling diameter growth, mortality and recruitment of trees in ...
African Journals Online (AJOL)
Miombo woodlands cover large areas in Tanzania but very little reliable data on forest dynamics for the woodlands exist. The main objective of this study was to develop a model system describing such dynamics based on easily measurable tree variables. Individual tree diameter growth and mortality models, and ...
Total tree, merchantable stem and branch volume models for ...
African Journals Online (AJOL)
Total tree, merchantable stem and branch volume models for miombo woodlands of Malawi. Daud J Kachamba, Tron Eid. Abstract. The objective of this study was to develop general (multispecies) models for prediction of total tree, merchantable stem and branch volume including options with diameter at breast height (dbh) ...
Jeng, Albert; Chang, Li-Chung; Chen, Sheng-Hui
There are many protocols proposed for protecting Radio Frequency Identification (RFID) system privacy and security. A number of these protocols are designed for protecting long-term security of RFID system using symmetric key or public key cryptosystem. Others are designed for protecting user anonymity and privacy. In practice, the use of RFID technology often has a short lifespan, such as commodity check out, supply chain management and so on. Furthermore, we know that designing a long-term security architecture to protect the security and privacy of RFID tags information requires a thorough consideration from many different aspects. However, any security enhancement on RFID technology will jack up its cost which may be detrimental to its widespread deployment. Due to the severe constraints of RFID tag resources (e. g., power source, computing power, communication bandwidth) and open air communication nature of RFID usage, it is a great challenge to secure a typical RFID system. For example, computational heavy public key and symmetric key cryptography algorithms (e. g., RSA and AES) may not be suitable or over-killed to protect RFID security or privacy. These factors motivate us to research an efficient and cost effective solution for RFID security and privacy protection. In this paper, we propose a new effective generic binary tree based key agreement protocol (called BKAP) and its variations, and show how it can be applied to secure the low cost and resource constraint RFID system. This BKAP is not a general purpose key agreement protocol rather it is a special purpose protocol to protect privacy, un-traceability and anonymity in a single RFID closed system domain.
Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification
Directory of Open Access Journals (Sweden)
Yidong Tang
2016-01-01
Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.
Unobserved Heterogeneity in the Binary Logit Model with Cross-Sectional Data and Short Panels
DEFF Research Database (Denmark)
Holm, Anders; Jæger, Mads Meier; Pedersen, Morten
This paper proposes a new approach to dealing with unobserved heterogeneity in applied research using the binary logit model with cross-sectional data and short panels. Unobserved heterogeneity is particularly important in non-linear regression models such as the binary logit model because, unlike...... in linear regression models, estimates of the effects of observed independent variables are biased even when omitted independent variables are uncorrelated with the observed independent variables. We propose an extension of the binary logit model based on a finite mixture approach in which we conceptualize...
Impacts of Tree Height-Dbh Allometry on Lidar-Based Tree Aboveground Biomass Modeling
Fang, R.
2016-06-01
Lidar has been widely used in tree aboveground biomass (AGB) estimation at plot or stand levels. Lidar-based AGB models are usually constructed with the ground AGB reference as the response variable and lidar canopy indices as predictor variables. Tree diameter at breast height (dbh) is the major variable of most allometric models for estimating reference AGB. However, lidar measurements are mainly related to tree vertical structure. Therefore, tree height-dbh allometric model residuals are expected to have a large impact on lidar-based AGB model performance. This study attempts to investigate sensitivity of lidar-based AGB model to the decreasing strength of height-dbh relationship using a Monte Carlo simulation approach. Striking decrease in R2 and increase in relative RMSE were found in lidar-based AGB model, as the variance of height-dbh model residuals grew. I, therefore, concluded that individual tree height-dbh model residuals fundamentally introduce errors to lidar-AGB models.
Modeling and analysis of periodic orbits around a contact binary asteroid
Feng, J.; Noomen, R.; Visser, P.N.A.M.; Yuan, J.
2015-01-01
The existence and characteristics of periodic orbits (POs) in the vicinity of a contact binary asteroid are investigated with an averaged spherical harmonics model. A contact binary asteroid consists of two components connected to each other, resulting in a highly bifurcated shape. Here, it is
Radar Shape Modeling of Binary Near-Earth Asteroid 2000 CO101
Jimenez, Nicholas; Howell, E. S.; Nolan, M. C.; Taylor, P. A.; Benner, L. A. M.; Brozovic, M.; Giorgini, J. D.; Vervack, R. J.; Fernandez, Y. R.; Mueller, M.; Margot, J.; Shepard, M. K.
2010-01-01
We observed the near-Earth binary system 2000 CO101 in 2009 Septemberusing the Goldstone and Arecibo radar systems and inverted these imagesto create shape models of the primary. Asteroid 2000 CO101 wasdiscovered to be a binary system from Arecibo images taken on 2009September 26 (Taylor et al.
A discussion of calibration techniques for evaluating binary and categorical predictive models.
Fenlon, Caroline; O'Grady, Luke; Doherty, Michael L; Dunnion, John
2018-01-01
Modelling of binary and categorical events is a commonly used tool to simulate epidemiological processes in veterinary research. Logistic and multinomial regression, naïve Bayes, decision trees and support vector machines are popular data mining techniques used to predict the probabilities of events with two or more outcomes. Thorough evaluation of a predictive model is important to validate its ability for use in decision-support or broader simulation modelling. Measures of discrimination, such as sensitivity, specificity and receiver operating characteristics, are commonly used to evaluate how well the model can distinguish between the possible outcomes. However, these discrimination tests cannot confirm that the predicted probabilities are accurate and without bias. This paper describes a range of calibration tests, which typically measure the accuracy of predicted probabilities by comparing them to mean event occurrence rates within groups of similar test records. These include overall goodness-of-fit statistics in the form of the Hosmer-Lemeshow and Brier tests. Visual assessment of prediction accuracy is carried out using plots of calibration and deviance (the difference between the outcome and its predicted probability). The slope and intercept of the calibration plot are compared to the perfect diagonal using the unreliability test. Mean absolute calibration error provides an estimate of the level of predictive error. This paper uses sample predictions from a binary logistic regression model to illustrate the use of calibration techniques. Code is provided to perform the tests in the R statistical programming language. The benefits and disadvantages of each test are described. Discrimination tests are useful for establishing a model's diagnostic abilities, but may not suitably assess the model's usefulness for other predictive applications, such as stochastic simulation. Calibration tests may be more informative than discrimination tests for evaluating
Developing Models to Forcast Sales of Natural Christmas Trees
Lawrence D. Garrett; Thomas H. Pendleton
1977-01-01
A study of practices for marketing Christmas trees in Winston-Salem, North Carolina, and Denver, Colorado, revealed that such factors as retail lot competition, tree price, consumer traffic, and consumer income were very important in determining a particular retailer's sales. Analyses of 4 years of market data were used in developing regression models for...
Massive-scale tree modelling from TLS data
Raumonen, P.; Casella, E.; Calders, K.; Murphy, S.; Åkerblom, M.; Kaasalainen, M.
2015-01-01
This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak
A discrete element modelling approach for block impacts on trees
Toe, David; Bourrier, Franck; Olmedo, Ignatio; Berger, Frederic
2015-04-01
These past few year rockfall models explicitly accounting for block shape, especially those using the Discrete Element Method (DEM), have shown a good ability to predict rockfall trajectories. Integrating forest effects into those models still remain challenging. This study aims at using a DEM approach to model impacts of blocks on trees and identify the key parameters controlling the block kinematics after the impact on a tree. A DEM impact model of a block on a tree was developed and validated using laboratory experiments. Then, key parameters were assessed using a global sensitivity analyse. Modelling the impact of a block on a tree using DEM allows taking into account large displacements, material non-linearities and contacts between the block and the tree. Tree stems are represented by flexible cylinders model as plastic beams sustaining normal, shearing, bending, and twisting loading. Root soil interactions are modelled using a rotation stiffness acting on the bending moment at the bottom of the tree and a limit bending moment to account for tree overturning. The crown is taken into account using an additional mass distribute uniformly on the upper part of the tree. The block is represented by a sphere. The contact model between the block and the stem consists of an elastic frictional model. The DEM model was validated using laboratory impact tests carried out on 41 fresh beech (Fagus Sylvatica) stems. Each stem was 1,3 m long with a diameter between 3 to 7 cm. Wood stems were clamped on a rigid structure and impacted by a 149 kg charpy pendulum. Finally an intensive simulation campaign of blocks impacting trees was done to identify the input parameters controlling the block kinematics after the impact on a tree. 20 input parameters were considered in the DEM simulation model : 12 parameters were related to the tree and 8 parameters to the block. The results highlight that the impact velocity, the stem diameter, and the block volume are the three input
Preliminary Modeling of the Eclipsing Binary Star GSC 05765-01271
Marullo, S.; Marchini, A.; Franco, L.; Papini, R.; Salvaggio, F.
2017-12-01
The authors discovered the eclipsing binary star system GSC 05765-01271 on August 19, 2015; here a preliminary model is presented. Lacking spectroscopic radial velocity data, period-based empirical relations have been used in order to constrain physical parameters as masses and radii. The effective temperature has been evaluated using color index (V-R) and spectral type estimated from a composite spectrum. These parameters were used as input to obtain a preliminary model of this binary system with Binary Maker 3 and PHOEBE software.
Modeling AGN outbursts from supermassive black hole binaries
Directory of Open Access Journals (Sweden)
Tanaka T.
2012-12-01
Full Text Available When galaxies merge to assemble more massive galaxies, their nuclear supermassive black holes (SMBHs should form bound binaries. As these interact with their stellar and gaseous environments, they will become increasingly compact, culminating in inspiral and coalescence through the emission of gravitational radiation. Because galaxy mergers and interactions are also thought to fuel star formation and nuclear black hole activity, it is plausible that such binaries would lie in gas-rich environments and power active galactic nuclei (AGN. The primary difference is that these binaries have gravitational potentials that vary – through their orbital motion as well as their orbital evolution – on humanly tractable timescales, and are thus excellent candidates to give rise to coherent AGN variability in the form of outbursts and recurrent transients. Although such electromagnetic signatures would be ideally observed concomitantly with the binary’s gravitational-wave signatures, they are also likely to be discovered serendipitously in wide-field, high-cadence surveys; some may even be confused for stellar tidal disruption events. I discuss several types of possible “smoking gun” AGN signatures caused by the peculiar geometry predicted for accretion disks around SMBH binaries.
A binary logistic regression model with complex sampling design of ...
African Journals Online (AJOL)
2017-09-03
Sep 3, 2017 ... SPSS-21. Binary logistic regression with complex sam- pling design was fitted for the unmet need outcomes. Married women are disaggregated by various background characteristics to have an insight of their characteristics. All background characteristics of women used in this study were categorical ...
Maximum parsimony, substitution model, and probability phylogenetic trees.
Weng, J F; Thomas, D A; Mareels, I
2011-01-01
The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.
Directory of Open Access Journals (Sweden)
YU Jintao
2016-09-01
Full Text Available After the characteristics of geodesic active contour model (GAC, Chan-Vese model(CV and local binary fitting model(LBF are analyzed, and the active contour model based on regions and edges is combined with image segmentation method based on quad-tree, a waterline extraction method based on quad-tree and multiple active contour model is proposed in this paper. Firstly, the method provides an initial contour according to quad-tree segmentation. Secondly, a new signed pressure force(SPF function based on global image statistics information of CV model and local image statistics information of LBF model has been defined, and then ,the edge stopping function(ESF is replaced by the proposed SPF function, which solves the problem such as evolution stopped in advance and excessive evolution. Finally, the selective binary and Gaussian filtering level set method is used to avoid reinitializing and regularization to improve the evolution efficiency. The experimental results show that this method can effectively extract the weak edges and serious concave edges, and owns some properties such as sub-pixel accuracy, high efficiency and reliability for waterline extraction.
Challenges in Species Tree Estimation Under the Multispecies Coalescent Model.
Xu, Bo; Yang, Ziheng
2016-12-01
The multispecies coalescent (MSC) model has emerged as a powerful framework for inferring species phylogenies while accounting for ancestral polymorphism and gene tree-species tree conflict. A number of methods have been developed in the past few years to estimate the species tree under the MSC. The full likelihood methods (including maximum likelihood and Bayesian inference) average over the unknown gene trees and accommodate their uncertainties properly but involve intensive computation. The approximate or summary coalescent methods are computationally fast and are applicable to genomic datasets with thousands of loci, but do not make an efficient use of information in the multilocus data. Most of them take the two-step approach of reconstructing the gene trees for multiple loci by phylogenetic methods and then treating the estimated gene trees as observed data, without accounting for their uncertainties appropriately. In this article we review the statistical nature of the species tree estimation problem under the MSC, and explore the conceptual issues and challenges of species tree estimation by focusing mainly on simple cases of three or four closely related species. We use mathematical analysis and computer simulation to demonstrate that large differences in statistical performance may exist between the two classes of methods. We illustrate that several counterintuitive behaviors may occur with the summary methods but they are due to inefficient use of information in the data by summary methods and vanish when the data are analyzed using full-likelihood methods. These include (i) unidentifiability of parameters in the model, (ii) inconsistency in the so-called anomaly zone, (iii) singularity on the likelihood surface, and (iv) deterioration of performance upon addition of more data. We discuss the challenges and strategies of species tree inference for distantly related species when the molecular clock is violated, and highlight the need for improving the
Context Tree Estimation in Variable Length Hidden Markov Models
Dumont, Thierry
2011-01-01
We address the issue of context tree estimation in variable length hidden Markov models. We propose an estimator of the context tree of the hidden Markov process which needs no prior upper bound on the depth of the context tree. We prove that the estimator is strongly consistent. This uses information-theoretic mixture inequalities in the spirit of Finesso and Lorenzo(Consistent estimation of the order for Markov and hidden Markov chains(1990)) and E.Gassiat and S.Boucheron (Optimal error exp...
Modeling and Testing Landslide Hazard Using Decision Tree
Directory of Open Access Journals (Sweden)
Mutasem Sh. Alkhasawneh
2014-01-01
Full Text Available This paper proposes a decision tree model for specifying the importance of 21 factors causing the landslides in a wide area of Penang Island, Malaysia. These factors are vegetation cover, distance from the fault line, slope angle, cross curvature, slope aspect, distance from road, geology, diagonal length, longitude curvature, rugosity, plan curvature, elevation, rain perception, soil texture, surface area, distance from drainage, roughness, land cover, general curvature, tangent curvature, and profile curvature. Decision tree models are used for prediction, classification, and factors importance and are usually represented by an easy to interpret tree like structure. Four models were created using Chi-square Automatic Interaction Detector (CHAID, Exhaustive CHAID, Classification and Regression Tree (CRT, and Quick-Unbiased-Efficient Statistical Tree (QUEST. Twenty-one factors were extracted using digital elevation models (DEMs and then used as input variables for the models. A data set of 137570 samples was selected for each variable in the analysis, where 68786 samples represent landslides and 68786 samples represent no landslides. 10-fold cross-validation was employed for testing the models. The highest accuracy was achieved using Exhaustive CHAID (82.0% compared to CHAID (81.9%, CRT (75.6%, and QUEST (74.0% model. Across the four models, five factors were identified as most important factors which are slope angle, distance from drainage, surface area, slope aspect, and cross curvature.
International Nuclear Information System (INIS)
Babak, S; Balasubramanian, R; Churches, D; Cokelaer, T; Sathyaprakash, B S
2006-01-01
Gravitational waves from coalescing compact binaries are searched for using the matched filtering technique. As the model waveform depends on a number of parameters, it is necessary to filter the data through a template bank covering the astrophysically interesting region of the parameter space. The choice of templates is defined by the maximum allowed drop in signal-to-noise ratio due to the discreteness of the template bank. In this paper we describe the template-bank algorithm that was used in the analysis of data from the Laser Interferometer Gravitational Wave Observatory (LIGO) and GEO 600 detectors to search for signals from binaries consisting of non-spinning compact objects. Using Monte Carlo simulations, we study the efficiency of the bank and show that its performance is satisfactory for the design sensitivity curves of ground-based interferometric gravitational wave detectors GEO 600, initial LIGO, advanced LIGO and Virgo. The bank is efficient in searching for various compact binaries such as binary primordial black holes, binary neutron stars, binary black holes, as well as a mixed binary consisting of a non-spinning black hole and a neutron star
Processing tree point clouds using Gaussian Mixture Models
Directory of Open Access Journals (Sweden)
D. Belton
2013-10-01
Full Text Available While traditionally used for surveying and photogrammetric fields, laser scanning is increasingly being used for a wider range of more general applications. In addition to the issues typically associated with processing point data, such applications raise a number of new complications, such as the complexity of the scenes scanned, along with the sheer volume of data. Consequently, automated procedures are required for processing, and analysing such data. This paper introduces a method for modelling multi-modal, geometrically complex objects in terrestrial laser scanning point data; specifically, the modelling of trees. The model method comprises a number of geometric features in conjunction with a multi-modal machine learning technique. The model can then be used for contextually dependent region growing through separating the tree into its component part at the point level. Subsequently object analysis can be performed, for example, performing volumetric analysis of a tree by removing points associated with leaves. The workflow for this process is as follows: isolate individual trees within the scanned scene, train a Gaussian mixture model (GMM, separate clusters within the mixture model according to exemplar points determined by the GMM, grow the structure of the tree, and then perform volumetric analysis on the structure.
International Nuclear Information System (INIS)
Fang Zheng; Zhang Quanru
2006-01-01
A model has been derived to predict thermodynamic properties of ternary metallic systems from those of its three binaries. In the model, the excess Gibbs free energies and the interaction parameter ω 123 for three components of a ternary are expressed as a simple sum of those of the three sub-binaries, and the mole fractions of the components of the ternary are identical with the sub-binaries. This model is greatly simplified compared with the current symmetrical and asymmetrical models. It is able to overcome some shortcomings of the current models, such as the arrangement of the components in the Gibbs triangle, the conversion of mole fractions between ternary and corresponding binaries, and some necessary processes for optimizing the various parameters of these models. Two ternary systems, Mg-Cu-Ni and Cd-Bi-Pb are recalculated to demonstrate the validity and precision of the present model. The calculated results on the Mg-Cu-Ni system are better than those in the literature. New parameters in the Margules equations expressing the excess Gibbs free energies of three binary systems of the Cd-Bi-Pb ternary system are also given
Biomass models to estimate carbon stocks for hardwood tree species
Energy Technology Data Exchange (ETDEWEB)
Ruiz-Peinado, R.; Montero, G.; Rio, M. del
2012-11-01
To estimate forest carbon pools from forest inventories it is necessary to have biomass models or biomass expansion factors. In this study, tree biomass models were developed for the main hardwood forest species in Spain: Alnus glutinosa, Castanea sativa, Ceratonia siliqua, Eucalyptus globulus, Fagus sylvatica, Fraxinus angustifolia, Olea europaea var. sylvestris, Populus x euramericana, Quercus canariensis, Quercus faginea, Quercus ilex, Quercus pyrenaica and Quercus suber. Different tree biomass components were considered: stem with bark, branches of different sizes, above and belowground biomass. For each species, a system of equations was fitted using seemingly unrelated regression, fulfilling the additivity property between biomass components. Diameter and total height were explored as independent variables. All models included tree diameter whereas for the majority of species, total height was only considered in the stem biomass models and in some of the branch models. The comparison of the new biomass models with previous models fitted separately for each tree component indicated an improvement in the accuracy of the models. A mean reduction of 20% in the root mean square error and a mean increase in the model efficiency of 7% in comparison with recently published models. So, the fitted models allow estimating more accurately the biomass stock in hardwood species from the Spanish National Forest Inventory data. (Author) 45 refs.
(Liquid plus liquid) equilibria of binary polymer solutions using a free-volume UNIQUAC-NRF model
DEFF Research Database (Denmark)
Radfarnia, H.R.; Ghotbi, C.; Taghikhani, V.
2006-01-01
+ liquid) equilibria (LLE) for a number of binary polymer solutions at various temperatures. The values for the binary characteristic energy parameters for the proposed model and the FV-UNIQUAC model along with their average relative deviations from the experimental data were reported. It should be stated...... that the binary polymer solutions studied in this work were considered as monodisperse. The results obtained from the FV-UNIQUAC-NRF model were compared with those obtained from the FV-UNIQUAC model. The results of the proposed model show that the FV-UNIQUAC-NRF model can accurately correlate the experimental...... in predicting the LCST for binary polymer solutions....
Fruit tree model for uptake of organic compounds from soil
DEFF Research Database (Denmark)
Trapp, Stefan; Rasmussen, D.; Samsoe-Petersen, L.
2003-01-01
rences: 20 [ view related records ] Citation Map Abstract: Apples and other fruits are frequently cultivated in gardens and are part of our daily diet. Uptake of pollutants into apples may therefore contribute to the human daily intake of toxic substances. In current risk assessment of polluted...... soils, regressions or models are in use, which were not intended to be used for tree fruits. A simple model for uptake of neutral organic contaminants into fruits is developed. It considers xylem and phloem transport to fruits through the stem. The mass balance is solved for the steady......-state, and an example calculation is given. The Fruit Tree Model is compared to the empirical equation of Travis and Arms (T&A), and to results from fruits, collected in contaminated areas. For polar compounds, both T&A and the Fruit Tree Model predict bioconcentration factors fruit to soil (BCF, wet weight based...
Massive-Scale Tree Modelling from Tls Data
Raumonen, P.; Casella, E.; Calders, K.; Murphy, S.; Åkerbloma, , M.; Kaasalainen, M.
2015-03-01
This paper presents a method for reconstructing automatically the quantitative structure model of every tree in a forest plot from terrestrial laser scanner data. A new feature is the automatic extraction of individual trees from the point cloud. The method is tested with a 30-m diameter English oak plot and a 80-m diameter Australian eucalyptus plot. For the oak plot the total biomass was overestimated by about 17 %, when compared to allometry (N = 15), and the modelling time was about 100 min with a laptop. For the eucalyptus plot the total biomass was overestimated by about 8.5 %, when compared to a destructive reference (N = 27), and the modelling time was about 160 min. The method provides accurate and fast tree modelling abilities for, e.g., biomass estimation and ground truth data for airborne measurements at a massive ground scale.
Photometric Analysis and Modeling of Five Mass-Transferring Binary Systems
Geist, Emily; Beaky, Matthew; Jamison, Kate
2018-01-01
In overcontact eclipsing binary systems, both stellar components have overfilled their Roche lobes, resulting in a dumbbell-shaped shared envelope. Mass transfer is common in overcontact binaries, which can be observed as a slow change on the rotation period of the system.We studied five overcontact eclipsing binary systems with evidence of period change, and thus likely mass transfer between the components, identified by Nelson (2014): V0579 Lyr, KN Vul, V0406 Lyr, V2240 Cyg, and MS Her. We used the 31-inch NURO telescope at Lowell Observatory in Flagstaff, Arizona to obtain images in B,V,R, and I filters for V0579 Lyr, and the 16-inch Meade LX200GPS telescope with attached SBIG ST-8XME CCD camera at Juniata College in Huntingdon, Pennsylvania to image KN Vul, V0406 Lyr, V2240 Cyg, and MS Her, also in B,V,R, and I.After data reduction, we created light curves for each of the systems and modeled the eclipsing binaries using the BinaryMaker3 and PHOEBE programs to determine their fundamental physical parameters for the first time. Complete light curves and preliminary models for each of these neglected eclipsing binary systems will be presented.
Smith, J. E., Jr.
1985-01-01
Transparent binary metallic alloy solidification models are important in attempts to understand the processes causing liquid-liquid and solid-liquid phase transformations in metallic alloy systems. These models permit visual observation of the phase transformation and the processes proceding solidification. The number of these transparent monotectic binary models needs to be expanded to distinguish between the unique and general phenomena observed. The expansion of the number of accurately determined monotectic phase diagrams of model systems, and contribution to a data base for eventual use with UNIFAC group contribution methods is examined.
Dynamic Ising model: reconstruction of evolutionary trees
International Nuclear Information System (INIS)
De Oliveira, P M C
2013-01-01
An evolutionary tree is a cascade of bifurcations starting from a single common root, generating a growing set of daughter species as time goes by. ‘Species’ here is a general denomination for biological species, spoken languages or any other entity which evolves through heredity. From the N currently alive species within a clade, distances are measured through pairwise comparisons made by geneticists, linguists, etc. The larger is such a distance that, for a pair of species, the older is their last common ancestor. The aim is to reconstruct the previously unknown bifurcations, i.e. the whole clade, from knowledge of the N(N − 1)/2 quoted distances, which are taken for granted. A mechanical method is presented and its applicability is discussed. (paper)
Constraining Roche-Lobe Overflow Models Using the Hot-Subdwarf Wide Binary Population
Vos, Joris; Vučković, Maja
2017-12-01
One of the important issues regarding the final evolution of stars is the impact of binarity. A rich zoo of peculiar, evolved objects are born from the interaction between the loosely bound envelope of a giant, and the gravitational pull of a companion. However, binary interactions are not understood from first principles, and the theoretical models are subject to many assumptions. It is currently agreed upon that hot subdwarf stars can only be formed through binary interaction, either through common envelope ejection or stable Roche-lobe overflow (RLOF) near the tip of the red giant branch (RGB). These systems are therefore an ideal testing ground for binary interaction models. With our long term study of wide hot subdwarf (sdB) binaries we aim to improve our current understanding of stable RLOF on the RGB by comparing the results of binary population synthesis studies with the observed population. In this article we describe the current model and possible improvements, and which observables can be used to test different parts of the interaction model.
Verification of Fault Tree Models with RBDGG Methodology
International Nuclear Information System (INIS)
Kim, Man Cheol
2010-01-01
Currently, fault tree analysis is widely used in the field of probabilistic safety assessment (PSA) of nuclear power plants (NPPs). To guarantee the correctness of fault tree models, which are usually manually constructed by analysts, a review by other analysts is widely used for verifying constructed fault tree models. Recently, an extension of the reliability block diagram was developed, which is named as RBDGG (reliability block diagram with general gates). The advantage of the RBDGG methodology is that the structure of a RBDGG model is very similar to the actual structure of the analyzed system and, therefore, the modeling of a system for a system reliability and unavailability analysis becomes very intuitive and easy. The main idea of the development of the RBDGG methodology is similar to that of the development of the RGGG (Reliability Graph with General Gates) methodology. The difference between the RBDGG methodology and RGGG methodology is that the RBDGG methodology focuses on the block failures while the RGGG methodology focuses on the connection line failures. But, it is also known that an RGGG model can be converted to an RBDGG model and vice versa. In this paper, a new method for the verification of the constructed fault tree models using the RBDGG methodology is proposed and demonstrated
International Nuclear Information System (INIS)
Kee, Ernest J.; Sun, Alice; Rodgers, Shawn; Popova, ElmiraV; Nelson, Paul; Moiseytseva, Vera; Wang, Eric
2006-01-01
South Texas Project uses a large fault tree to produce scenarios (minimal cut sets) used in quantification of plant availability and event frequency predictions. On the other hand, the South Texas Project probabilistic risk assessment model uses a large event tree, small fault tree for quantifying core damage and radioactive release frequency predictions. The South Texas Project is converting its availability and event frequency model to use a large event tree, small fault in an effort to streamline application support and to provide additional detail in results. The availability and event frequency model as well as the applications it supports (maintenance and operational risk management, system engineering health assessment, preventive maintenance optimization, and RIAM) are briefly described. A methodology to perform availability modeling in a large event tree, small fault tree framework is described in detail. How the methodology can be used to support South Texas Project maintenance and operations risk management is described in detail. Differences with other fault tree methods and other recently proposed methods are discussed in detail. While the methods described are novel to the South Texas Project Risk Management program and to large event tree, small fault tree models, concepts in the area of application support and availability modeling have wider applicability to the industry. (authors)
tqDist: a library for computing the quartet and triplet distances between binary or general trees.
Sand, Andreas; Holt, Morten K; Johansen, Jens; Brodal, Gerth Stølting; Mailund, Thomas; Pedersen, Christian N S
2014-07-15
tqDist is a software package for computing the triplet and quartet distances between general rooted or unrooted trees, respectively. The program is based on algorithms with running time [Formula: see text] for the triplet distance calculation and [Formula: see text] for the quartet distance calculation, where n is the number of leaves in the trees and d is the degree of the tree with minimum degree. These are currently the fastest algorithms both in theory and in practice. tqDist can be installed on Windows, Linux and Mac OS X. Doing this will install a set of command-line tools together with a Python module and an R package for scripting in Python or R. The software package is freely available under the GNU LGPL licence at http://birc.au.dk/software/tqDist. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Modeling tree crown dynamics with 3D partial differential equations.
Beyer, Robert; Letort, Véronique; Cournède, Paul-Henry
2014-01-01
We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth toward light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
Modeling Tree Crown Dynamics with 3D Partial Differential Equations
Directory of Open Access Journals (Sweden)
Robert eBeyer
2014-07-01
Full Text Available We characterize a tree's spatial foliage distribution by the local leaf area density. Considering this spatially continuous variable allows to describe the spatiotemporal evolution of the tree crown by means of 3D partial differential equations. These offer a framework to rigorously take locally and adaptively acting effects into account, notably the growth towards light. Biomass production through photosynthesis and the allocation to foliage and wood are readily included in this model framework. The system of equations stands out due to its inherent dynamic property of self-organization and spontaneous adaptation, generating complex behavior from even only a few parameters. The density-based approach yields spatially structured tree crowns without relying on detailed geometry. We present the methodological fundamentals of such a modeling approach and discuss further prospects and applications.
UML Statechart Fault Tree Generation By Model Checking
DEFF Research Database (Denmark)
Herbert, Luke Thomas; Herbert-Hansen, Zaza Nadja Lee
Creating fault tolerant and efficient process work-flows poses a significant challenge. Individual faults, defined as an abnormal conditions or defects in a component, equipment, or sub-process, must be handled so that the system may continue to operate, and are typically addressed by implementing...... engineers imagine what undesirable events can occur under which conditions. Fault Tree Analysis (FTA) attempts to analyse the failure of systems by composing logic diagrams of separate individual faults to determine the probabil-ity of larger compound faults occurring. FTA is a commonly used method......-pleteness). To avoid these deficiencies, our approach derives the fault tree directly from the formal system model, under the assumption that any state can fail. We present a framework for the automated gener-ation of fault trees from models of real-world pro-cess workflows, expressed in a formalised subset...
River flow modelling using fuzzy decision trees
Han, D.; Cluckie, I. D.; Karbassioun, D.; Lawry, J.; Krauskopf, B.
2002-01-01
A modern real time flood forecasting system requires its mathematical model(s) to handle highly complex rainfall runoff processes. Uncertainty in real time flood forecasting will involve a variety of components such as measurement noise from telemetry systems, inadequacy of the models, insufficiency
B. Li (Bayoue); B. Roozenbeek (Bob); E.W. Steyerberg (Ewout); E.M.E.H. Lesaffre (Emmanuel)
2011-01-01
textabstractBackground: Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods. We used individual patient data from 8509
Modeling diffusion coefficients in binary mixtures of polar and non-polar compounds
DEFF Research Database (Denmark)
Medvedev, Oleg; Shapiro, Alexander
2005-01-01
The theory of transport coefficients in liquids, developed previously, is tested on a description of the diffusion coefficients in binary polar/non-polar mixtures, by applying advanced thermodynamic models. Comparison to a large set of experimental data shows good performance of the model. Only...
Testing Models of Circum-Binary-AGN Accretion for PSO J334.2028+01.4075
Foord, Adi; Gultekin, Kayhan; Reynolds, Mark
2017-08-01
We present analysis of new Chandra data of PSO J334.2028+01.4075 (PSO J334 hereafter), a strong binary AGN candidate discovered by Liu et al. (2015) based on periodic variation of the optical flux. Recent radio coverage presented in Mooley et al. (2017) further supports that PSO J334 is a binary black hole system, as the quasar was found to be lobe-dominated with a twisted radio structure, possibly due to a precessing jet. With no prior X-ray coverage for PSO J334, our new 50 ksec Chandra observation allows for the unique opportunity to differentiate between a single or binary-AGN system, and if a binary, can characterize the mode of accretion. The two most basic sets of predictions via simulations of circum-binary accretion model are a “cavity”, where the inner region of the accretion disk is mostly empty and emission is truncated blueward of the wavelength associated with the temperature of the innermost ring, or “minidisks”, where there is substantial accretion onto one or both of the members of the binary, each with their own shock-heated thin-disk accretion system. We find the X-ray emission to be well-fit with a heavily absorbed power-law, incompatible with the cavity scenario. Further, we construct an SED of PSO J334 by combining radio through X-ray observations and compare it to standard QSO SEDs. We discuss the implications of the comparison between the SED of PSO J334 and that of a single AGN, and assess the likelihood of the binary model for PSO J334.
Fractal approach to computer-analytical modelling of tree crown
International Nuclear Information System (INIS)
Berezovskaya, F.S.; Karev, G.P.; Kisliuk, O.F.; Khlebopros, R.G.; Tcelniker, Yu.L.
1993-09-01
In this paper we discuss three approaches to the modeling of a tree crown development. These approaches are experimental (i.e. regressive), theoretical (i.e. analytical) and simulation (i.e. computer) modeling. The common assumption of these is that a tree can be regarded as one of the fractal objects which is the collection of semi-similar objects and combines the properties of two- and three-dimensional bodies. We show that a fractal measure of crown can be used as the link between the mathematical models of crown growth and light propagation through canopy. The computer approach gives the possibility to visualize a crown development and to calibrate the model on experimental data. In the paper different stages of the above-mentioned approaches are described. The experimental data for spruce, the description of computer system for modeling and the variant of computer model are presented. (author). 9 refs, 4 figs
Approximate dynamic fault tree calculations for modelling water supply risks
International Nuclear Information System (INIS)
Lindhe, Andreas; Norberg, Tommy; Rosén, Lars
2012-01-01
Traditional fault tree analysis is not always sufficient when analysing complex systems. To overcome the limitations dynamic fault tree (DFT) analysis is suggested in the literature as well as different approaches for how to solve DFTs. For added value in fault tree analysis, approximate DFT calculations based on a Markovian approach are presented and evaluated here. The approximate DFT calculations are performed using standard Monte Carlo simulations and do not require simulations of the full Markov models, which simplifies model building and in particular calculations. It is shown how to extend the calculations of the traditional OR- and AND-gates, so that information is available on the failure probability, the failure rate and the mean downtime at all levels in the fault tree. Two additional logic gates are presented that make it possible to model a system's ability to compensate for failures. This work was initiated to enable correct analyses of water supply risks. Drinking water systems are typically complex with an inherent ability to compensate for failures that is not easily modelled using traditional logic gates. The approximate DFT calculations are compared to results from simulations of the corresponding Markov models for three water supply examples. For the traditional OR- and AND-gates, and one gate modelling compensation, the errors in the results are small. For the other gate modelling compensation, the error increases with the number of compensating components. The errors are, however, in most cases acceptable with respect to uncertainties in input data. The approximate DFT calculations improve the capabilities of fault tree analysis of drinking water systems since they provide additional and important information and are simple and practically applicable.
International Nuclear Information System (INIS)
Sun Zhongguo; Xi Guang; Chen Xi
2009-01-01
The binary collision of liquid droplets is of both practical importance and fundamental value in computational fluid mechanics. We present a modified surface tension model within the moving particle semi-implicit (MPS) method, and carry out two-dimensional simulations to investigate the mechanisms of coalescence and separation of the droplets during binary collision. The modified surface tension model improves accuracy and convergence. A mechanism map is established for various possible deformation pathways encountered during binary collision, as the impact speed is varied; a new pathway is reported when the collision speed is critical. In addition, eccentric collisions are simulated and the effect of the rotation of coalesced particle is explored. The results qualitatively agree with experiments and the numerical protocol may find applications in studying free surface flows and interface deformation
Interfacing modeling suite Physics Of Eclipsing Binaries 2.0 with a Virtual Reality Platform
Harriett, Edward; Conroy, Kyle; Prša, Andrej; Klassner, Frank
2018-01-01
To explore alternate methods for modeling eclipsing binary stars, we extrapolate upon PHOEBE’s (PHysics Of Eclipsing BinariEs) capabilities in a virtual reality (VR) environment to create an immersive and interactive experience for users. The application used is Vizard, a python-scripted VR development platform for environments such as Cave Automatic Virtual Environment (CAVE) and other off-the-shelf VR headsets. Vizard allows the freedom for all modeling to be precompiled without compromising functionality or usage on its part. The system requires five arguments to be precomputed using PHOEBE’s python front-end: the effective temperature, flux, relative intensity, vertex coordinates, and orbits; the user can opt to implement other features from PHOEBE to be accessed within the simulation as well. Here we present the method for making the data observables accessible in real time. An Occulus Rift will be available for a live showcase of various cases of VR rendering of PHOEBE binary systems including detached and contact binary stars.
Modelling mite dynamics on apple trees in eastern North America
Hartman, J.M.; Werf, van der W.; Nyrop, J.P.
1999-01-01
The model described in this paper simulates seasonal dynamics of Panonychus ulmi and the phytoseiid predator Typhlodromus pyri on apple trees in Eastern North America. It was originally developed to understand the effect of weather, predation, cannibalism, alternate food for the predator, and uneven
tree crown ratio models for tropical rainforests in oban division
African Journals Online (AJOL)
DR ADESOPE
habitat variable. It is often estimated using allometry. Modified versions of Logistics,. Richards, Weibull and Exponential functions were used to predict CR for ..... (ANOVA) were carried out to investigate significant differences in tree growth variables under different canopy layers. The mathematical model for the design is: 9.
Discrete Discriminant analysis based on tree-structured graphical models
DEFF Research Database (Denmark)
Perez de la Cruz, Gonzalo; Eslava, Guillermina
The purpose of this paper is to illustrate the potential use of discriminant analysis based on tree{structured graphical models for discrete variables. This is done by comparing its empirical performance using estimated error rates for real and simulated data. The results show that discriminant...
Ethnographic Decision Tree Modeling: A Research Method for Counseling Psychology.
Beck, Kirk A.
2005-01-01
This article describes ethnographic decision tree modeling (EDTM; C. H. Gladwin, 1989) as a mixed method design appropriate for counseling psychology research. EDTM is introduced and located within a postpositivist research paradigm. Decision theory that informs EDTM is reviewed, and the 2 phases of EDTM are highlighted. The 1st phase, model…
Modelling dimensional growth of three street tree species in the ...
African Journals Online (AJOL)
The results could also be used in the process of modelling energy use reduction, air pollution uptake, rainfall interception, carbon sequestration and microclimate modification of urban forests such as those found in the City of Tshwane. Keywords: allometry; regression; size relationships; tree growth; urban forests. Southern ...
Steppe, Kathy; von der Crone, Jonas S; De Pauw, Dirk J W
2016-01-01
TreeWatch.net is an initiative that has been developed to watch trees grow and function in real-time. It is a water- and carbon-monitoring and modeling network, in which high-quality measurements of sap flow and stem diameter variation are collected on individual trees. Automated data processing using a cloud service enables instant visualization of water movement and radial stem growth. This can be used to demonstrate the sensitivity of trees to changing weather conditions, such as drought, heat waves, or heavy rain showers. But TreeWatch.net's true innovation lies in its use of these high-precision harmonized data to also parameterize process-based tree models in real-time, which makes displaying the much-needed mechanisms underlying tree responses to climate change possible. Continuous simulation of turgor to describe growth processes and long-term time series of hydraulic resistance to assess drought-vulnerability in real-time are only a few of the opportunities our approach offers. TreeWatch.net has been developed with the view to be complementary to existing forest monitoring networks and with the aim to contribute to existing dynamic global vegetation models. It provides high-quality data and real-time simulations in order to advance research on the impact of climate change on the biological response of trees and forests. Besides its application in natural forests to answer climate-change related scientific and political questions, we also envision a broader societal application of TreeWatch.net by selecting trees in nature reserves, public areas, cities, university areas, schoolyards, and parks to teach youngsters and create public awareness on the effects of changing weather conditions on trees and forests in this era of climate change.
Water-Tree Modelling and Detection for Underground Cables
Chen, Qi
In recent years, aging infrastructure has become a major concern for the power industry. Since its inception in early 20th century, the electrical system has been the cornerstone of an industrial society. Stable and uninterrupted delivery of electrical power is now a base necessity for the modern world. As the times march-on, however, the electrical infrastructure ages and there is the inevitable need to renew and replace the existing system. Unfortunately, due to time and financial constraints, many electrical systems today are forced to operate beyond their original design and power utilities must find ways to prolong the lifespan of older equipment. Thus, the concept of preventative maintenance arises. Preventative maintenance allows old equipment to operate longer and at better efficiency, but in order to implement preventative maintenance, the operators must know minute details of the electrical system, especially some of the harder to assess issues such water-tree. Water-tree induced insulation degradation is a problem typically associated with older cable systems. It is a very high impedance phenomenon and it is difficult to detect using traditional methods such as Tan-Delta or Partial Discharge. The proposed dissertation studies water-tree development in underground cables, potential methods to detect water-tree location and water-tree severity estimation. The dissertation begins by developing mathematical models of water-tree using finite element analysis. The method focuses on surface-originated vented tree, the most prominent type of water-tree fault in the field. Using the standard operation parameters of North American electrical systems, the water-tree boundary conditions are defined. By applying finite element analysis technique, the complex water-tree structure is broken down to homogeneous components. The result is a generalized representation of water-tree capacitance at different stages of development. The result from the finite element analysis
X-ray-binary spectra in the lamp post model
Vincent, F. H.; Różańska, A.; Zdziarski, A. A.; Madej, J.
2016-05-01
Context. The high-energy radiation from black-hole binaries may be due to the reprocessing of a lamp located on the black hole rotation axis and emitting X-rays. The observed spectrum is made of three major components: the direct spectrum traveling from the lamp directly to the observer; the thermal bump at the equilibrium temperature of the accretion disk heated by the lamp; and the reflected spectrum essentially made of the Compton hump and the iron-line complex. Aims: We aim to accurately compute the complete reprocessed spectrum (thermal bump + reflected) of black-hole binaries over the entire X-ray band. We also determine the strength of the direct component. Our choice of parameters is adapted to a source showing an important thermal component. We are particularly interested in investigating the possibility to use the iron-line complex as a probe to constrain the black hole spin. Methods: We computed in full general relativity the illumination of a thin accretion disk by a fixed X-ray lamp along the rotation axis. We used the ATM21 radiative transfer code to compute the local, energy-dependent spectrum emitted along the disk as a function of radius, emission angle and black hole spin. We then ray traced this local spectrum to determine the final reprocessed spectrum as received by a distant observer. We consider two extreme values of the black hole spin (a = 0 and a = 0.98) and discuss the dependence of the local and ray-traced spectra on the emission angle and black hole spin. Results: We show the importance of the angle dependence of the total disk specific intensity spectrum emitted by the illuminated atmosphere when the thermal disk emission is fully taken into account. The disk flux, together with the X-ray flux from the lamp, determines the temperature and ionization structure of the atmosphere. High black hole spin implies high temperature in the inner disk regions, therefore, the emitted thermal disk spectrum fully covers the iron-line complex. As a
Price, B; Gomez, A; Mathys, L; Gardi, O; Schellenberger, A; Ginzler, C; Thürig, E
2017-03-01
Trees outside forest (TOF) can perform a variety of social, economic and ecological functions including carbon sequestration. However, detailed quantification of tree biomass is usually limited to forest areas. Taking advantage of structural information available from stereo aerial imagery and airborne laser scanning (ALS), this research models tree biomass using national forest inventory data and linear least-square regression and applies the model both inside and outside of forest to create a nationwide model for tree biomass (above ground and below ground). Validation of the tree biomass model against TOF data within settlement areas shows relatively low model performance (R 2 of 0.44) but still a considerable improvement on current biomass estimates used for greenhouse gas inventory and carbon accounting. We demonstrate an efficient and easily implementable approach to modelling tree biomass across a large heterogeneous nationwide area. The model offers significant opportunity for improved estimates on land use combination categories (CC) where tree biomass has either not been included or only roughly estimated until now. The ALS biomass model also offers the advantage of providing greater spatial resolution and greater within CC spatial variability compared to the current nationwide estimates.
Sequential and Parallel Attack Tree Modelling
Arnold, Florian; Guck, Dennis; Kumar, Rajesh; Stoelinga, Mariëlle Ida Antoinette; Koornneef, Floor; van Gulijk, Coen
The intricacy of socio-technical systems requires a careful planning and utilisation of security resources to ensure uninterrupted, secure and reliable services. Even though many studies have been conducted to understand and model the behaviour of a potential attacker, the detection of crucial
Systems analysis approach to probabilistic modeling of fault trees
International Nuclear Information System (INIS)
Bartholomew, R.J.; Qualls, C.R.
1985-01-01
A method of probabilistic modeling of fault tree logic combined with stochastic process theory (Markov modeling) has been developed. Systems are then quantitatively analyzed probabilistically in terms of their failure mechanisms including common cause/common mode effects and time dependent failure and/or repair rate effects that include synergistic and propagational mechanisms. The modeling procedure results in a state vector set of first order, linear, inhomogeneous, differential equations describing the time dependent probabilities of failure described by the fault tree. The solutions of this Failure Mode State Variable (FMSV) model are cumulative probability distribution functions of the system. A method of appropriate synthesis of subsystems to form larger systems is developed and applied to practical nuclear power safety systems
A dynamic analysis of Schelling’s binary corruption model : A competitive equilibrium approach
Caulkins, J.P.; Feichtinger, G.; Grass, D.; Hartl, R.F.; Kort, P.M.; Novak, A.J.; Seidl, A.; Wirl, F.
Schelling (in Micromotives and Macrobehavior, Norton, New York, 1978) suggested a simple binary choice model to explain the variation of corruption levels across societies. His basic idea was that the expected profitability of engaging in corruption depends on its prevalence. The key result of the
Optimization of binary breeder reactor. 1. Sodium void reactivity and Doppler effect in a new model
International Nuclear Information System (INIS)
Nascimento, J.A. do; Dias, A.F.; Ishiguro, Y.
1985-01-01
A model for the Binary Breeder Reactor (BBR) is examined for the inherent safety characteristics, sodium void reactivity and Doppler effect in the beginning of cycle and a hypothetical end of cycle. In addition to the standard fueling mode of the BBR, two others are considered: U 238 /U 233 -alternate fueling, and U 238 /PU-normal fueling of LMFBRs. (Author) [pt
Theoretical model of the density of states of random binary alloys
International Nuclear Information System (INIS)
Zekri, N.; Brezini, A.
1991-09-01
A theoretical formulation of the density of states for random binary alloys is examined based on a mean field treatment. The present model includes both diagonal and off-diagonal disorder and also short-range order. Extensive results are reported for various concentrations and compared to other calculations. (author). 22 refs, 6 figs
Photometric Modelling of Close Binary Star CN And DMZ Jassur & A ...
Indian Academy of Sciences (India)
Photometric Modelling of Close Binary Star CN And. D. M. Z. Jassur. 1,2,∗. & A. Khodadadi. 2. 1Faculty of Physics, Tabriz University, Tabriz, Iran. ∗ e-mail: Jassur@tabrizu.ac.ir. 2Center for Applied Physics and Astronomical Research, Khadjeh Nassir Addin Observatory,. Tabriz, Iran. Received 2004 April 15; accepted 2006 ...
Directory of Open Access Journals (Sweden)
Da Liu
Full Text Available Traditional forecasting models fit a function approximation from dependent invariables to independent variables. However, they usually get into trouble when date are presented in various formats, such as text, voice and image. This study proposes a novel image-encoded forecasting method that input and output binary digital two-dimensional (2D images are transformed from decimal data. Omitting any data analysis or cleansing steps for simplicity, all raw variables were selected and converted to binary digital images as the input of a deep learning model, convolutional neural network (CNN. Using shared weights, pooling and multiple-layer back-propagation techniques, the CNN was adopted to locate the nexus among variations in local binary digital images. Due to the computing capability that was originally developed for binary digital bitmap manipulation, this model has significant potential for forecasting with vast volume of data. The model was validated by a power loads predicting dataset from the Global Energy Forecasting Competition 2012.
Tree Memory Networks for Modelling Long-term Temporal Dependencies
Fernando, Tharindu; Denman, Simon; McFadyen, Aaron; Sridharan, Sridha; Fookes, Clinton
2017-01-01
In the domain of sequence modelling, Recurrent Neural Networks (RNN) have been capable of achieving impressive results in a variety of application areas including visual question answering, part-of-speech tagging and machine translation. However this success in modelling short term dependencies has not successfully transitioned to application areas such as trajectory prediction, which require capturing both short term and long term relationships. In this paper, we propose a Tree Memory Networ...
Forecasting Shaharchay River Flow in Lake Urmia Basin using Genetic Programming and M5 Model Tree
Directory of Open Access Journals (Sweden)
S. Samadianfard
2017-01-01
data were used for calibration and the rest were used for validation of study models including genetic programming and M5 model trees. It should be noted that for prediction of Shaharchay river flows, previous data of mentioned river in 1, 2 and 3 months ago (Q, Q, Q were used. Genetic programming: was first proposed by Koza (17. It is a generalization of genetic algorithms. The fundamental difference between genetic programming and genetic algorithm is due to the nature of the individuals. In genetic algorithm, the individuals are linear strings of fixed length (chromosomes. In genetic programming, the individuals are nonlinear entities of different sizes and shapes (parse trees. Genetic programming applies genetic algorithms to a “population” of programs, typically encoded as tree-structures. Trial programs are evaluated against a “fitness function”. Then the best solutions are selected for modification and re-evaluation. This modification-evaluation cycle is repeated until a “correct” program is produced. Model trees generalize the concepts of regression trees, which have constant values at their leaves. So, they are analogous to piece-wise linear functions. M5 model tree is a binary decision tree having linear regression function at the terminal nodes, which can predict continuous numerical attributes. Tree-based models are constructed by a divide-and-conquer method. Results and Discussion: In order to investigate the probability of using different mathematical functions in genetic programming method, three combinations of the functions were used in the current study. The results showed that in the case of predicting river flows with Q, M5 model trees with root mean squared error of 4.7907 in comparison with genetic programming by the best mathematical functions and root mean squared error of 4.8233 had better performances. Obtained results indicated that adding more mathematical functions to the genetic programming and producing more complicated
Geometric Modelling of Tree Roots with Different Levels of Detail
Guerrero Iñiguez, J. I.
2017-09-01
This paper presents a geometric approach for modelling tree roots with different Levels of Detail, suitable for analysis of the tree anchoring, potentially occupied underground space, interaction with urban elements and damage produced and taken in the built-in environment. Three types of tree roots are considered to cover several species: tap root, heart shaped root and lateral roots. Shrubs and smaller plants are not considered, however, a similar approach can be considered if the information is available for individual species. The geometrical approach considers the difficulties of modelling the actual roots, which are dynamic and almost opaque to direct observation, proposing generalized versions. For each type of root, different geometric models are considered to capture the overall shape of the root, a simplified block model, and a planar or surface projected version. Lower detail versions are considered as compatibility version for 2D systems while higher detail models are suitable for 3D analysis and visualization. The proposed levels of detail are matched with CityGML Levels of Detail, enabling both analysis and aesthetic views for urban modelling.
Modelling Single Tree Structure with Terrestrial Laser Scanner
Yurtseven, H.; Akgül, M.; Gülci, S.
2017-11-01
Recent technological developments, which has reliable accuracy and quality for all engineering works, such as remote sensing tools have wide range use in forestry applications. Last decade, sustainable use and management opportunities of forest resources are favorite topics. Thus, precision of obtained data plays an important role in evaluation of current status of forests' value. The use of aerial and terrestrial laser technology has more reliable and effective models to advance the appropriate natural resource management. This study investigates the use of terrestrial laser scanner (TLS) technology in forestry, and also the methodological data processing stages for tree volume extraction is explained. Z+F Imager 5010C TLS system was used for measure single tree information such as tree height, diameter of breast height, branch volume and canopy closure. In this context more detailed and accurate data can be obtained than conventional inventory sampling in forestry by using TLS systems. However the accuracy of obtained data is up to the experiences of TLS operator in the field. Number of scan stations and its positions are other important factors to reduce noise effect and accurate 3D modelling. The results indicated that the use of point cloud data to extract tree information for forestry applications are promising methodology for precision forestry.
Lattice Boltzmann model for thermal binary-mixture gas flows.
Kang, Jinfen; Prasianakis, Nikolaos I; Mantzaras, John
2013-05-01
A lattice Boltzmann model for thermal gas mixtures is derived. The kinetic model is designed in a way that combines properties of two previous literature models, namely, (a) a single-component thermal model and (b) a multicomponent isothermal model. A comprehensive platform for the study of various practical systems involving multicomponent mixture flows with large temperature differences is constructed. The governing thermohydrodynamic equations include the mass, momentum, energy conservation equations, and the multicomponent diffusion equation. The present model is able to simulate mixtures with adjustable Prandtl and Schmidt numbers. Validation in several flow configurations with temperature and species concentration ratios up to nine is presented.
Hierarchical models for informing general biomass equations with felled tree data
Brian J. Clough; Matthew B. Russell; Christopher W. Woodall; Grant M. Domke; Philip J. Radtke
2015-01-01
We present a hierarchical framework that uses a large multispecies felled tree database to inform a set of general models for predicting tree foliage biomass, with accompanying uncertainty, within the FIA database. Results suggest significant prediction uncertainty for individual trees and reveal higher errors when predicting foliage biomass for larger trees and for...
Two-dimensional model of laser alloying of binary alloy powder with interval of melting temperature
Knyzeva, A. G.; Sharkeev, Yu. P.
2017-10-01
The paper contains two-dimensional model of laser beam melting of powders from binary alloy. The model takes into consideration the melting of alloy in some temperature interval between solidus and liquidus temperatures. The external source corresponds to laser beam with energy density distributed by Gauss law. The source moves along the treated surface according to given trajectory. The model allows investigating the temperature distribution and thickness of powder layer depending on technological parameters.
Danandeh Mehr, Ali; Nourani, Vahid; Hrnjica, Bahrudin; Molajou, Amir
2017-12-01
The effectiveness of genetic programming (GP) for solving regression problems in hydrology has been recognized in recent studies. However, its capability to solve classification problems has not been sufficiently explored so far. This study develops and applies a novel classification-forecasting model, namely Binary GP (BGP), for teleconnection studies between sea surface temperature (SST) variations and maximum monthly rainfall (MMR) events. The BGP integrates certain types of data pre-processing and post-processing methods with conventional GP engine to enhance its ability to solve both regression and classification problems simultaneously. The model was trained and tested using SST series of Black Sea, Mediterranean Sea, and Red Sea as potential predictors as well as classified MMR events at two locations in Iran as predictand. Skill of the model was measured in regard to different rainfall thresholds and SST lags and compared to that of the hybrid decision tree-association rule (DTAR) model available in the literature. The results indicated that the proposed model can identify potential teleconnection signals of surrounding seas beneficial to long-term forecasting of the occurrence of the classified MMR events.
Modeling synchronized calling behavior of Japanese tree frogs.
Aihara, Ikkyu
2009-07-01
We experimentally observed synchronized calling behavior of male Japanese tree frogs Hyla japonica; namely, while isolated single frogs called nearly periodically, a pair of interacting frogs called synchronously almost in antiphase or inphase. In this study, we propose two types of phase-oscillator models on different degrees of approximations, which can quantitatively explain the phase and frequency properties in the experiment. Moreover, it should be noted that, although the second model is obtained by fitting to the experimental data of the two synchronized states, the model can also explain the transitory dynamics in the interactive calling behavior, namely, the shift from a transient inphase state to a stable antiphase state. We also discuss the biological relevance of the estimated parameter values to calling behavior of Japanese tree frogs and the possible biological meanings of the synchronized calling behavior.
Populus: arabidopsis for forestry. Do we need a model tree?
Taylor, Gail
2002-12-01
Trees are used to produce a variety of wood-based products including timber, pulp and paper. More recently, their use as a source of renewable energy has also been highlighted, as has their value for carbon mitigation within the Kyoto Protocol. Relative to food crops, the domestication of trees has only just begun; the long generation time and complex nature of juvenile and mature growth forms are contributory factors. To accelerate domestication, and to understand further some of the unique processes that occur in woody plants such as dormancy and secondary wood formation, a 'model' tree is needed. Here it is argued that Populus is rapidly becoming accepted as the 'model' woody plant and that such a 'model' tree is necessary to complement the genetic resource being developed in arabidopsis. The genus Populus (poplars, cottonwoods and aspens) contains approx. 30 species of woody plant, all found in the Northern hemisphere and exhibiting some of the fastest growth rates observed in temperate trees. Populus is fulfilling the 'model' role for a number of reasons. First, and most important, is the very recent commitment to sequence the Populus genome, a project initiated in February 2002. This will be the first woody plant to be sequenced. Other reasons include the relatively small genome size (450-550 Mbp) of Populus, the large number of molecular genetic maps and the ease of genetic transformation. Populus may also be propagated vegetatively, making mapping populations immortal and facilitating the production of large amounts of clonal material for experimentation. Hybridization occurs routinely and, in these respects, Populus has many similarities to arabidopsis. However, Populus also differs from arabidopsis in many respects, including being dioecious, which makes selfing and back-cross manipulations impossible. The long time-to-flower is also a limitation, whilst physiological and biochemical experiments are more readily conducted in Populus compared with the
Directory of Open Access Journals (Sweden)
Jörgen Wallerman
2013-04-01
Full Text Available Individual tree crowns may be delineated from airborne laser scanning (ALS data by segmentation of surface models or by 3D analysis. Segmentation of surface models benefits from using a priori knowledge about the proportions of tree crowns, which has not yet been utilized for 3D analysis to any great extent. In this study, an existing surface segmentation method was used as a basis for a new tree model 3D clustering method applied to ALS returns in 104 circular field plots with 12 m radius in pine-dominated boreal forest (64°14'N, 19°50'E. For each cluster below the tallest canopy layer, a parabolic surface was fitted to model a tree crown. The tree model clustering identified more trees than segmentation of the surface model, especially smaller trees below the tallest canopy layer. Stem attributes were estimated with k-Most Similar Neighbours (k-MSN imputation of the clusters based on field-measured trees. The accuracy at plot level from the k-MSN imputation (stem density root mean square error or RMSE 32.7%; stem volume RMSE 28.3% was similar to the corresponding results from the surface model (stem density RMSE 33.6%; stem volume RMSE 26.1% with leave-one-out cross-validation for one field plot at a time. Three-dimensional analysis of ALS data should also be evaluated in multi-layered forests since it identified a larger number of small trees below the tallest canopy layer.
A GDP-driven model for the binary and weighted structure of the International Trade Network
Almog, Assaf; Squartini, Tiziano; Garlaschelli, Diego
2015-01-01
Recent events such as the global financial crisis have renewed the interest in the topic of economic networks. One of the main channels of shock propagation among countries is the International Trade Network (ITN). Two important models for the ITN structure, the classical gravity model of trade (more popular among economists) and the fitness model (more popular among networks scientists), are both limited to the characterization of only one representation of the ITN. The gravity model satisfactorily predicts the volume of trade between connected countries, but cannot reproduce the missing links (i.e. the topology). On the other hand, the fitness model can successfully replicate the topology of the ITN, but cannot predict the volumes. This paper tries to make an important step forward in the unification of those two frameworks, by proposing a new gross domestic product (GDP) driven model which can simultaneously reproduce the binary and the weighted properties of the ITN. Specifically, we adopt a maximum-entropy approach where both the degree and the strength of each node are preserved. We then identify strong nonlinear relationships between the GDP and the parameters of the model. This ultimately results in a weighted generalization of the fitness model of trade, where the GDP plays the role of a ‘macroeconomic fitness’ shaping the binary and the weighted structure of the ITN simultaneously. Our model mathematically explains an important asymmetry in the role of binary and weighted network properties, namely the fact that binary properties can be inferred without the knowledge of weighted ones, while the opposite is not true.
Efficient and robust estimation for longitudinal mixed models for binary data
DEFF Research Database (Denmark)
Holst, René
2009-01-01
This paper proposes a longitudinal mixed model for binary data. The model extends the classical Poisson trick, in which a binomial regression is fitted by switching to a Poisson framework. A recent estimating equations method for generalized linear longitudinal mixed models, called GEEP, is used...... as a vehicle for fitting the conditional Poisson regressions, given a latent process of serial correlated Tweedie variables. The regression parameters are estimated using a quasi-score method, whereas the dispersion and correlation parameters are estimated by use of bias-corrected Pearson-type estimating...... equations, using second moments only. Random effects are predicted by BLUPs. The method provides a computationally efficient and robust approach to the estimation of longitudinal clustered binary data and accommodates linear and non-linear models. A simulation study is used for validation and finally...
Optimization Method of Fusing Model Tree into Partial Least Squares
Directory of Open Access Journals (Sweden)
Yu Fang
2017-01-01
Full Text Available Partial Least Square (PLS can’t adapt to the characteristics of the data of many fields due to its own features multiple independent variables, multi-dependent variables and non-linear. However, Model Tree (MT has a good adaptability to nonlinear function, which is made up of many multiple linear segments. Based on this, a new method combining PLS and MT to analysis and predict the data is proposed, which build MT through the main ingredient and the explanatory variables(the dependent variable extracted from PLS, and extract residual information constantly to build Model Tree until well-pleased accuracy condition is satisfied. Using the data of the maxingshigan decoction of the monarch drug to treat the asthma or cough and two sample sets in the UCI Machine Learning Repository, the experimental results show that, the ability of explanation and predicting get improved in the new method.
A diagnostic tree model for polytomous responses with multiple strategies.
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.
Dang, Qianyu; Mazumdar, Sati; Houck, Patricia R
2008-08-01
The generalized linear mixed model (GLIMMIX) provides a powerful technique to model correlated outcomes with different types of distributions. The model can now be easily implemented with SAS PROC GLIMMIX in version 9.1. For binary outcomes, linearization methods of penalized quasi-likelihood (PQL) or marginal quasi-likelihood (MQL) provide relatively accurate variance estimates for fixed effects. Using GLIMMIX based on these linearization methods, we derived formulas for power and sample size calculations for longitudinal designs with attrition over time. We found that the power and sample size estimates depend on the within-subject correlation and the size of random effects. In this article, we present tables of minimum sample sizes commonly used to test hypotheses for longitudinal studies. A simulation study was used to compare the results. We also provide a Web link to the SAS macro that we developed to compute power and sample sizes for correlated binary outcomes.
3D Modeling of Accretion Disks and Circumbinary Envelopes in Close Binaries
Bisikalo, D.
2010-12-01
A number of observations prove the complex flow structure in close binary stars. The gas dynamic structure of the flow is governed by the stream of matter from the inner Lagrange point, the accretion disk, the circum-disk halo, and the circumbinary envelope. Observations reflect the current state of a binary system and for their interpretation one should consider the gas dynamics of flow patterns. Three-dimensional numerical gasdynamical modeling is used to study the gaseous flow structure and dynamics in close binaries. It is shown that the periodic variations of the positions of the disk and the bow shock formed when the inner parts of the circumbinary envelope flow around the disk result in variations in both the rate of angular-momentum transfer to the disk and the flow structure near the Lagrange point L3. All these factors lead to periodic ejections of matter from the accretion disk and circum-disk halo into the outer layers of the circumbinary envelope. The results of simulations are used to estimate the physical parameters of the circumbinary envelope, including 3D matter distribution in it, and the matter-flow configuration and dynamics. The envelope becomes optically thick for systems with high mass-exchange rates, M⊙=10-8 Msun/year, and has a significant influence on the binary's observed features. The uneven phase distributions of the matter and density variations due to periodic injections of matter into the envelope are important for interpretations of observations of CBSs.
MODELING SPATIAL TREE PATTERNS IN THE TAPAJÓS FOREST USING INTERFEROMETRIC HEIGHT
Directory of Open Access Journals (Sweden)
João R. dos Santos
2005-04-01
Full Text Available The spatial distribution of very large trees in primary Amazon forest is extracted from a digital model of interferometric forest height by an approach of local maximum filtering. The spatial point patterns of very large trees are modeled by a series of Markov point process models. Spatial distribution is regular, and interaction decreases with distance; very large trees are shown to exert repulsive interaction with their neighboring very large trees.
A Conditional Curie-Weiss Model for Stylized Multi-group Binary Choice with Social Interaction
Opoku, Alex Akwasi; Edusei, Kwame Owusu; Ansah, Richard Kwame
2018-04-01
This paper proposes a conditional Curie-Weiss model as a model for decision making in a stylized society made up of binary decision makers that face a particular dichotomous choice between two options. Following Brock and Durlauf (Discrete choice with social interaction I: theory, 1955), we set-up both socio-economic and statistical mechanical models for the choice problem. We point out when both the socio-economic and statistical mechanical models give rise to the same self-consistent equilibrium mean choice level(s). Phase diagram of the associated statistical mechanical model and its socio-economic implications are discussed.
Marginal and Random Intercepts Models for Longitudinal Binary Data With Examples From Criminology.
Long, Jeffrey D; Loeber, Rolf; Farrington, David P
2009-01-01
Two models for the analysis of longitudinal binary data are discussed: the marginal model and the random intercepts model. In contrast to the linear mixed model (LMM), the two models for binary data are not subsumed under a single hierarchical model. The marginal model provides group-level information whereas the random intercepts model provides individual-level information including information about heterogeneity of growth. It is shown how a type of numerical averaging can be used with the random intercepts model to obtain group-level information, thus approximating individual and marginal aspects of the LMM. The types of inferences associated with each model are illustrated with longitudinal criminal offending data based on N = 506 males followed over a 22-year period. Violent offending indexed by official records and self-report were analyzed, with the marginal model estimated using generalized estimating equations and the random intercepts model estimated using maximum likelihood. The results show that the numerical averaging based on the random intercepts can produce prediction curves almost identical to those obtained directly from the marginal model parameter estimates. The results provide a basis for contrasting the models and the estimation procedures and key features are discussed to aid in selecting a method for empirical analysis.
Model-Based Design of Tree WSNs for Decentralized Detection
Directory of Open Access Journals (Sweden)
Ashraf Tantawy
2015-08-01
Full Text Available The classical decentralized detection problem of finding the optimal decision rules at the sensor and fusion center, as well as variants that introduce physical channel impairments have been studied extensively in the literature. The deployment of WSNs in decentralized detection applications brings new challenges to the field. Protocols for different communication layers have to be co-designed to optimize the detection performance. In this paper, we consider the communication network design problem for a tree WSN. We pursue a system-level approach where a complete model for the system is developed that captures the interactions between different layers, as well as different sensor quality measures. For network optimization, we propose a hierarchical optimization algorithm that lends itself to the tree structure, requiring only local network information. The proposed design approach shows superior performance over several contentionless and contention-based network design approaches.
Tree Contractions and Evolutionary Trees
Kao, Ming-Yang
2001-01-01
An evolutionary tree is a rooted tree where each internal vertex has at least two children and where the leaves are labeled with distinct symbols representing species. Evolutionary trees are useful for modeling the evolutionary history of species. An agreement subtree of two evolutionary trees is an evolutionary tree which is also a topological subtree of the two given trees. We give an algorithm to determine the largest possible number of leaves in any agreement subtree of two trees T_1 and ...
Observational constraints from models of close binary evolution
International Nuclear Information System (INIS)
Greve, J.P. de; Packet, W.
1984-01-01
The evolution of a system of 9 solar masses + 5.4 solar masses is computed from Zero Age Main Sequence through an early case B of mass exchange, up to the second phase of mass transfer after core helium burning. Both components are calculated simultaneously. The evolution is divided into several physically different phases. The characteristics of the models in each of these phases are transformed into corresponding 'observable' quantities. The outlook of the system for photometric observations is discussed, for an idealized case. The influence of the mass of the loser and the initial mass ratio is considered. (Auth.)
Application of Goal Tree-Success Tree model as the knowledge-base of operator advisory systems
International Nuclear Information System (INIS)
Kim, I.S.; Modarres, M.
1987-01-01
The most important portion of an expert system development is the articulation of knowledge by the expert and its satisfactory formulation in a suitable knowledge representation scheme for mechanization by a computer. A 'deep knowledge' approach called Goal Tree-Success Tree model is devised to represent complex dynamic domain knowledge. This approach can hierarchically model the underlying principles of a given process domain (for example nuclear power plant operations domain). The Goal Tree-Success Tree can then be used to represent the knowledge-base and provide means of selecting an efficient search routine in the inference engine of an expert system. A prototype expert system has been developed to demonstrate the method. This expert system models the operation of a typical system used in the pressurized water reactors. The expert system is modeled for real-time operations if an interface between plant parameters and the expert system is established. The real-time operation provides an ability to quickly remedy minor disturbances that can quickly lead to a system malfunction or trip. A description of both the Goal Tree-Success Tree model and the prototype expert system is presented. (orig.)
Decision tree models for data mining in hit discovery.
Hammann, Felix; Drewe, Juergen
2012-04-01
Decision tree induction (DTI) is a powerful means of modeling data without much prior preparation. Models are readable by humans, robust and easily applied in real-world applications, features that are mutually exclusive in other commonly used machine learning paradigms. While DTI is widely used in disciplines ranging from economics to medicine, they are an intriguing option in pharmaceutical research, especially when dealing with large data stores. This review covers the automated technologies available for creating decision trees and other rules efficiently, even from large datasets such as chemical libraries. The authors discuss the need for properly documented and validated models. Lastly, the authors cover several case studies in hit discovery, drug metabolism and toxicology, and drug surveillance, and compare them with other established techniques. DTI is a competitive and easy-to-use tool in basic research as well as in hit and drug discovery. Its strengths lie in its ability to handle all sorts of different data formats, the visual nature of the models, and the small computational effort needed for implementation in real-world systems. Limitations include lack of robustness and over-fitted models for certain types of data. As with any modeling technique, proper validation and quality measures are of utmost importance. © 2012 Informa UK, Ltd.
Binary collisions in popovici’s photogravitational model
Directory of Open Access Journals (Sweden)
Mioc V.
2002-01-01
Full Text Available The dynamics of bodies under the combined action of the gravitational attraction and the radiative repelling force has large and deep implications in astronomy. In the 1920s, the Romanian astronomer Constantin Popovici proposed a modified photogravitational law (considered by other scientists too. This paper deals with the collisions of the two-body problem associated with Popovici’s model. Resorting to McGehee-type transformations of the second kind, we obtain regular equations of motion and define the collision manifold. The flow on this boundary manifold is wholly described. This allows to point out some important qualitative features of the collisional motion: existence of the black-hole effect, gradientlikeness of the flow on the collision manifold, regularizability of collisions under certain conditions. Some questions, coming from the comparison of Levi-Civita’s regularizing transformations and McGehee’s ones, are formulated.
No tension between assembly models of super massive black hole binaries and pulsar observations.
Middleton, Hannah; Chen, Siyuan; Del Pozzo, Walter; Sesana, Alberto; Vecchio, Alberto
2018-02-08
Pulsar timing arrays are presently the only means to search for the gravitational wave stochastic background from super massive black hole binary populations, considered to be within the grasp of current or near-future observations. The stringent upper limit from the Parkes Pulsar Timing Array has been interpreted as excluding (>90% confidence) the current paradigm of binary assembly through galaxy mergers and hardening via stellar interaction, suggesting evolution is accelerated or stalled. Using Bayesian hierarchical modelling we consider implications of this upper limit for a range of astrophysical scenarios, without invoking stalling, nor more exotic physical processes. All scenarios are fully consistent with the upper limit, but (weak) bounds on population parameters can be inferred. Recent upward revisions of the black hole-galaxy bulge mass relation are disfavoured at 1.6σ against lighter models. Once sensitivity improves by an order of magnitude, a non-detection will disfavour the most optimistic scenarios at 3.9σ.
Molecular dynamics and binary collision modeling of the primary damage state of collision cascades
DEFF Research Database (Denmark)
Heinisch, H.L.; Singh, B.N.
1992-01-01
Quantitative information on defect production in cascades in copper obtained from recent molecular dynamics simulations is compared to defect production information determined earlier with a model based on the binary collision approximation (BCA). The total numbers of residual defects, the fracti...... that is practical for simulating much higher energies and longer times than MD alone can achieve. The extraction of collisional phase information from MD simulations and the correspondence of MD and BCA versions of the collisional phase is demonstrated at low energy.......Quantitative information on defect production in cascades in copper obtained from recent molecular dynamics simulations is compared to defect production information determined earlier with a model based on the binary collision approximation (BCA). The total numbers of residual defects...
Modeling of urban trees' effects on reducing human exposure to UV radiation in Seoul, Korea
Hang Ryeol Na; Gordon M. Heisler; David J. Nowak; Richard H. Grant
2014-01-01
A mathematical model isconstructed for quantifying urban treesâ effects on mitigating the intensity of ultraviolet (UV) radiation on the ground within different landuse types across a city. The model is based upon local field data, meteorological data and equations designed to predict the reduced UV fraction due to trees at the ground level. Trees in Seoul, Korea (2010...
[Sectional structure of a tree. Model analysis of the vertical biomass distribution].
Galitskiĭ, V V
2010-01-01
A model has been proposed for the architecture of a tree in which virtual trees appear rhythmically on the treetop. Each consecutive virtual tree is a part of the previous tree. The difference between two adjacent virtual trees is a section--an element of the real tree structure. In case of a spruce, the section represents a verticil of a stem with the corresponding internode. Dynamics of a photosynthesizing part of the physiologically active biomass of each section differ from the corresponding dynamics of the virtual trees and the whole real tree. If the tree biomass dynamics has a sigma-shaped form, then the section dynamics have to be bell-shaped. It means that the lower stem should accordingly become bare, which is typically observed in nature. Model analysis reveals the limiting, in the age, form of trees to be an "umbrella". It can be observed in nature and is an outcome of physical limitation of the tree height combined with the sigma-shaped form of the tree biomass dynamics. Variation of model parameters provides for various forms of the tree biomass distribution along the height, which can be associated with certain biological species of trees.
A deterministic model for the growth of non-conducting electrical tree structures
International Nuclear Information System (INIS)
Dodd, S J
2003-01-01
Electrical treeing is of interest to the electrical generation, transmission and distribution industries as it is one of the causes of insulation failure in electrical machines, switchgear and transformer bushings. In this paper a deterministic electrical tree growth model is described. The model is based on electrostatics and local electron avalanches to model partial discharge activity within the growing tree structure. Damage to the resin surrounding the tree structure is dependent on the local electrostatic energy dissipation by partial discharges within the tree structure and weighted by the magnitudes of the local electric fields in the resin surrounding the tree structure. The model is successful in simulating the formation of branched structures without the need of a random variable, a requirement of previous stochastic models. Instability in the spatial development of partial discharges within the tree structure takes the role of the stochastic element as used in previous models to produce branched tree structures. The simulated electrical trees conform to the experimentally observed behaviour; tree length versus time and electrical tree growth rate as a function of applied voltage for non-conducting electrical trees. The phase synchronous partial discharge activity and the spatial distribution of emitted light from the tree structure are also in agreement with experimental data for non-conducting trees as grown in a flexible epoxy resin and in polyethylene. The fact that similar tree growth behaviour is found using pure amorphous (epoxy resin) and semicrystalline (polyethylene) materials demonstrate that neither annealed or quenched noise, representing material inhomogeneity, is required for the formation of irregular branched structures (electrical trees). Instead, as shown in this paper, branched growth can occur due to the instability of individual discharges within the tree structure
Exponet taper-shape models to describe tree trunks
Directory of Open Access Journals (Sweden)
Valdir Carlos Lima de Andrade
2014-12-01
Full Text Available This study evaluated exponent taper-shape models and other types applied in Brazil. Data from 270 sample trees scaled-hybrid Eucalyptus urophylla and Eucalyptus grandis were used as a studying case with 18 taper types models: simple (2, biomathematics (4, segmented (2 and exponent-form (10. It was adopted the analysis of the residual distribution and statistics: multiple linear correlation, residual standard error, percentage of no significant parcels in a completely randomized split plot and average error Dunnett, both at the level of 5% significance level. It was concluded that models of taper-shape exponents, in general, are superior to other types, the segmented model of Clark et al. is superior to Max and Burkhart biomathematics and the model developed in this paper, is better than the other biomathematics evaluated.
Time variability of X-ray binaries: observations with INTEGRAL. Modeling
International Nuclear Information System (INIS)
Cabanac, Clement
2007-01-01
The exact origin of the observed X and Gamma ray variability in X-ray binaries is still an open debate in high energy astrophysics. Among others, these objects are showing aperiodic and quasi-periodic luminosity variations on timescales as small as the millisecond. This erratic behavior must put constraints on the proposed emission processes occurring in the vicinity of the neutrons star or the stellar mass black-hole held by these objects. We propose here to study their behavior following 3 different ways: first we examine the evolution of a particular X-ray source discovered by INTEGRAL, IGR J19140+0951. Using timing and spectral data given by different instruments, we show that the source type is plausibly consistent with a High Mass X-ray Binary hosting a neutrons star. Subsequently, we propose a new method dedicated to the study of timing data coming from coded mask aperture instruments. Using it on INTEGRAL/ISGRI real data, we detect the presence of periodic and quasi-periodic features in some pulsars and micro-quasars at energies as high as a hundred keV. Finally, we suggest a model designed to describe the low frequency variability of X-ray binaries in their hardest state. This model is based on thermal comptonization of soft photons by a warm corona in which a pressure wave is propagating in cylindrical geometry. By computing both numerical simulations and analytical solution, we show that this model should be suitable to describe some of the typical features observed in X-ray binaries power spectra in their hard state and their evolution such as aperiodic noise and low frequency quasi-periodic oscillations. (author) [fr
Effective-one-body waveforms for binary neutron stars using surrogate models
Lackey, Benjamin D.; Bernuzzi, Sebastiano; Galley, Chad R.; Meidam, Jeroen; Van Den Broeck, Chris
2017-05-01
Gravitational-wave observations of binary neutron star systems can provide information about the masses, spins, and structure of neutron stars. However, this requires accurate and computationally efficient waveform models that take ≲1 s to evaluate for use in Bayesian parameter estimation codes that perform 1 07- 1 08 waveform evaluations. We present a surrogate model of a nonspinning effective-one-body waveform model with ℓ=2 , 3, and 4 tidal multipole moments that reproduces waveforms of binary neutron star numerical simulations up to merger. The surrogate is built from compact sets of effective-one-body waveform amplitude and phase data that each form a reduced basis. We find that 12 amplitude and 7 phase basis elements are sufficient to reconstruct any binary neutron star waveform with a starting frequency of 10 Hz. The surrogate has maximum errors of 3.8% in amplitude (0.04% excluding the last 100 M before merger) and 0.043 rad in phase. This leads to typical mismatches of 10-5-10-4 for Advanced LIGO depending on the component masses, with a worst case match of 7 ×10-4 when both stars have masses ≥2 M⊙. The version implemented in the LIGO Algorithm Library takes ˜0.07 s to evaluate for a starting frequency of 30 Hz and ˜0.8 s for a starting frequency of 10 Hz, resulting in a speed-up factor of O (1 03) relative to the original matlab code. This allows parameter estimation codes to run in days to weeks rather than years, and we demonstrate this with a nested sampling run that recovers the masses and tidal parameters of a simulated binary neutron star system.
A deterministic model for the growth of non-conducting electrical tree structures
Dodd, S J
2003-01-01
Electrical treeing is of interest to the electrical generation, transmission and distribution industries as it is one of the causes of insulation failure in electrical machines, switchgear and transformer bushings. In this paper a deterministic electrical tree growth model is described. The model is based on electrostatics and local electron avalanches to model partial discharge activity within the growing tree structure. Damage to the resin surrounding the tree structure is dependent on the local electrostatic energy dissipation by partial discharges within the tree structure and weighted by the magnitudes of the local electric fields in the resin surrounding the tree structure. The model is successful in simulating the formation of branched structures without the need of a random variable, a requirement of previous stochastic models. Instability in the spatial development of partial discharges within the tree structure takes the role of the stochastic element as used in previous models to produce branched t...
Herguido, Estela; Pulido, Manuel; Francisco Lavado Contador, Joaquín; Schnabel, Susanne
2017-04-01
In Iberian dehesas and montados, the lack of tree recruitment compromises its long-term sustainability. However, in marginal areas of dehesas shrub encroachment facilitates tree recruitment while altering the distinctive physiognomic and cultural characteristics of the system. These are ongoing processes that should be considered when designing afforestation measures and policies. Based on spatial variables, we modeled the proneness of a piece of land to undergo tree recruitment and the results were related with the afforestation measures carried out under the UE First Afforestation Agricultural Land Program between 1992 and 2008. We analyzed the temporal tree population dynamics in 800 randomly selected plots of 100 m radius (2,510 ha in total) in dehesas and treeless pasturelands of Extremadura (hereafter rangelands). Tree changes were revealed by comparing aerial images taken in 1956 with orthophotographs and infrared ones from 2012. Spatial models that predict the areas prone either to lack tree recruitment or with recruitment were developed and based on three data mining algorithms: MARS (Multivariate Adaptive Regression Splines), Random Forest (RF) and Stochastic Gradient Boosting (Tree-Net, TN). Recruited-tree locations (1) vs. locations of places with no recruitment (0) (randomly selected from the study areas) were used as the binary dependent variable. A 5% of the data were used as test data set. As candidate explanatory variables we used 51 different topographic, climatic, bioclimatic, land cover-related and edaphic ones. The statistical models developed were extrapolated to the spatial context of the afforested areas in the region and also to the whole Extremenian rangelands, and the percentage of area modelled as prone to tree recruitment was calculated for each case. A total of 46,674.63 ha were afforested with holm oak (Quercus ilex) or cork oak (Quercus suber) in the studied rangelands under the UE First Afforestation Agricultural Land Program. In
Measurement and modelling of hydrogen bonding in 1-alkanol plus n-alkane binary mixtures
DEFF Research Database (Denmark)
von Solms, Nicolas; Jensen, Lars; Kofod, Jonas L.
2007-01-01
Two equations of state (simplified PC-SAFT and CPA) are used to predict the monomer fraction of 1-alkanols in binary mixtures with n-alkanes. It is found that the choice of parameters and association schemes significantly affects the ability of a model to predict hydrogen bonding in mixtures, eve...... studies, which is clarified in the present work. New hydrogen bonding data based on infrared spectroscopy are reported for seven binary mixtures of alcohols and alkanes. (C) 2007 Elsevier B.V. All rights reserved....... though pure-component liquid densities and vapour pressures are predicted equally accurately for the associating compound. As was the case in the study of pure components, there exists some confusion in the literature about the correct interpretation and comparison of experimental data and theoretical...
A re-examination of thermodynamic modelling of U-Ru binary phase diagram
Energy Technology Data Exchange (ETDEWEB)
Wang, L.C.; Kaye, M.H., E-mail: matthew.kaye@uoit.ca [University of Ontario Institute of Technology, Oshawa, ON (Canada)
2015-07-01
Ruthenium (Ru) is one of the more abundant fission products (FPs) both in fast breeder reactors and thermal reactors. Post irradiation examinations (PIE) show that both 'the white metallic phase' (MoTc-Ru-Rh-Pd) and 'the other metallic phase' (U(Pd-Rh-Ru)3) are present in spent nuclear fuels. To describe this quaternary system, binary subsystems of uranium (U) with Pd, Rh, and Ru are necessary. Presently, only the U-Ru system has been thermodynamically described but with some problems. As part of research on U-Ru-Rh-Pd quaternary system, an improved consistent thermodynamic model describing the U-Ru binary phase diagram has been obtained. (author)
A New Simplified Local Density Model for Adsorption of Pure Gases and Binary Mixtures
Hasanzadeh, M.; Dehghani, M. R.; Feyzi, F.; Behzadi, B.
2010-12-01
Adsorption modeling is an important tool for process simulation and design. Many theoretical models have been developed to describe adsorption data for pure and multicomponent gases. The simplified local density (SLD) approach is a thermodynamic model that can be used with any equation of state and offers some predictive capability with adjustable parameters for modeling of slit-shaped pores. In previous studies, the SLD model has been utilized with the Lennard-Jones potential function for modeling of fluid-solid interactions. In this article, we have focused on application of the Sutherland potential function in an SLD-Peng-Robinson model. The advantages and disadvantages of using the new potential function for adsorption of methane, ethane, carbon dioxide, nitrogen, and three binary mixtures on two types of activated carbon are illustrated. The results have been compared with previous models. It is shown that the new SLD model can correlate adsorption data for different pressures and temperatures with minimum error.
On models of the genetic code generated by binary dichotomic algorithms.
Gumbel, Markus; Fimmel, Elena; Danielli, Alberto; Strüngmann, Lutz
2015-02-01
In this paper we introduce the concept of a BDA-generated model of the genetic code which is based on binary dichotomic algorithms (BDAs). A BDA-generated model is based on binary dichotomic algorithms (BDAs). Such a BDA partitions the set of 64 codons into two disjoint classes of size 32 each and provides a generalization of known partitions like the Rumer dichotomy. We investigate what partitions can be generated when a set of different BDAs is applied sequentially to the set of codons. The search revealed that these models are able to generate code tables with very different numbers of classes ranging from 2 to 64. We have analyzed whether there are models that map the codons to their amino acids. A perfect matching is not possible. However, we present models that describe the standard genetic code with only few errors. There are also models that map all 64 codons uniquely to 64 classes showing that BDAs can be used to identify codons precisely. This could serve as a basis for further mathematical analysis using coding theory, for example. The hypothesis that BDAs might reflect a molecular mechanism taking place in the decoding center of the ribosome is discussed. The scan demonstrated that binary dichotomic partitions are able to model different aspects of the genetic code very well. The search was performed with our tool Beady-A. This software is freely available at http://mi.informatik.hs-mannheim.de/beady-a. It requires a JVM version 6 or higher. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Meta-analysis of studies with bivariate binary outcomes: a marginal beta-binomial model approach.
Chen, Yong; Hong, Chuan; Ning, Yang; Su, Xiao
2016-01-15
When conducting a meta-analysis of studies with bivariate binary outcomes, challenges arise when the within-study correlation and between-study heterogeneity should be taken into account. In this paper, we propose a marginal beta-binomial model for the meta-analysis of studies with binary outcomes. This model is based on the composite likelihood approach and has several attractive features compared with the existing models such as bivariate generalized linear mixed model (Chu and Cole, 2006) and Sarmanov beta-binomial model (Chen et al., 2012). The advantages of the proposed marginal model include modeling the probabilities in the original scale, not requiring any transformation of probabilities or any link function, having closed-form expression of likelihood function, and no constraints on the correlation parameter. More importantly, because the marginal beta-binomial model is only based on the marginal distributions, it does not suffer from potential misspecification of the joint distribution of bivariate study-specific probabilities. Such misspecification is difficult to detect and can lead to biased inference using currents methods. We compare the performance of the marginal beta-binomial model with the bivariate generalized linear mixed model and the Sarmanov beta-binomial model by simulation studies. Interestingly, the results show that the marginal beta-binomial model performs better than the Sarmanov beta-binomial model, whether or not the true model is Sarmanov beta-binomial, and the marginal beta-binomial model is more robust than the bivariate generalized linear mixed model under model misspecifications. Two meta-analyses of diagnostic accuracy studies and a meta-analysis of case-control studies are conducted for illustration. Copyright © 2015 John Wiley & Sons, Ltd.
Study on competitive interaction models in Cayley tree
International Nuclear Information System (INIS)
Moreira, J.G.M.A.
1987-12-01
We propose two kinds of models in the Cayley tree to simulate Ising models with axial anisotropy in the cubic lattice. The interaction in the direction of the anisotropy is simulated by the interaction along the branches of the tree. The interaction in the planes perpendicular to the anisotropy direction, in the first model, is simulated by interactions between spins in neighbour branches of the same generation arising from same site of the previous generation. In the second model, the simulation of the interaction in the planes are produced by mean field interactions among all spins in sites of the same generation arising from the same site of the previous generations. We study these models in the limit of infinite coordination number. First, we analyse a situation with antiferromagnetic interactions along the branches between first neighbours only, and we find the analogous of a metamagnetic Ising model. In the following, we introduce competitive interactions between first and second neighbours along the branches, to simulate the ANNNI model. We obtain one equation of differences which relates the magnetization of one generation with the magnetization of the two previous generations, to permit a detailed study of the modulated phase region. We note that the wave number of the modulation, for one fixed temperature, changes with the competition parameter to form a devil's staircase with a fractal dimension which increases with the temperature. We discuss the existence of strange atractors, related to a possible caothic phase. Finally, we show the obtained results when we consider interactions along the branches with three neighbours. (author)
International Nuclear Information System (INIS)
Fang Zheng; Qiu Guanzhou
2007-01-01
A metallic solution model with adjustable parameter k has been developed to predict thermodynamic properties of ternary systems from those of its constituent three binaries. In the present model, the excess Gibbs free energy for a ternary mixture is expressed as a weighted probability sum of those of binaries and the k value is determined based on an assumption that the ternary interaction generally strengthens the mixing effects for metallic solutions with weak interaction, making the Gibbs free energy of mixing of the ternary system more negative than that before considering the interaction. This point is never considered in the models currently reported, where the only difference in a geometrical definition of molar values of components is considered that do not involve thermodynamic principles but are completely empirical. The current model describes the results of experiments very well, and by adjusting the k value also agrees with those from models used widely in the literature. Three ternary systems, Mg-Cu-Ni, Zn-In-Cd, and Cd-Bi-Pb are recalculated to demonstrate the method of determining k and the precision of the model. The results of the calculations, especially those in Mg-Cu-Ni system, are better than those predicted by the current models in the literature
Directory of Open Access Journals (Sweden)
Hiekata Takashi
2006-01-01
Full Text Available A new two-stage blind source separation (BSS method for convolutive mixtures of speech is proposed, in which a single-input multiple-output (SIMO-model-based independent component analysis (ICA and a new SIMO-model-based binary masking are combined. SIMO-model-based ICA enables us to separate the mixed signals, not into monaural source signals but into SIMO-model-based signals from independent sources in their original form at the microphones. Thus, the separated signals of SIMO-model-based ICA can maintain the spatial qualities of each sound source. Owing to this attractive property, our novel SIMO-model-based binary masking can be applied to efficiently remove the residual interference components after SIMO-model-based ICA. The experimental results reveal that the separation performance can be considerably improved by the proposed method compared with that achieved by conventional BSS methods. In addition, the real-time implementation of the proposed BSS is illustrated.
New approach in modeling Cr(VI) sorption onto biomass from metal binary mixtures solutions
Energy Technology Data Exchange (ETDEWEB)
Liu, Chang [College of Environmental Science and Engineering, Anhui Normal University, South Jiuhua Road, 189, 241002 Wuhu (China); Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Fiol, Núria [Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Villaescusa, Isabel, E-mail: Isabel.Villaescusa@udg.edu [Chemical Engineering Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain); Poch, Jordi [Applied Mathematics Department, Escola Politècnica Superior, Universitat de Girona, Ma Aurèlia Capmany, 61, 17071 Girona (Spain)
2016-01-15
In the last decades Cr(VI) sorption equilibrium and kinetic studies have been carried out using several types of biomasses. However there are few researchers that consider all the simultaneous processes that take place during Cr(VI) sorption (i.e., sorption/reduction of Cr(VI) and simultaneous formation and binding of reduced Cr(III)) when formulating a model that describes the overall sorption process. On the other hand Cr(VI) scarcely exists alone in wastewaters, it is usually found in mixtures with divalent metals. Therefore, the simultaneous removal of Cr(VI) and divalent metals in binary mixtures and the interactive mechanism governing Cr(VI) elimination have gained more and more attention. In the present work, kinetics of Cr(VI) sorption onto exhausted coffee from Cr(VI)–Cu(II) binary mixtures has been studied in a stirred batch reactor. A model including Cr(VI) sorption and reduction, Cr(III) sorption and the effect of the presence of Cu(II) in these processes has been developed and validated. This study constitutes an important advance in modeling Cr(VI) sorption kinetics especially when chromium sorption is in part based on the sorbent capacity of reducing hexavalent chromium and a metal cation is present in the binary mixture. - Highlights: • A kinetic model including Cr(VI) reduction, Cr(VI) and Cr(III) sorption/desorption • Synergistic effect of Cu(II) on Cr(VI) elimination included in the model • Model validation by checking it against independent sets of data.
Susan L. King
2003-01-01
The performance of two classifiers, logistic regression and neural networks, are compared for modeling noncatastrophic individual tree mortality for 21 species of trees in West Virginia. The output of the classifier is usually a continuous number between 0 and 1. A threshold is selected between 0 and 1 and all of the trees below the threshold are classified as...
Brown, Molly E.; McGroddy, Megan; Spence, Caitlin; Flake, Leah; Sarfraz, Amna; Nowak, David J.; Milesi, Cristina
2012-01-01
As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.
Spatially-explicit models of global tree density
Glick, Henry B.; Bettigole, Charlie; Maynard, Daniel S.; Covey, Kristofer R.; Smith, Jeffrey R.; Crowther, Thomas W.
2016-01-01
Remote sensing and geographic analysis of woody vegetation provide means of evaluating the distribution of natural resources, patterns of biodiversity and ecosystem structure, and socio-economic drivers of resource utilization. While these methods bring geographic datasets with global coverage into our day-to-day analytic spheres, many of the studies that rely on these strategies do not capitalize on the extensive collection of existing field data. We present the methods and maps associated with the first spatially-explicit models of global tree density, which relied on over 420,000 forest inventory field plots from around the world. This research is the result of a collaborative effort engaging over 20 scientists and institutions, and capitalizes on an array of analytical strategies. Our spatial data products offer precise estimates of the number of trees at global and biome scales, but should not be used for local-level estimation. At larger scales, these datasets can contribute valuable insight into resource management, ecological modelling efforts, and the quantification of ecosystem services. PMID:27529613
DEVELOPMENT OF INDIVIDUAL TREE GROWTH MODELS BASED ON DIFFERENTIAL EQUATIONS
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Breno Rodrigues Mendes
2006-09-01
Full Text Available This study generate individual tree non-linear models from differential equation and evaluated the adjustment quality to express the basal area growth. The data base is from continuous forest inventory of clonal Eucalyptus spp. plantations, given by Aracruz Cellulose Company, located in the Brazilian costal region, Bahia and Espirito Santo states. The model precision was verified by ratio likelihood test, by mean square error (MSE and by graphical residual analysis. The results showed that the complete model with 3 parameters, developed from the original model with one regressor, was superior to the other models, due to the inclusion of stand based variables, such as: clone, total height (HT, dominant height (HD, quadratic diameter (Dg, Basal Area (G, site index (IS and Density (N, generating a new model, called Complete Model III. The improvement of the precision was highly significant when compared to another models. Consequently, this model provides information with a high degree of precision and accuracy for the forest companies planning.
Blackman, Jonathan; Field, Scott E; Galley, Chad R; Szilágyi, Béla; Scheel, Mark A; Tiglio, Manuel; Hemberger, Daniel A
2015-09-18
Simulating a binary black hole coalescence by solving Einstein's equations is computationally expensive, requiring days to months of supercomputing time. Using reduced order modeling techniques, we construct an accurate surrogate model, which is evaluated in a millisecond to a second, for numerical relativity (NR) waveforms from nonspinning binary black hole coalescences with mass ratios in [1, 10] and durations corresponding to about 15 orbits before merger. We assess the model's uncertainty and show that our modeling strategy predicts NR waveforms not used for the surrogate's training with errors nearly as small as the numerical error of the NR code. Our model includes all spherical-harmonic _{-2}Y_{ℓm} waveform modes resolved by the NR code up to ℓ=8. We compare our surrogate model to effective one body waveforms from 50M_{⊙} to 300M_{⊙} for advanced LIGO detectors and find that the surrogate is always more faithful (by at least an order of magnitude in most cases).
Reconstruction of binary geological images using analytical edge and object models
Abdollahifard, Mohammad J.; Ahmadi, Sadegh
2016-04-01
Reconstruction of fields using partial measurements is of vital importance in different applications in geosciences. Solving such an ill-posed problem requires a well-chosen model. In recent years, training images (TI) are widely employed as strong prior models for solving these problems. However, in the absence of enough evidence it is difficult to find an adequate TI which is capable of describing the field behavior properly. In this paper a very simple and general model is introduced which is applicable to a fairly wide range of binary images without any modifications. The model is motivated by the fact that nearly all binary images are composed of simple linear edges in micro-scale. The analytic essence of this model allows us to formulate the template matching problem as a convex optimization problem having efficient and fast solutions. The model has the potential to incorporate the qualitative and quantitative information provided by geologists. The image reconstruction problem is also formulated as an optimization problem and solved using an iterative greedy approach. The proposed method is capable of recovering the image unknown values with accuracies about 90% given samples representing as few as 2% of the original image.
An Odor Interaction Model of Binary Odorant Mixtures by a Partial Differential Equation Method
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Luchun Yan
2014-07-01
Full Text Available A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE method. Based on the measurement method (tangent-intercept method of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture’s odor intensity to the individual odorant’s relative odor activity value (OAV. Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.
An odor interaction model of binary odorant mixtures by a partial differential equation method.
Yan, Luchun; Liu, Jiemin; Wang, Guihua; Wu, Chuandong
2014-07-09
A novel odor interaction model was proposed for binary mixtures of benzene and substituted benzenes by a partial differential equation (PDE) method. Based on the measurement method (tangent-intercept method) of partial molar volume, original parameters of corresponding formulas were reasonably displaced by perceptual measures. By these substitutions, it was possible to relate a mixture's odor intensity to the individual odorant's relative odor activity value (OAV). Several binary mixtures of benzene and substituted benzenes were respectively tested to establish the PDE models. The obtained results showed that the PDE model provided an easily interpretable method relating individual components to their joint odor intensity. Besides, both predictive performance and feasibility of the PDE model were proved well through a series of odor intensity matching tests. If combining the PDE model with portable gas detectors or on-line monitoring systems, olfactory evaluation of odor intensity will be achieved by instruments instead of odor assessors. Many disadvantages (e.g., expense on a fixed number of odor assessors) also will be successfully avoided. Thus, the PDE model is predicted to be helpful to the monitoring and management of odor pollutions.
Macroscopic Models of Clique Tree Growth for Bayesian Networks
National Aeronautics and Space Administration — In clique tree clustering, inference consists of propagation in a clique tree compiled from a Bayesian network. In this paper, we develop an analytical approach to...
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Sean M. Lamb
2018-03-01
Full Text Available A method to forecast forest inventory variables derived from light detection and ranging (LiDAR would increase the usefulness of such data in future forest management. We evaluated the accuracy of forecasted inventory from imputed tree lists for LiDAR grid cells (20 × 20 m in spruce (Picea sp. plantations and tree growth predicted using a locally calibrated tree-list growth model. Tree lists were imputed by matching measurements from a library of sample plots with grid cells based on planted species and the smallest sum of squared difference between six inventory variables. Total and merchantable basal area, total and merchantable volume, Lorey’s height, and quadratic mean diameter increments predicted using imputed tree lists were highly correlated (0.75–0.86 with those from measured tree lists in 98 validation plots. Percent root mean squared error ranged from 12.8–49.0% but was much lower (4.9–13.5% for plots with ≤10% LiDAR-derived error for all plot-matched variables. When compared with volumes from 15 blocks harvested 3–5 years after LiDAR acquisition, average forecasted volume differed by only 1.5%. To demonstrate the novel application of this method for operational management decisions, annual commercial thinning was planned at grid-cell resolution from 2018–2020 using forecasted inventory variables and commercial thinning eligibility rules.
The Use of Function/Means Trees for Modelling Technical, Semantic and Business Functions
DEFF Research Database (Denmark)
Robotham, Antony John
2000-01-01
This paper considers the feasibility of using the function/means tree to create a single tree for a complete motor vehicle. It is argued that function/means trees can be used for modelling technical and semantic functions, but it is an inappropriate method for business functions when one tree...... of the vehicle is required. Life cycle modelling provides an effective means for determining all the required purpose functions and is considered a more effective method than the function/means tree for this task when the structure and mode of operation of the vehicle is well defined and understood....
Wang, Jing; Li, Man; Hu, Yun-tao; Zhu, Yu
2009-09-14
In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients. Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN) and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes. After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608) and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806). The predictive ability and adaptive capacity of ANN model were better than those of decision tree model. ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.
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Hu Yun-tao
2009-09-01
Full Text Available Abstract Background In recent years, artificial neural network is advocated in modeling complex multivariable relationships due to its ability of fault tolerance; while decision tree of data mining technique was recommended because of its richness of classification arithmetic rules and appeal of visibility. The aim of our research was to compare the performance of ANN and decision tree models in predicting hospital charges on gastric cancer patients. Methods Data about hospital charges on 1008 gastric cancer patients and related demographic information were collected from the First Affiliated Hospital of Anhui Medical University from 2005 to 2007 and preprocessed firstly to select pertinent input variables. Then artificial neural network (ANN and decision tree models, using same hospital charge output variable and same input variables, were applied to compare the predictive abilities in terms of mean absolute errors and linear correlation coefficients for the training and test datasets. The transfer function in ANN model was sigmoid with 1 hidden layer and three hidden nodes. Results After preprocess of the data, 12 variables were selected and used as input variables in two types of models. For both the training dataset and the test dataset, mean absolute errors of ANN model were lower than those of decision tree model (1819.197 vs. 2782.423, 1162.279 vs. 3424.608 and linear correlation coefficients of the former model were higher than those of the latter (0.955 vs. 0.866, 0.987 vs. 0.806. The predictive ability and adaptive capacity of ANN model were better than those of decision tree model. Conclusion ANN model performed better in predicting hospital charges of gastric cancer patients of China than did decision tree model.
Modeling effects of overstory density and competing vegetation on tree height growth
Christian Salas; Albert R. Stage; Andrew P. Robinson
2007-01-01
We developed and evaluated an individual-tree height growth model for Douglas-fir [Pseudotsuga menziesii (Mirbel) Franco] in the Inland Northwest United States. The model predicts growth for all tree sizes continuously, rather than requiring a transition between independent models for juvenile and mature growth phases. The model predicts the effects...
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P. Y. Dibal
2015-08-01
Full Text Available The design of binary multipliers is a critical aspect of any reliable hardware in computing and computer engineering. In this paper, the design of a 4 bit binary multiplier has been undertaken, starting with a review of the importance of binary multipliers and wide areas of application. The paper then presents the multiplication methodology which involves an accumulator, a full adder, and a control circuit. The accumulator and full adder were designed using VHDL in the Vivado IDE, whereas the control circuit was modelled using the powerful technique of State flow in Simulink. The 4 bit binary multiplier is then modelled and simulated using the combination of Simulink and VHDL. Results obtained from the simulation verified the accuracy of the design methodology.
Bayesian nonparametric meta-analysis using Polya tree mixture models.
Branscum, Adam J; Hanson, Timothy E
2008-09-01
Summary. A common goal in meta-analysis is estimation of a single effect measure using data from several studies that are each designed to address the same scientific inquiry. Because studies are typically conducted in geographically disperse locations, recent developments in the statistical analysis of meta-analytic data involve the use of random effects models that account for study-to-study variability attributable to differences in environments, demographics, genetics, and other sources that lead to heterogeneity in populations. Stemming from asymptotic theory, study-specific summary statistics are modeled according to normal distributions with means representing latent true effect measures. A parametric approach subsequently models these latent measures using a normal distribution, which is strictly a convenient modeling assumption absent of theoretical justification. To eliminate the influence of overly restrictive parametric models on inferences, we consider a broader class of random effects distributions. We develop a novel hierarchical Bayesian nonparametric Polya tree mixture (PTM) model. We present methodology for testing the PTM versus a normal random effects model. These methods provide researchers a straightforward approach for conducting a sensitivity analysis of the normality assumption for random effects. An application involving meta-analysis of epidemiologic studies designed to characterize the association between alcohol consumption and breast cancer is presented, which together with results from simulated data highlight the performance of PTMs in the presence of nonnormality of effect measures in the source population.
The effect of error models in the multiscale inversion of binary permeability fields
Ray, J.; Bloemenwaanders, B. V.; McKenna, S. A.; Marzouk, Y. M.
2010-12-01
We present results from a recently developed multiscale inversion technique for binary media, with emphasis on the effect of subgrid model errors on the inversion. Binary media are a useful fine-scale representation of heterogeneous porous media. Averaged properties of the binary field representations can be used to characterize flow through the porous medium at the macroscale. Both direct measurements of the averaged properties and upscaling are complicated and may not provide accurate results. However, it may be possible to infer upscaled properties of the binary medium from indirect measurements at the coarse scale. Multiscale inversion, performed with a subgrid model to connect disparate scales together, can also yield information on the fine-scale properties. We model the binary medium using truncated Gaussian fields, and develop a subgrid model for the upscaled permeability based on excursion sets of those fields. The subgrid model requires an estimate of the proportion of inclusions at the block scale as well as some geometrical parameters of the inclusions as inputs, and predicts the effective permeability. The inclusion proportion is assumed to be spatially varying, modeled using Gaussian processes and represented using a truncated Karhunen-Louve (KL) expansion. This expansion is used, along with the subgrid model, to pose as a Bayesian inverse problem for the KL weights and the geometrical parameters of the inclusions. The model error is represented in two different ways: (1) as a homoscedastic error and (2) as a heteroscedastic error, dependent on inclusion proportionality and geometry. The error models impact the form of the likelihood function in the expression for the posterior density of the objects of inference. The problem is solved using an adaptive Markov Chain Monte Carlo method, and joint posterior distributions are developed for the KL weights and inclusion geometry. Effective permeabilities and tracer breakthrough times at a few
Allometric Models for Estimating Tree Volume and Aboveground Biomass in Lowland Forests of Tanzania
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Wilson Ancelm Mugasha
2016-01-01
Full Text Available Models to assist management of lowland forests in Tanzania are in most cases lacking. Using a sample of 60 trees which were destructively harvested from both dry and wet lowland forests of Dindili in Morogoro Region (30 trees and Rondo in Lindi Region (30 trees, respectively, this study developed site specific and general models for estimating total tree volume and aboveground biomass. Specifically the study developed (i height-diameter (ht-dbh models for trees found in the two sites, (ii total, merchantable, and branches volume models, and (iii total and sectional aboveground biomass models of trees found in the two study sites. The findings show that site specific ht-dbh model appears to be suitable in estimating tree height since the tree allometry was found to differ significantly between studied forests. The developed general volume models yielded unbiased mean prediction error and hence can adequately be applied to estimate tree volume in dry and wet lowland forests in Tanzania. General aboveground biomass model appears to yield biased estimates; hence, it is not suitable when accurate results are required. In this case, site specific biomass allometric models are recommended. Biomass allometric models which include basic wood density are highly recommended for improved estimates accuracy when such information is available.
Symmetrization of excess Gibbs free energy: A simple model for binary liquid mixtures
Energy Technology Data Exchange (ETDEWEB)
Castellanos-Suarez, Aly J., E-mail: acastell@ivic.gob.v [Centro de Estudios Interdisciplinarios de la Fisica (CEIF), Instituto Venezolano de Investigaciones Cientificas (IVIC), Apartado 21827, Caracas 1020A (Venezuela, Bolivarian Republic of); Garcia-Sucre, Maximo, E-mail: mgs@ivic.gob.v [Centro de Estudios Interdisciplinarios de la Fisica (CEIF), Instituto Venezolano de Investigaciones Cientificas (IVIC), Apartado 21827, Caracas 1020A (Venezuela, Bolivarian Republic of)
2011-03-15
A symmetric expression for the excess Gibbs free energy of liquid binary mixtures is obtained using an appropriate definition for the effective contact fraction. We have identified a mechanism of local segregation as the main cause of the contact fraction variation with the concentration. Starting from this mechanism we develop a simple model for describing binary liquid mixtures. In this model two parameters appear: one adjustable, and the other parameter depending on the first one. Following this procedure we reproduce the experimental data of (liquid + vapor) equilibrium with a degree of accuracy comparable to well-known more elaborated models. The way in which we take into account the effective contacts between molecules allows identifying the compound which may be considered to induce one of the following processes: segregation, anti-segregation and dispersion of the components in the liquid mixture. Finally, the simplicity of the model allows one to obtain only one resulting interaction energy parameter, which makes easier the physical interpretation of the results.
Model-free tests of equality in binary data under an incomplete block design.
Lui, Kung-Jong; Zhu, Lixia
2018-02-16
Using Prescott's model-free approach, we develop an asymptotic procedure and an exact procedure for testing equality between treatments with binary responses under an incomplete block crossover design. We employ Monte Carlo simulation and note that these test procedures can not only perform well in small-sample cases but also outperform the corresponding test procedures accounting for only patients with discordant responses published elsewhere. We use the data taken as a part of the crossover trial comparing two different doses of an analgesic with placebo for the relief of primary dysmenorrhea to illustrate the use of test procedures discussed here.
Goal-oriented error estimation for Cahn-Hilliard models of binary phase transition
van der Zee, Kristoffer G.
2010-10-27
A posteriori estimates of errors in quantities of interest are developed for the nonlinear system of evolution equations embodied in the Cahn-Hilliard model of binary phase transition. These involve the analysis of wellposedness of dual backward-in-time problems and the calculation of residuals. Mixed finite element approximations are developed and used to deliver numerical solutions of representative problems in one- and two-dimensional domains. Estimated errors are shown to be quite accurate in these numerical examples. © 2010 Wiley Periodicals, Inc.
Tree Branching: Leonardo da Vinci's Rule versus Biomechanical Models
Minamino, Ryoko; Tateno, Masaki
2014-01-01
This study examined Leonardo da Vinci's rule (i.e., the sum of the cross-sectional area of all tree branches above a branching point at any height is equal to the cross-sectional area of the trunk or the branch immediately below the branching point) using simulations based on two biomechanical models: the uniform stress and elastic similarity models. Model calculations of the daughter/mother ratio (i.e., the ratio of the total cross-sectional area of the daughter branches to the cross-sectional area of the mother branch at the branching point) showed that both biomechanical models agreed with da Vinci's rule when the branching angles of daughter branches and the weights of lateral daughter branches were small; however, the models deviated from da Vinci's rule as the weights and/or the branching angles of lateral daughter branches increased. The calculated values of the two models were largely similar but differed in some ways. Field measurements of Fagus crenata and Abies homolepis also fit this trend, wherein models deviated from da Vinci's rule with increasing relative weights of lateral daughter branches. However, this deviation was small for a branching pattern in nature, where empirical measurements were taken under realistic measurement conditions; thus, da Vinci's rule did not critically contradict the biomechanical models in the case of real branching patterns, though the model calculations described the contradiction between da Vinci's rule and the biomechanical models. The field data for Fagus crenata fit the uniform stress model best, indicating that stress uniformity is the key constraint of branch morphology in Fagus crenata rather than elastic similarity or da Vinci's rule. On the other hand, mechanical constraints are not necessarily significant in the morphology of Abies homolepis branches, depending on the number of daughter branches. Rather, these branches were often in agreement with da Vinci's rule. PMID:24714065
Characterization of an alpine tree line using airborne LiDAR data and physiological modeling.
Coops, Nicholas C; Morsdorf, Felix; Schaepman, Michael E; Zimmermann, Niklaus E
2013-12-01
Understanding what environmental drivers control the position of the alpine tree line is important for refining our understanding of plant stress and tree development, as well as for climate change studies. However, monitoring the location of the tree line position and potential movement is difficult due to cost and technical challenges, as well as a lack of a clear boundary. Advanced remote sensing technologies such as Light Detection and Ranging (LiDAR) offer significant potential to map short individual tree crowns within the transition zone despite the lack of predictive capacity. Process-based forest growth models offer a complementary approach by quantifying the environmental stresses trees experience at the tree line, allowing transition zones to be defined and ultimately mapped. In this study, we investigate the role remote sensing and physiological, ecosystem-based modeling can play in the delineation of the alpine tree line. To do so, we utilize airborne LiDAR data to map tree height and stand density across a series of altitudinal gradients from below to above the tree line within the Swiss National Park (SNP), Switzerland. We then utilize a simple process-based model to assess the importance of seasonal variations on four climatically related variables that impose non-linear constraints on photosynthesis. Our results indicate that all methods predict the tree line to within a 50 m altitudinal zone and indicate that aspect is not a driver of significant variations in tree line position in the region. Tree cover, rather than tree height is the main discriminator of the tree line at higher elevations. Temperatures in fall and spring are responsible for the major differences along altitudinal zones, however, changes in evaporative demand also control plant growth at lower altitudes. Our results indicate that the two methods provide complementary information on tree line location and, when combined, provide additional insights into potentially endangered
U.S. Environmental Protection Agency — Spreadsheets are included here to support the manuscript "Boosted Regression Tree Models to Explain Watershed Nutrient Concentrations and Biological Condition". This...
3D Modeling of Forbidden Line Emission in the Binary Wind Interaction Region of Eta Carinae
Madura, Thomas; Gull, T. R.; Owocki, S.; Okazaki, A. T.; Russell, C. M. P.
2010-01-01
We present recent work using three-dimensional (3D) Smoothed Particle Hydrodynamics (SPH) simulations to model the high ([Fe III], [Ar III], [Ne III] and [S III]) and low ([Fe II], [Ni II]) ionization forbidden emission lines observed in Eta Carinae using the HST/STIS. These structures are interpreted as the time-averaged, outer extensions of the primary wind and the wind-wind interaction region directly excited by the FUV of the hot companion star of this massive binary system. We discuss how analyzing the results of the 3D SPH simulations and synthetic slit spectra and comparing them to the spectra obtained with the HST/STIS helps us determine the absolute orientation of the binary orbit and helps remove the degeneracy inherent to models based solely on the observed RXTE X-ray light curve. A key point of this work is that spatially resolved observations like those with HST/STIS and comparison to 3D models are necessary to determine the alignment or misalignment of the orbital angular momentum axis with the Homunculus, or correspondingly, the alignment of the orbital plane with the Homunculus skirt.
Tree-Based Global Model Tests for Polytomous Rasch Models
Komboz, Basil; Strobl, Carolin; Zeileis, Achim
2018-01-01
Psychometric measurement models are only valid if measurement invariance holds between test takers of different groups. Global model tests, such as the well-established likelihood ratio (LR) test, are sensitive to violations of measurement invariance, such as differential item functioning and differential step functioning. However, these…
DEFF Research Database (Denmark)
Kheir, Rania Bou; Greve, Mogens Humlekrog; Bøcher, Peder Klith
2010-01-01
) selected pairs of parameters, (vi) soil type, parent material and landscape type only, and (vii) the parameters having a high impact on SOC distribution in built pruned trees. The best constructed classification tree models (in the number of three) with the lowest misclassification error (ME......) and the lowest number of nodes (N) as well are: (i) the tree (T1) combining all of the parameters (ME ¼ 29.5%; N¼ 54); (ii) the tree (T2) based on the parent material, soil type and landscape type (ME¼ 31.5%; N ¼ 14); and (iii) the tree (T3) constructed using parent material, soil type, landscape type, elevation...
USAHA PENINGKATAN PRODUKTIVITAS DENGAN PRODUCTIVITY EVALUATION TREE (PET MODELS
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Muchlison Anis
2007-04-01
Full Text Available Usaha peningkatan produktivitas merupakan suatu langkah menuju perbaikan perusahaan dimasa yang akan datang. Model perencanaan produktivitas Productivity Evaluation Tree (PET memberikan kemudahan bagi perusahaan dalam mengembangkan dan menilai seluruh alternatif yang mungkin dilakukan dalam menetapkan target peningkatan produktivitas dan usaha peningkatan produktivitas. Dalam penelitian ini alternatif perencanaan ada tiga. Pertama, meningkatkan standart penggunaan bahan baku dari 20% menjadi 30%. Kedua, pengeluaran bahan baku diusulkan sama dengan bulan lalu dengan menerapkan peningkatan standart penggunaan bahan baku sama seperti dengan alternatif pertama, Ketiga, menstimulasi alternatif 2 dengan melakukan manajemen motivasi terhadap tenaga kerja. Dari hasil evaluasi pohon produktivitas maka dapat diketahui estimasi peningkatan produktivitas yang tertinggi adalah alternatif ke tiga dengan perubahan tingkat produktivitas sebesar 0,39.
Effects of uncertainty in model predictions of individual tree volume on large area volume estimates
Ronald E. McRoberts; James A. Westfall
2014-01-01
Forest inventory estimates of tree volume for large areas are typically calculated by adding model predictions of volumes for individual trees. However, the uncertainty in the model predictions is generally ignored with the result that the precision of the large area volume estimates is overestimated. The primary study objective was to estimate the effects of model...
Case Study on High Dimensional Data Analysis Using Decision Tree Model
Smitha.T; V.Sundaram
2012-01-01
The major aspire of this paper is to build a model to predict the chances of occurrences of disease in an area. This paper mainly concentrating the data mining technique-Decision tree model to identify the significant parameters for prediction process. The decision tree model created with the help of ID3 algorithm.
Effects of lightning on trees: A predictive model based on in situ electrical resistivity.
Gora, Evan M; Bitzer, Phillip M; Burchfield, Jeffrey C; Schnitzer, Stefan A; Yanoviak, Stephen P
2017-10-01
The effects of lightning on trees range from catastrophic death to the absence of observable damage. Such differences may be predictable among tree species, and more generally among plant life history strategies and growth forms. We used field-collected electrical resistivity data in temperate and tropical forests to model how the distribution of power from a lightning discharge varies with tree size and identity, and with the presence of lianas. Estimated heating density (heat generated per volume of tree tissue) and maximum power (maximum rate of heating) from a standardized lightning discharge differed 300% among tree species. Tree size and morphology also were important; the heating density of a hypothetical 10 m tall Alseis blackiana was 49 times greater than for a 30 m tall conspecific, and 127 times greater than for a 30 m tall Dipteryx panamensis . Lianas may protect trees from lightning by conducting electric current; estimated heating and maximum power were reduced by 60% (±7.1%) for trees with one liana and by 87% (±4.0%) for trees with three lianas. This study provides the first quantitative mechanism describing how differences among trees can influence lightning-tree interactions, and how lianas can serve as natural lightning rods for trees.
Shu, Min; Zhu, Liang; Wang, Yan-fei; Yang, Jing; Wang, Liyu; Yang, Libin; Zhao, Xiaoyu; Du, Wei
2018-01-01
The solubility and dissolution thermodynamic properties of raspberry ketone in a set of binary solvent mixtures (ethanol + water) with different compositions were experimentally determined by static gravimetrical method in the temperature range of 283.15-313.15 K at 0.10 MPa. The solubility of raspberry ketone in this series of ethanol/water binary solvent mixtures was found to increase with a rise in temperature and the rising mole fraction of ethanol in binary solvent mixtures. The van't Hoff, modified Apelblat and 3D Jouyban-Acree-van't Hoff equations were increasingly applied to correlate the solubility in ethanol/water binary solvent mixtures. The former two models could reach better fitting results with the solubility data, while the 3D model can be comprehensively used to estimate the solubility data in all the ratios of ethanol and water in binary solvent mixtures at random temperature. Furthermore, the changes of dissolution thermodynamic properties of raspberry ketone in experimental ethanol/water solvent mixtures were obtained by van't Hoff equation. For all the above experiments, these dissolution processes of raspberry ketone in experimental ethanol/water binary solvent mixtures were estimated to be endothermic and enthalpy-driven.
Thomas C. Edwards; D. Richard Cutler; Niklaus E. Zimmermann; Linda Geiser; Gretchen G. Moisen
2006-01-01
We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by...
Modelling the influence of tree removal on embankment slope hydrology
Briggs, Kevin; Smethurst, Joel; Powrie, William
2014-01-01
Trees cover the slopes of many railway earthworks supporting the UK’s transport network. Root water uptake by trees can cause seasonal shrinkage and swelling of the embankment soil, affecting the line and level of the railway track. This requires continual maintenance to maintain the serviceability of the track and reduce train speed restrictions. However, the removal of trees from railway embankment slopes and the loss of soil suctions generated by root water uptake may negatively impact emb...
Modeling the transport of nanoparticle-filled binary fluids through micropores.
Ma, Yongting; Bhattacharya, Amitabh; Kuksenok, Olga; Perchak, Dennis; Balazs, Anna C
2012-08-07
Understanding the transport of multicomponent fluids through porous medium is of great importance for a number of technological applications, ranging from ink jet printing and the production of textiles to enhanced oil recovery. The process of capillary filling is relatively well understood for a single-component fluid; much less attention, however, has been devoted to investigating capillary filling processes that involve multiphase fluids, and especially nanoparticle-filled fluids. Here, we examine the behavior of binary fluids containing nanoparticles that are driven by capillary forces to fill well-defined pores or microchannels. To carry out these studies, we use a hybrid computational approach that combines the lattice Boltzmann model for binary fluids with a Brownian dynamics model for the nanoparticles. This hybrid approach allows us to capture the interactions among the fluids, nanoparticles, and pore walls. We show that the nanoparticles can dynamically alter the interfacial tension between the two fluids and the contact angle at the pore walls; this, in turn, strongly affects the dynamics of the capillary filling. We demonstrate that by tailoring the wetting properties of the nanoparticles, one can effectively control the filling velocities. Our findings provide fundamental insights into the dynamics of this complex multicomponent system, as well as potential guidelines for a number of technological processes that involve capillary filling with nanoparticles in porous media.
Modeling and analysis of periodic orbits around a contact binary asteroid
Feng, Jinglang; Noomen, Ron; Visser, Pieter N. A. M.; Yuan, Jianping
2015-06-01
The existence and characteristics of periodic orbits (POs) in the vicinity of a contact binary asteroid are investigated with an averaged spherical harmonics model. A contact binary asteroid consists of two components connected to each other, resulting in a highly bifurcated shape. Here, it is represented by a combination of an ellipsoid and a sphere. The gravitational field of this configuration is for the first time expanded into a spherical harmonics model up to degree and order 8. Compared with the exact potential, the truncation at degree and order 4 is found to introduce an error of less than 10 % at the circumscribing sphere and less than 1 % at a distance of the double of the reference radius. The Hamiltonian taking into account harmonics up to degree and order 4 is developed. After double averaging of this Hamiltonian, the model is reduced to include zonal harmonics only and frozen orbits are obtained. The tesseral terms are found to introduce significant variations on the frozen orbits and distort the frozen situation. Applying the method of Poincaré sections, phase space structures of the single-averaged model are generated for different energy levels and rotation rates of the asteroid, from which the dynamics driven by the 4×4 harmonics model is identified and POs are found. It is found that the disturbing effect of the highly irregular gravitational field on orbital motion is weakened around the polar region, and also for an asteroid with a fast rotation rate. Starting with initial conditions from this averaged model, families of exact POs in the original non-averaged system are obtained employing a numerical search method and a continuation technique. Some of these POs are stable and are candidates for future missions.
Modeling carbon allocation in trees: a search for principles.
Franklin, Oskar; Johansson, Jacob; Dewar, Roderick C; Dieckmann, Ulf; McMurtrie, Ross E; Brännström, Ake; Dybzinski, Ray
2012-06-01
We review approaches to predicting carbon and nitrogen allocation in forest models in terms of their underlying assumptions and their resulting strengths and limitations. Empirical and allometric methods are easily developed and computationally efficient, but lack the power of evolution-based approaches to explain and predict multifaceted effects of environmental variability and climate change. In evolution-based methods, allocation is usually determined by maximization of a fitness proxy, either in a fixed environment, which we call optimal response (OR) models, or including the feedback of an individual's strategy on its environment (game-theoretical optimization, GTO). Optimal response models can predict allocation in single trees and stands when there is significant competition only for one resource. Game-theoretical optimization can be used to account for additional dimensions of competition, e.g., when strong root competition boosts root allocation at the expense of wood production. However, we demonstrate that an OR model predicts similar allocation to a GTO model under the root-competitive conditions reported in free-air carbon dioxide enrichment (FACE) experiments. The most evolutionarily realistic approach is adaptive dynamics (AD) where the allocation strategy arises from eco-evolutionary dynamics of populations instead of a fitness proxy. We also discuss emerging entropy-based approaches that offer an alternative thermodynamic perspective on allocation, in which fitness proxies are replaced by entropy or entropy production. To help develop allocation models further, the value of wide-ranging datasets, such as FLUXNET, could be greatly enhanced by ancillary measurements of driving variables, such as water and soil nitrogen availability.
Modeled distributions of 12 tree species in New York
Rachel I. Riemann; Barry T. Wilson; Andrew J. Lister; Oren Cook; Sierra. Crane-Murdoch
2014-01-01
These maps depict the distribution of 12 tree species across the state of New York. The maps show where these trees do not occur (gray), occasionally occur (pale green), are a minor component (medium green), are a major component (dark green), or are the dominant species (black) in the forest, as determined by that species' total basal area. Basal area is the area...
Stem biomass and volume models of selected tropical tree species ...
African Journals Online (AJOL)
Estimating tree volume and biomass constitutes an essential part of the forest resources assessment and the evaluation of the climate change mitigation potential of forests through biomass accumulation and carbon sequestration. This research article provides stem volume and biomass equations applicable to five tree ...
A. Morani; D. Nowak; S. Hirabayashi; G. Guidolotti; M. Medori; V. Muzzini; S. Fares; G. Scarascia Mugnozza; C. Calfapietra
2014-01-01
Ozone flux estimates from the i-Tree model were compared with ozone flux measurements using the Eddy Covariance technique in a periurban Mediterranean forest near Rome (Castelporziano). For the first time i-Tree model outputs were compared with field measurements in relation to dry deposition estimates. Results showed generally a...
Incorporating additional tree and environmental variables in a lodgepole pine stem profile model
John C. Byrne
1993-01-01
A new variable-form segmented stem profile model is developed for lodgepole pine (Pinus contorta) trees from the northern Rocky Mountains of the United States. I improved estimates of stem diameter by predicting two of the model coefficients with linear equations using a measure of tree form, defined as a ratio of dbh and total height. Additional improvements were...
Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments
Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.
2009-01-01
The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…
Models for estimation of tree volume in the miombo woodlands of ...
African Journals Online (AJOL)
Volume of trees is an important parameter in forest management, but only volume models with limited geographical and tree size coverage have previously been developed for Tanzanian miombo woodlands. This study developed models for estimating total, merchantable stem and branches volume applicable for the entire ...
A modeling study of the impact of urban trees on ozone
David J. Nowak; Kevin L. Civerolo; S. Trivikrama Rao; Gopal Sistla; Christopher J. Luley; Daniel E. Crane
2000-01-01
Modeling the effects of increased urban tree cover on ozone concentrations (July 13-15, 1995) from Washington, DC, to central Massachusetts reveals that urban trees generally reduce ozone concentrations in cities, but tend to increase average ozone concentrations in the overall modeling domain. During the daytime, average ozone reductions in urban areas (1 ppb) were...
Modeling the Effects of Asynchronous Rotation on Secondary Eclipse Timings in HW VIr Binaries
Clancy, Padraig
2018-01-01
HW Vir binaries are post common envelope binaries consisting of a hot subdwarf and red dwarf, with light curves dominated by primary eclipses, a strong reflection effect, and secondary eclipses. They have orbital periods ranging from a few hours to half a day and are generally thought to be tidally locked; most studies assume both synchronous rotation and zero eccentricity when modeling HW Vir light curves and radial velocities. Their stable eclipse timings are frequently used in O-C studies to look for the presence of circumbinary objects, measure evolutionary changes in the orbital period, and even constrain the component masses through Roemer delay measurements of the secondary eclipse. While most systems are probably tidally locked or close to it, even slightly asynchronous rotation could theoretically shift the orbital phase of the reflection effect. Here we investigate how asynchronous rotation might affect measurements of secondary eclipse timings by generating thousands of synthetic light curves with a range of reflection effect phases, fitting eclipse timings, and creating O-C diagrams.
Wulandari, S. P.; Salamah, M.; Rositawati, A. F. D.
2018-04-01
Food security is the condition where the food fulfilment is managed well for the country till the individual. Indonesia is one of the country which has the commitment to create the food security becomes main priority. However, the food necessity becomes common thing means that it doesn’t care about nutrient standard and the health condition of family member, so in the fulfilment of food necessity also has to consider the disease suffered by the family member, one of them is pulmonary tuberculosa. From that reasons, this research is conducted to know the factors which influence on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya by using binary logistic regression method. The analysis result by using binary logistic regression shows that the variables wife latest education, house density and spacious house ventilation significantly affect on household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya, where the wife education level is University/equivalent, the house density is eligible or 8 m2/person and spacious house ventilation 10% of the floor area has the opportunity to become food secure households amounted to 0.911089. While the chance of becoming food insecure households amounted to 0.088911. The model household food security status which suffered from pulmonary tuberculosis in the coastal area of Surabaya has been conformable, and the overall percentages of those classifications are at 71.8%.
A stochastic model of nanoparticle self-assembly on Cayley trees
International Nuclear Information System (INIS)
Mazilu, I; Schwen, E M; Banks, W E; Pope, B K; Mazilu, D A
2015-01-01
Nanomedicine is an emerging area of medical research that uses innovative nanotechnologies to improve the delivery of therapeutic and diagnostic agents with maximum clinical benefit. We present a versatile stochastic model that can be used to capture the basic features of drug encapsulation of nanoparticles on tree-like synthetic polymers called dendrimers. The geometry of a dendrimer is described mathematically as a Cayley tree. We use our stochastic model to study the dynamics of deposition and release of monomers (simulating the drug molecules) on Cayley trees (simulating dendrimers). We present analytical and Monte Carlo simulation results for the particle density on Cayley trees of coordination number three and four
Binary modelling the milling of UG2 ore using a matrix approach
Directory of Open Access Journals (Sweden)
Méschac-Bill Kime
2017-04-01
Full Text Available The study reports a binary matrix modelling and simulation studies to improve the performance of the secondary grinding circuit of UG2 ores. The model developed was intended to help searching for optimal operating conditions of the secondary milling circuit so that the platinum group element (PGE recovery is increased while reducing Cr2O3 entrainment in the subsequent flotation stage. A series of laboratory batch-scale tests was carried out in order to estimate the milling kinetics parameters of the chromite and non-chromite components. Finally, two alternatives circuit configurations for a better performance were evaluated using simulations. The optimal design consisted of a conventional ball mill in closed circuit with a hydrocyclone to separate the milling product into lights (non-chromite-rich and heavies (chromite-rich fractions followed by a vibrating screen to de-slime the cyclone underflow before it is returned to the mill for further grinding.
Molecular dynamics and binary collisions modeling of the primary damage state of collision cascades
International Nuclear Information System (INIS)
Heinisch, H.L.; Singh, B.N.
1992-01-01
The objective of this work is to determine the spectral dependence of defect production and microstructure evolution for the development of fission-fusion correlations. Quantitative information on defect production in cascades in copper obtained from recent molecular dynamics (MD) simulations is compared to defect production information determined earlier with a model based on the binary collision approximation (BCA). The total numbers of residual defects, the fractions of them that are mobile, and the sizes of immobile clusters compare favorably, especially when the termination conditions of the two simulations are taken into account. A strategy is laid out for integrating the details of the cascade quenching phase determined by MD into a BCA-based model that is practical for simulating much higher energies and longer times than MD alone can achieve. The extraction of collisional phase information from MD simulations and the correspondence of MD and BCA versions of the collisional phase demonstrated at low energy
International Nuclear Information System (INIS)
Modarres, Mohammad; Cheon, Se Woo
1999-01-01
Most of the complex systems are formed through some hierarchical evolution. Therefore, those systems can be best described through hierarchical frameworks. This paper describes some fundamental attributes of complex physical systems and several hierarchies such as functional, behavioral, goal/condition, and event hierarchies, then presents a function-centered approach to system modeling. Based on the function-centered concept, this paper describes the joint goal tree-success tree (GTST) and the master logic diagram (MLD) as a framework for developing models of complex physical systems. A function-based lexicon for classifying the most common elements of engineering systems for use in the GTST-MLD framework has been proposed. The classification is based on the physical conservation laws that govern the engineering systems. Functional descriptions based on conservation laws provide a simple and rich vocabulary for modeling complex engineering systems
Isoprene Emission Factors for Subtropical Street Trees for Regional Air Quality Modeling.
Dunn-Johnston, Kristina A; Kreuzwieser, Jürgen; Hirabayashi, Satoshi; Plant, Lyndal; Rennenberg, Heinz; Schmidt, Susanne
2016-01-01
Evaluating the environmental benefits and consequences of urban trees supports their sustainable management in cities. Models such as i-Tree Eco enable decision-making by quantifying effects associated with particular tree species. Of specific concern are emissions of biogenic volatile organic compounds, particularly isoprene, that contribute to the formation of photochemical smog and ground level ozone. Few studies have quantified these potential disservices of urban trees, and current models predominantly use emissions data from trees that differ from those in our target region of subtropical Australia. The present study aimed (i) to quantify isoprene emission rates of three tree species that together represent 16% of the inventoried street trees in the target region; (ii) to evaluate outputs of the i-Tree Eco model using species-specific versus currently used, generic isoprene emission rates; and (iii) to evaluate the findings in the context of regional air quality. Isoprene emission rates of (Myrtaceae) and (Proteaceae) were 2.61 and 2.06 µg g dry leaf weight h, respectively, whereas (Sapindaceae) was a nonisoprene emitter. We substituted the generic isoprene emission rates with these three empirical values in i-Tree Eco, resulting in a 182 kg yr (97%) reduction in isoprene emissions, totaling 6284 kg yr when extrapolated to the target region. From these results we conclude that care has to be taken when using generic isoprene emission factors for urban tree models. We recommend that emissions be quantified for commonly planted trees, allowing decision-makers to select tree species with the greatest overall benefit for the urban environment. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.
An assessment of estimation methods for generalized linear mixed models with binary outcomes.
Capanu, Marinela; Gönen, Mithat; Begg, Colin B
2013-11-20
Two main classes of methodology have been developed for addressing the analytical intractability of generalized linear mixed models: likelihood-based methods and Bayesian methods. Likelihood-based methods such as the penalized quasi-likelihood approach have been shown to produce biased estimates especially for binary clustered data with small clusters sizes. More recent methods using adaptive Gaussian quadrature perform well but can be overwhelmed by problems with large numbers of random effects, and efficient algorithms to better handle these situations have not yet been integrated in standard statistical packages. Bayesian methods, although they have good frequentist properties when the model is correct, are known to be computationally intensive and also require specialized code, limiting their use in practice. In this article, we introduce a modification of the hybrid approach of Capanu and Begg, 2011, Biometrics 67, 371-380, as a bridge between the likelihood-based and Bayesian approaches by employing Bayesian estimation for the variance components followed by Laplacian estimation for the regression coefficients. We investigate its performance as well as that of several likelihood-based methods in the setting of generalized linear mixed models with binary outcomes. We apply the methods to three datasets and conduct simulations to illustrate their properties. Simulation results indicate that for moderate to large numbers of observations per random effect, adaptive Gaussian quadrature and the Laplacian approximation are very accurate, with adaptive Gaussian quadrature preferable as the number of observations per random effect increases. The hybrid approach is overall similar to the Laplace method, and it can be superior for data with very sparse random effects. Copyright © 2013 John Wiley & Sons, Ltd.
Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy
Directory of Open Access Journals (Sweden)
Changsheng Zhu
2018-03-01
Full Text Available In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
Multi-GPU hybrid programming accelerated three-dimensional phase-field model in binary alloy
Zhu, Changsheng; Liu, Jieqiong; Zhu, Mingfang; Feng, Li
2018-03-01
In the process of dendritic growth simulation, the computational efficiency and the problem scales have extremely important influence on simulation efficiency of three-dimensional phase-field model. Thus, seeking for high performance calculation method to improve the computational efficiency and to expand the problem scales has a great significance to the research of microstructure of the material. A high performance calculation method based on MPI+CUDA hybrid programming model is introduced. Multi-GPU is used to implement quantitative numerical simulations of three-dimensional phase-field model in binary alloy under the condition of multi-physical processes coupling. The acceleration effect of different GPU nodes on different calculation scales is explored. On the foundation of multi-GPU calculation model that has been introduced, two optimization schemes, Non-blocking communication optimization and overlap of MPI and GPU computing optimization, are proposed. The results of two optimization schemes and basic multi-GPU model are compared. The calculation results show that the use of multi-GPU calculation model can improve the computational efficiency of three-dimensional phase-field obviously, which is 13 times to single GPU, and the problem scales have been expanded to 8193. The feasibility of two optimization schemes is shown, and the overlap of MPI and GPU computing optimization has better performance, which is 1.7 times to basic multi-GPU model, when 21 GPUs are used.
Models for Predicting the Biomass of Cunninghamialanceolata Trees and Stands in Southeastern China.
Guangyi, Mei; Yujun, Sun; Saeed, Sajjad
2017-01-01
Using existing equations to estimate the biomass of a single tree or a forest stand still involves large uncertainties. In this study, we developed individual-tree biomass models for Chinese Fir (Cunninghamia lanceolata.) stands in Fujian Province, southeast China, by using 74 previously established models that have been most commonly used to estimate tree biomass. We selected the best fit models and modified them. The results showed that the published model ln(B(Biomass)) = a + b * ln(D) + c * (ln(H))2 + d * (ln(H))3 + e * ln(WD) had the best fit for estimating the tree biomass of Chinese Fir stands. Furthermore, we observed that variables D(diameter at breast height), H (height), and WD(wood density)were significantly correlated with the total tree biomass estimation model. As a result, a natural logarithm structure gave the best estimates for the tree biomass structure. Finally, when a multi-step improvement on tree biomass model was performed, the tree biomass model with Tree volume(TV), WD and biomass wood density conversion factor (BECF),achieved the highest simulation accuracy, expressed as ln(TB) = -0.0703 + 0.9780 * ln(TV) + 0.0213 * ln(WD) + 1.0166 * ln(BECF). Therefore, when TV, WD and BECF were combined with tree biomass volume coefficient bi for Chinese Fir, the stand biomass (SB)model included both volume(SV) and coefficient bi variables of the stand as follows: bi = Exp(-0.0703+0.9780*ln(TV)+0.0213 * ln(WD)+1.0166*ln(BECF)). The stand biomass model is SB = SV/TV * bi.
Suvorova, S.; Clearwater, P.; Melatos, A.; Sun, L.; Moran, W.; Evans, R. J.
2017-11-01
A hidden Markov model (HMM) scheme for tracking continuous-wave gravitational radiation from neutron stars in low-mass x-ray binaries (LMXBs) with wandering spin is extended by introducing a frequency-domain matched filter, called the J -statistic, which sums the signal power in orbital sidebands coherently. The J -statistic is similar but not identical to the binary-modulated F -statistic computed by demodulation or resampling. By injecting synthetic LMXB signals into Gaussian noise characteristic of the Advanced Laser Interferometer Gravitational-wave Observatory (Advanced LIGO), it is shown that the J -statistic HMM tracker detects signals with characteristic wave strain h0≥2 ×10-26 in 370 d of data from two interferometers, divided into 37 coherent blocks of equal length. When applied to data from Stage I of the Scorpius X-1 Mock Data Challenge organized by the LIGO Scientific Collaboration, the tracker detects all 50 closed injections (h0≥6.84 ×10-26), recovering the frequency with a root-mean-square accuracy of ≤1.95 ×10-5 Hz . Of the 50 injections, 43 (with h0≥1.09 ×10-25) are detected in a single, coherent 10 d block of data. The tracker employs an efficient, recursive HMM solver based on the Viterbi algorithm, which requires ˜105 CPU-hours for a typical broadband (0.5 kHz) LMXB search.
A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction.
De Oliveira Martins, Leonardo; Mallo, Diego; Posada, David
2016-05-01
Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models. © The Author(s) 2014. Published by Oxford University Press on behalf of the Society of Systematic Biologists.
Binary Logistic Predictive Model in Determining Students’ Intention to Take Higher Education
Directory of Open Access Journals (Sweden)
Marvin S. Daguplo
2017-11-01
Full Text Available Students’ choice to take higher education is defined by the interaction among behavior and cognition, personal factors, and environmental factors. Using data mining technique and binary regression analysis, this study aims to uncover factors that significantly predict the likelihood for a student to take higher education. Analysis revealed that (i students whose parents are educated with high income are 1.77 times more likely to pursue higher education than not; and (ii Older Female Students are less likely to pursue higher education. The model explains that parents should encouraged their young children to embrace education to its highest level by capacitating themselves economically to provide their basic educational and financial needs. Lastly, the study concludes that the pursuit for higher education among young students can be defined primarily by their parents’ educational and financial capability.
Knee cartilage segmentation using active shape models and local binary patterns
González, Germán.; Escalante-Ramírez, Boris
2014-05-01
Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.
Smith, J. E., Jr.
1983-01-01
Succinonitrile-water and diethylene glycol-ethyl salicylate are two transparent systems which have been studied as monotectic binary metallic alloy solidification models. Being transparent, these systems allow for the direct observations of phase transformations and solidification reactions. The objective was to develop a screening technique to find systems of interest and then experimentally measure those systems. The succinonitrile-water system was used to check the procedures. To simulate the phase diagram of the system, two computer programs which determine solid-liquid and liquid-liquid equilibria were obtained. These programs use the UNIFAC method to determine activity coefficients and together with several other programs were used to predict the phase diagram. An experimental apparatus was developed and the succinonitrile-water phase diagram measured. The diagram was compared to both the simulation and literature data. Substantial differences were found in the comparisons which serve to demonstrate the need for this procedure.
Binary logistic regression modelling: Measuring the probability of relapse cases among drug addict
Ismail, Mohd Tahir; Alias, Siti Nor Shadila
2014-07-01
For many years Malaysia faced the drug addiction issues. The most serious case is relapse phenomenon among treated drug addict (drug addict who have under gone the rehabilitation programme at Narcotic Addiction Rehabilitation Centre, PUSPEN). Thus, the main objective of this study is to find the most significant factor that contributes to relapse to happen. The binary logistic regression analysis was employed to model the relationship between independent variables (predictors) and dependent variable. The dependent variable is the status of the drug addict either relapse, (Yes coded as 1) or not, (No coded as 0). Meanwhile the predictors involved are age, age at first taking drug, family history, education level, family crisis, community support and self motivation. The total of the sample is 200 which the data are provided by AADK (National Antidrug Agency). The finding of the study revealed that age and self motivation are statistically significant towards the relapse cases..
Nested partially latent class models for dependent binary data; estimating disease etiology.
Wu, Zhenke; Deloria-Knoll, Maria; Zeger, Scott L
2017-04-01
The Pneumonia Etiology Research for Child Health (PERCH) study seeks to use modern measurement technology to infer the causes of pneumonia for which gold-standard evidence is unavailable. Based on case-control data, the article describes a latent variable model designed to infer the etiology distribution for the population of cases, and for an individual case given her measurements. We assume each observation is drawn from a mixture model for which each component represents one disease class. The model conisidered here addresses a major limitation of the traditional latent class approach by taking account of residual dependence among multivariate binary outcomes given disease class, hence reducing estimation bias, retaining efficiency and offering more valid inference. Such "local dependence" on each subject is induced in the model by nesting latent subclasses within each disease class. Measurement precision and covariation can be estimated using the control sample for whom the class is known. In a Bayesian framework, we use stick-breaking priors on the subclass indicators for model-averaged inference across different numbers of subclasses. Assessment of model fit and individual diagnosis are done using posterior samples drawn by Gibbs sampling. We demonstrate the utility of the method on simulated and on the motivating PERCH data. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Risk of Recurrence in Operated Parasagittal Meningiomas: A Logistic Binary Regression Model.
Escribano Mesa, José Alberto; Alonso Morillejo, Enrique; Parrón Carreño, Tesifón; Huete Allut, Antonio; Narro Donate, José María; Méndez Román, Paddy; Contreras Jiménez, Ascensión; Pedrero García, Francisco; Masegosa González, José
2018-02-01
Parasagittal meningiomas arise from the arachnoid cells of the angle formed between the superior sagittal sinus (SSS) and the brain convexity. In this retrospective study, we focused on factors that predict early recurrence and recurrence times. We reviewed 125 patients with parasagittal meningiomas operated from 1985 to 2014. We studied the following variables: age, sex, location, laterality, histology, surgeons, invasion of the SSS, Simpson removal grade, follow-up time, angiography, embolization, radiotherapy, recurrence and recurrence time, reoperation, neurologic deficit, degree of dependency, and patient status at the end of follow-up. Patients ranged in age from 26 to 81 years (mean 57.86 years; median 60 years). There were 44 men (35.2%) and 81 women (64.8%). There were 57 patients with neurologic deficits (45.2%). The most common presenting symptom was motor deficit. World Health Organization grade I tumors were identified in 104 patients (84.6%), and the majority were the meningothelial type. Recurrence was detected in 34 cases. Time of recurrence was 9 to 336 months (mean: 84.4 months; median: 79.5 months). Male sex was identified as an independent risk for recurrence with relative risk 2.7 (95% confidence interval 1.21-6.15), P = 0.014. Kaplan-Meier curves for recurrence had statistically significant differences depending on sex, age, histologic type, and World Health Organization histologic grade. A binary logistic regression was made with the Hosmer-Lemeshow test with P > 0.05; sex, tumor size, and histologic type were used in this model. Male sex is an independent risk factor for recurrence that, associated with other factors such tumor size and histologic type, explains 74.5% of all cases in a binary regression model. Copyright © 2017 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
BOJAN D. DJORDJEVIC
2007-12-01
Full Text Available Although many cubic equations of state coupled with van der Waals-one fluid mixing rules including temperature dependent interaction parameters are sufficient for representing phase equilibria and excess properties (excess molar enthalpy HE, excess molar volume VE, etc., difficulties appear in the correlation and prediction of thermodynamic properties of complex mixtures at various temperature and pressure ranges. Great progress has been made by a new approach based on CEOS/GE models. This paper reviews the last six-year of progress achieved in modelling of the volumetric properties for complex binary and ternary systems of non-electrolytes by the CEOS and CEOS/GE approaches. In addition, the vdW1 and TCBT models were used to estimate the excess molar volume VE of ternary systems methanol + chloroform + benzene and 1-propanol + chloroform + benzene, as well as the corresponding binaries methanol + chloroform, chloroform + benzene, 1-propanol + chloroform and 1-propanol + benzene at 288.15–313.15 K and atmospheric pressure. Also, prediction of VE for both ternaries by empirical models (Radojković, Kohler, Jackob–Fitzner, Colinet, Tsao–Smith, Toop, Scatchard, Rastogi was performed.
Lin, Yi; Jiang, Miao; Pellikka, Petri; Heiskanen, Janne
2018-01-01
Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology-light detection and ranging (LiDAR). Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs) into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Directory of Open Access Journals (Sweden)
Yi Lin
2018-02-01
Full Text Available Mensuration of tree growth habits is of considerable importance for understanding forest ecosystem processes and forest biophysical responses to climate changes. However, the complexity of tree crown morphology that is typically formed after many years of growth tends to render it a non-trivial task, even for the state-of-the-art 3D forest mapping technology—light detection and ranging (LiDAR. Fortunately, botanists have deduced the large structural diversity of tree forms into only a limited number of tree architecture models, which can present a-priori knowledge about tree structure, growth, and other attributes for different species. This study attempted to recruit Hallé architecture models (HAMs into LiDAR mapping to investigate tree growth habits in structure. First, following the HAM-characterized tree structure organization rules, we run the kernel procedure of tree species classification based on the LiDAR-collected point clouds using a support vector machine classifier in the leave-one-out-for-cross-validation mode. Then, the HAM corresponding to each of the classified tree species was identified based on expert knowledge, assisted by the comparison of the LiDAR-derived feature parameters. Next, the tree growth habits in structure for each of the tree species were derived from the determined HAM. In the case of four tree species growing in the boreal environment, the tests indicated that the classification accuracy reached 85.0%, and their growth habits could be derived by qualitative and quantitative means. Overall, the strategy of recruiting conventional HAMs into LiDAR mapping for investigating tree growth habits in structure was validated, thereby paving a new way for efficiently reflecting tree growth habits and projecting forest structure dynamics.
Evaluation of Thermodynamic Models for Predicting Phase Equilibria of CO2 + Impurity Binary Mixture
Shin, Byeong Soo; Rho, Won Gu; You, Seong-Sik; Kang, Jeong Won; Lee, Chul Soo
2018-03-01
For the design and operation of CO2 capture and storage (CCS) processes, equation of state (EoS) models are used for phase equilibrium calculations. Reliability of an EoS model plays a crucial role, and many variations of EoS models have been reported and continue to be published. The prediction of phase equilibria for CO2 mixtures containing SO2, N2, NO, H2, O2, CH4, H2S, Ar, and H2O is important for CO2 transportation because the captured gas normally contains small amounts of impurities even though it is purified in advance. For the design of pipelines in deep sea or arctic conditions, flow assurance and safety are considered priority issues, and highly reliable calculations are required. In this work, predictive Soave-Redlich-Kwong, cubic plus association, Groupe Européen de Recherches Gazières (GERG-2008), perturbed-chain statistical associating fluid theory, and non-random lattice fluids hydrogen bond EoS models were compared regarding performance in calculating phase equilibria of CO2-impurity binary mixtures and with the collected literature data. No single EoS could cover the entire range of systems considered in this study. Weaknesses and strong points of each EoS model were analyzed, and recommendations are given as guidelines for safe design and operation of CCS processes.
Estimating tree bole volume using artificial neural network models for four species in Turkey.
Ozçelik, Ramazan; Diamantopoulou, Maria J; Brooks, John R; Wiant, Harry V
2010-01-01
Tree bole volumes of 89 Scots pine (Pinus sylvestris L.), 96 Brutian pine (Pinus brutia Ten.), 107 Cilicica fir (Abies cilicica Carr.) and 67 Cedar of Lebanon (Cedrus libani A. Rich.) trees were estimated using Artificial Neural Network (ANN) models. Neural networks offer a number of advantages including the ability to implicitly detect complex nonlinear relationships between input and output variables, which is very helpful in tree volume modeling. Two different neural network architectures were used and produced the Back propagation (BPANN) and the Cascade Correlation (CCANN) Artificial Neural Network models. In addition, tree bole volume estimates were compared to other established tree bole volume estimation techniques including the centroid method, taper equations, and existing standard volume tables. An overview of the features of ANNs and traditional methods is presented and the advantages and limitations of each one of them are discussed. For validation purposes, actual volumes were determined by aggregating the volumes of measured short sections (average 1 meter) of the tree bole using Smalian's formula. The results reported in this research suggest that the selected cascade correlation artificial neural network (CCANN) models are reliable for estimating the tree bole volume of the four examined tree species since they gave unbiased results and were superior to almost all methods in terms of error (%) expressed as the mean of the percentage errors. 2009 Elsevier Ltd. All rights reserved.
Modeled PM2.5 removal by trees in ten US cities and associated health effects
David J. Nowak; Satoshi Hirabayashi; Allison Bodine; Robert. Hoehn
2013-01-01
Urban particulate air pollution is a serious health issue. Trees within cities can remove ﬁne particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM2.5 removed annually by...
Bianca N.I. Eskelson; Hailemariam Temesgen; Tara M. Barrett
2009-01-01
Cavity tree and snag abundance data are highly variable and contain many zero observations. We predict cavity tree and snag abundance from variables that are readily available from forest cover maps or remotely sensed data using negative binomial (NB), zero-inflated NB, and zero-altered NB (ZANB) regression models as well as nearest neighbor (NN) imputation methods....
Relating FIA data to habitat classifications via tree-based models of canopy cover
Mark D. Nelson; Brian G. Tavernia; Chris Toney; Brian F. Walters
2012-01-01
Wildlife species-habitat matrices are used to relate lists of species with abundance of their habitats. The Forest Inventory and Analysis Program provides data on forest composition and structure, but these attributes may not correspond directly with definitions of wildlife habitats. We used FIA tree data and tree crown diameter models to estimate canopy cover, from...
A structurally based analytic model for estimation of biomass and fuel loads of woodland trees
Robin J. Tausch
2009-01-01
Allometric/structural relationships in tree crowns are a consequence of the physical, physiological, and fluid conduction processes of trees, which control the distribution, efficient support, and growth of foliage in the crown. The structural consequences of these processes are used to develop an analytic model based on the concept of branch orders. A set of...
Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H
2017-10-25
Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.
Past and ongoing shifts in Joshua tree distribution support future modeled range contraction
Kenneth L. Cole; Kirsten Ironside; Jon Eischeid; Gregg Garfin; Phillip B. Duffy; Chris Toney
2011-01-01
The future distribution of the Joshua tree (Yucca brevifolia) is projected by combining a geostatistical analysis of 20th-century climates over its current range, future modeled climates, and paleoecological data showing its response to a past similar climate change. As climate rapidly warmed ~11 700 years ago, the range of Joshua tree contracted, leaving only the...
An individual-tree basal area growth model for loblolly pine stands
Paul A. Murphy; Michael G. Shelton
1996-01-01
Tree basal area growth has been modeled as a combination of a potential growth function and a modifier function, in which the potential function is fitted separately from open-grown tree data or a subset of the data and the modifier function includes stand and site variables. We propose a modification of this by simultaneously fitting both a growth component and a...
Directory of Open Access Journals (Sweden)
Claudia Pedroza
2016-08-01
Full Text Available Abstract Background Reporting of absolute risk difference (RD is recommended for clinical and epidemiological prospective studies. In analyses of multicenter studies, adjustment for center is necessary when randomization is stratified by center or when there is large variation in patients outcomes across centers. While regression methods are used to estimate RD adjusted for baseline predictors and clustering, no formal evaluation of their performance has been previously conducted. Methods We performed a simulation study to evaluate 6 regression methods fitted under a generalized estimating equation framework: binomial identity, Poisson identity, Normal identity, log binomial, log Poisson, and logistic regression model. We compared the model estimates to unadjusted estimates. We varied the true response function (identity or log, number of subjects per center, true risk difference, control outcome rate, effect of baseline predictor, and intracenter correlation. We compared the models in terms of convergence, absolute bias and coverage of 95 % confidence intervals for RD. Results The 6 models performed very similar to each other for the majority of scenarios. However, the log binomial model did not converge for a large portion of the scenarios including a baseline predictor. In scenarios with outcome rate close to the parameter boundary, the binomial and Poisson identity models had the best performance, but differences from other models were negligible. The unadjusted method introduced little bias to the RD estimates, but its coverage was larger than the nominal value in some scenarios with an identity response. Under the log response, coverage from the unadjusted method was well below the nominal value (<80 % for some scenarios. Conclusions We recommend the use of a binomial or Poisson GEE model with identity link to estimate RD for correlated binary outcome data. If these models fail to run, then either a logistic regression, log Poisson
Bartczak, P.; Kryszczyńska, A.; Dudziński, G.; Polińska, M.; Colas, F.; Vachier, F.; Marciniak, A.; Pollock, J.; Apostolovska, G.; Santana-Ros, T.; Hirsch, R.; Dimitrow, W.; Murawiecka, M.; Wietrzycka, P.; Nadolny, J.
2017-10-01
We present a new non-convex model of the binary asteroid (809) Lundia. A SAGE (Shaping Asteroids with Genetic Evolution) method using disc-integrated photometry only was used for deriving physical parameters of this binary system. The model of (809) Lundia improves former system's pole solution and gives the ecliptic coordinates of the orbit pole - λ = 122°, β = 22°, σ = ±5° - and the orbital period of 15.415 74 ± 0.000 01 h. For scaling our results, we used an effective diameter (Deff) of 9.6 ± 1.1 km obtained from Spitzer observations. The non-convex shape description of the components permitted a refined calculation of the components' volumes, leading to a density estimation of 2.5 ± 0.2 g cm-3 and a macroporosity of 13-23 per cent. The intermediate-scale features of the model may also offer new clues on the components' origin and evolution.
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Zbisław Tabor
2011-05-01
Full Text Available In the study an algorithm based on a lattice gas model is proposed as a tool for enhancing quality of lowresolution images of binary structures. Analyzed low-resolution gray-level images are replaced with binary images, in which pixel size is decreased. The intensity in the pixels of these new images is determined by corresponding gray-level intensities in the original low-resolution images. Then the white phase pixels in the binary images are assumed to be particles interacting with one another, interacting with properly defined external field and allowed to diffuse. The evolution is driven towards a state with maximal energy by Metropolis algorithm. This state is used to estimate the imaged object. The performance of the proposed algorithm and local and global thresholding methods are compared.
Numerical modeling of two-phase binary fluid mixing using mixed finite elements
Sun, Shuyu
2012-07-27
Diffusion coefficients of dense gases in liquids can be measured by considering two-phase binary nonequilibrium fluid mixing in a closed cell with a fixed volume. This process is based on convection and diffusion in each phase. Numerical simulation of the mixing often requires accurate algorithms. In this paper, we design two efficient numerical methods for simulating the mixing of two-phase binary fluids in one-dimensional, highly permeable media. Mathematical model for isothermal compositional two-phase flow in porous media is established based on Darcy\\'s law, material balance, local thermodynamic equilibrium for the phases, and diffusion across the phases. The time-lag and operator-splitting techniques are used to decompose each convection-diffusion equation into two steps: diffusion step and convection step. The Mixed finite element (MFE) method is used for diffusion equation because it can achieve a high-order and stable approximation of both the scalar variable and the diffusive fluxes across grid-cell interfaces. We employ the characteristic finite element method with moving mesh to track the liquid-gas interface. Based on the above schemes, we propose two methods: single-domain and two-domain methods. The main difference between two methods is that the two-domain method utilizes the assumption of sharp interface between two fluid phases, while the single-domain method allows fractional saturation level. Two-domain method treats the gas domain and the liquid domain separately. Because liquid-gas interface moves with time, the two-domain method needs work with a moving mesh. On the other hand, the single-domain method allows the use of a fixed mesh. We derive the formulas to compute the diffusive flux for MFE in both methods. The single-domain method is extended to multiple dimensions. Numerical results indicate that both methods can accurately describe the evolution of the pressure and liquid level. © 2012 Springer Science+Business Media B.V.
Honda, Hidehito; Matsuka, Toshihiko; Ueda, Kazuhiro
2017-01-01
Some researchers on binary choice inference have argued that people make inferences based on simple heuristics, such as recognition, fluency, or familiarity. Others have argued that people make inferences based on available knowledge. To examine the boundary between heuristic and knowledge usage, we examine binary choice inference processes in…
Fabian C.C. Uzoh; William W. Oliver
2008-01-01
A diameter increment model is developed and evaluated for individual trees of ponderosa pine throughout the species range in the United States using a multilevel linear mixed model. Stochastic variability is broken down among period, locale, plot, tree and within-tree components. Covariates acting at tree and stand level, as breast height diameter, density, site index...
Component-based modeling of systems for automated fault tree generation
International Nuclear Information System (INIS)
Majdara, Aref; Wakabayashi, Toshio
2009-01-01
One of the challenges in the field of automated fault tree construction is to find an efficient modeling approach that can support modeling of different types of systems without ignoring any necessary details. In this paper, we are going to represent a new system of modeling approach for computer-aided fault tree generation. In this method, every system model is composed of some components and different types of flows propagating through them. Each component has a function table that describes its input-output relations. For the components having different operational states, there is also a state transition table. Each component can communicate with other components in the system only through its inputs and outputs. A trace-back algorithm is proposed that can be applied to the system model to generate the required fault trees. The system modeling approach and the fault tree construction algorithm are applied to a fire sprinkler system and the results are presented
Fang, F. J.
2017-12-01
Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.
Li, Tanda; Bedding, Timothy R.; Huber, Daniel; Ball, Warrick H.; Stello, Dennis; Murphy, Simon J.; Bland-Hawthorn, Joss
2018-03-01
Stellar models rely on a number of free parameters. High-quality observations of eclipsing binary stars observed by Kepler offer a great opportunity to calibrate model parameters for evolved stars. Our study focuses on six Kepler red giants with the goal of calibrating the mixing-length parameter of convection as well as the asteroseismic surface term in models. We introduce a new method to improve the identification of oscillation modes that exploits theoretical frequencies to guide the mode identification (`peak-bagging') stage of the data analysis. Our results indicate that the convective mixing-length parameter (α) is ≈14 per cent larger for red giants than for the Sun, in agreement with recent results from modelling the APOGEE stars. We found that the asteroseismic surface term (i.e. the frequency offset between the observed and predicted modes) correlates with stellar parameters (Teff, log g) and the mixing-length parameter. This frequency offset generally decreases as giants evolve. The two coefficients a-1 and a3 for the inverse and cubic terms that have been used to describe the surface term correction are found to correlate linearly. The effect of the surface term is also seen in the p-g mixed modes; however, established methods for correcting the effect are not able to properly correct the g-dominated modes in late evolved stars.
Model many-body Stoner Hamiltonian for binary FeCr alloys
Nguyen-Manh, D.; Dudarev, S. L.
2009-09-01
We derive a model tight-binding many-body d -electron Stoner Hamiltonian for FeCr binary alloys and investigate the sensitivity of its mean-field solutions to the choice of hopping integrals and the Stoner exchange parameters. By applying the local charge-neutrality condition within a self-consistent treatment we show that the negative enthalpy-of-mixing anomaly characterizing the alloy in the low chromium concentration limit is due entirely to the presence of the on-site exchange Stoner terms and that the occurrence of this anomaly is not specifically related to the choice of hopping integrals describing conventional chemical bonding between atoms in the alloy. The Bain transformation pathway computed, using the proposed model Hamiltonian, for the Fe15Cr alloy configuration is in excellent agreement with ab initio total-energy calculations. Our investigation also shows how the parameters of a tight-binding many-body model Hamiltonian for a magnetic alloy can be derived from the comparison of its mean-field solutions with other, more accurate, mean-field approximations (e.g., density-functional calculations), hence stimulating the development of large-scale computational algorithms for modeling radiation damage effects in magnetic alloys and steels.
A new binary model for university examination timetabling: a case study
Komijan, Alireza Rashidi; Koupaei, Mehrdad Nouri
2012-12-01
Examination timetabling problem (ETP) is one of the most important issues in universities. An improper timetable may result in students' dissatisfaction as it may not let them study enough between two sequential exams. In addition, the many exams to be scheduled, the large number of students who have taken different courses, the limited number of rooms, and some constraints such as no conflict in a single student's exams make it very difficult to schedule experimentally. A mathematical programming model is required to formulate such a sophisticated problem. In this paper, a new binary model is developed for ETP. The novelty of the paper can be discussed in two directions. The first one is that a course can be offered more than once in a semester. If a course is requested by a few students, then it is enough to be offered once. If the number of students requesting a course is more than the maximum number of students who are allowed to attend a single class, then the course is multi-offered. The second novelty is that sharing a room for two simultaneous exams is allowed. Also, the model considers some hard and soft constraints, and the objective function is set in such a way that soft constraints are satisfied as much as possible. Finally, the model is applied in a sample department and is solved by GAMS.
DEFF Research Database (Denmark)
Tsivintzelis, Ioannis; Kontogeorgis, Georgios; Michelsen, Michael Locht
2011-01-01
In Part I of this series of articles, the study of H2S mixtures has been presented with CPA. In this study the phase behavior of CO2 containing mixtures is modeled. Binary mixtures with water, alcohols, glycols and hydrocarbons are investigated. Both phase equilibria (vapor–liquid and liquid–liqu...
The Binary Fission Model for the Formation of the Pluto system
Prentice, Andrew
2016-10-01
The ratio F of the mass of Pluto (P) to Charon (C), viz. F ≈ 8:1, is the largest ratio of any planet-satellite pair in the solar system. Another measure of the PC binary is its normalized angular momentum density J (see McKinnon 1989). Analysis of astrometric data (Brozovic et al 2015) acquired before the New Horizons (NH) arrival at Pluto and new measurements made by NH (Stern et al 2015) show that J = 0.39. Yet these F & J values are ones expected if the PC binary had formed by the rotational fission of a single liquid mass (Darwin 1902; Lyttleton 1953). At first glance, therefore, the fission model seems to be a viable model for the formation of the Pluto system. In fact, Prentice (1993 Aust J Astron 5 111) had used this model to successfully predict the existence of several moons orbiting beyond Charon, before their discovery in 2005-2012. The main problem with the fission model is that the observed mean density of Charon, namely 1.70 g/cm3, greatly exceeds that of water ice. Charon thus could not have once been a globe of pure water. Here I review the fission model within the framework of the modern Laplacian theory of solar system origin (Prentice 1978 Moon Planets 19 341; 2006 PASA 23 1) and the NH results. I assume that Pluto and Charon were initially a single object (proto-Pluto [p-P]) which had condensed within the same gas ring shed by the proto-solar cloud at orbital distance ~43 AU, where the Kuiper belt was born. The temperature of this gas ring is 26 K and the mean orbit pressure is 1.3 × 10-9 bar. After the gas ring is shed, chemical condensation takes place. The bulk chemical composition of the condensate is anhydrous rock (mass fraction 0.5255), graphite (0.0163), water ice (0.1858), CO2 ice (0.2211) and methane ice (0.0513). Next I assume that melting of the ices in p-P takes place through the decay of short-lived radioactive nuclides, thus causing internal segregation of the rock & graphite. Settling of heavy grains to the centre lowers the
Zheng Zhao; Yaoqi Zhang; Yali Wen
2018-01-01
Urban trees are more about people than trees. Urban trees programs need public support and engagement, from the intentions to support to implement actions in supporting the programs. Built upon the theory of planned behavior and Structural Equation Modeling (SEM), this study uses Beijing as a case study to investigate how subjective norm (cognition of urban trees), attitude (benefits residents’ believe urban trees can provide), and perceived behavioral control (the believed ability of what re...
Directory of Open Access Journals (Sweden)
Jinmo Kim
2016-09-01
Full Text Available This study proposes a modeling method that can effectively generate multiple diverse digital trees for creating immersive virtual landscape based on virtual reality and an optimization method for real-time rendering. The proposed method simplifies a process of procedures from growth of tree models to the generation of the three-dimensional branch geometric model. Here, the procedural branch graph (PBG algorithm is proposed, which simultaneously and effectively generates diverse trees that have a similar branch pattern. Moreover, the optimization method is designed in a polygon-based branch model which controls the resolution of tree models according to the distance from the camera to generate a tree model structure that is appropriate for an immersive system based on virtual reality. Finally, a virtual reality system is established based on the Oculus SDK (Software Development Kit and Unity3D engine. In this process, the image processing-based pixel to tree (PTT method is proposed as a technique for easily and efficiently generating a virtual landscape by allocating multiple trees on terrain. An immersive virtual landscape that has a stereoscopic perception and spatial impression is created through the proposed method and whether it can deliver experience of nature in virtual reality to the users was checked through an experiment.
The Prediction of Drought-Related Tree Mortality in Vegetation Models
Schwinning, S.; Jensen, J.; Lomas, M. R.; Schwartz, B.; Woodward, F. I.
2013-12-01
Drought-related tree die-off events at regional scales have been reported from all wooded continents and it has been suggested that their frequency may be increasing. The prediction of these drought-related die-off events from regional to global scales has been recognized as a critical need for the conservation of forest resources and improving the prediction of climate-vegetation interactions. However, there is no conceptual consensus on how to best approach the quantitative prediction of tree mortality. Current models use a variety of mechanisms to represent demographic events. Mortality is modeled to represent a number of different processes, including death by fire, wind throw, extreme temperatures, and self-thinning, and each vegetation model differs in the emphasis they place on specific mechanisms. Dynamic global vegetation models generally operate on the assumption of incremental vegetation shift due to changes in the carbon economy of plant functional types and proportional effects on recruitment, growth, competition and mortality, but this may not capture sudden and sweeping tree death caused by extreme weather conditions. We tested several different approaches to predicting tree mortality within the framework of the Sheffield Dynamic Global Vegetation Model. We applied the model to the state of Texas, USA, which in 2011 experienced extreme drought conditions, causing the death of an estimated 300 million trees statewide. We then compared predicted to actual mortality to determine which algorithms most accurately predicted geographical variation in tree mortality. We discuss implications regarding the ongoing debate on the causes of tree death.
Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model
Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.
2015-11-01
In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.
Failed oceanic transform models: experience of shaking the tree
Gerya, Taras
2017-04-01
very same time, some pseudo-2D "side-models" with initial strait ridge and ad-hock strain weakened rheology, which were run for curiosity, suddenly showed spontaneous development of ridge curvature… Fraction of these models showed spontaneous development of orthogonal ridge-transform patterns by rotation of oblique ridge sections toward extension-parallel direction to accommodate asymmetric plate accretion. The later was controlled by detachment faults stabilized by strain weakening. Further exploration of these "side-models" resulted in complete changing of my concept for oceanic transforms: they are not plate fragmentation but rather plate growth structures stabilized by continuous plate accretion and rheological weakening of deforming rocks (Gerya, 2010, 2013). The conclusion is - keep shaking the tree and banana will fall… Gerya, T. (2010) Dynamical instability produces transform faults at mid-ocean ridges. Science, 329, 1047-1050. Gerya, T.V. (2013) Three-dimensional thermomechanical modeling of oceanic spreading initiation and evolution. Phys. Earth Planet. Interiors, 214, 35-52.
Cheaib, Alissar; Badeau, Vincent; Boe, Julien; Chuine, Isabelle; Delire, Christine; Dufrêne, Eric; François, Christophe; Gritti, Emmanuel S; Legay, Myriam; Pagé, Christian; Thuiller, Wilfried; Viovy, Nicolas; Leadley, Paul
2012-06-01
Model-based projections of shifts in tree species range due to climate change are becoming an important decision support tool for forest management. However, poorly evaluated sources of uncertainty require more scrutiny before relying heavily on models for decision-making. We evaluated uncertainty arising from differences in model formulations of tree response to climate change based on a rigorous intercomparison of projections of tree distributions in France. We compared eight models ranging from niche-based to process-based models. On average, models project large range contractions of temperate tree species in lowlands due to climate change. There was substantial disagreement between models for temperate broadleaf deciduous tree species, but differences in the capacity of models to account for rising CO(2) impacts explained much of the disagreement. There was good quantitative agreement among models concerning the range contractions for Scots pine. For the dominant Mediterranean tree species, Holm oak, all models foresee substantial range expansion. © 2012 Blackwell Publishing Ltd/CNRS.
Mowlavi, N.; Lecoeur-Taïbi, I.; Holl, B.; Rimoldini, L.; Barblan, F.; Prša, A.; Kochoska, A.; Süveges, M.; Eyer, L.; Nienartowicz, K.; Jevardat, G.; Charnas, J.; Guy, L.; Audard, M.
2017-10-01
Context. The advent of large scale multi-epoch surveys raises the need for automated light curve (LC) processing. This is particularly true for eclipsing binaries (EBs), which form one of the most populated types of variable objects. The Gaia mission, launched at the end of 2013, is expected to detect of the order of few million EBs over a five-year mission. Aims: We present an automated procedure to characterize EBs based on the geometric morphology of their LCs with two aims: first to study an ensemble of EBs on a statistical ground without the need to model the binary system, and second to enable the automated identification of EBs that display atypical LCs. Methods: We modeled the folded LC geometry of EBs using up to two Gaussian functions for the eclipses and a cosine function for any ellipsoidal-like variability that may be present between the eclipses. The procedure is applied to the OGLE-III data set of EBs in the Large Magellanic Cloud (LMC) as a proof of concept. The Bayesian information criterion is used to select the best model among models containing various combinations of those components, as well as to estimate the significance of the components. Results: Based on the two-Gaussian models, EBs with atypical LC geometries are successfully identified in two diagrams, using the Abbe values of the original and residual folded LCs, and the reduced χ2. Cleaning the data set from the atypical cases and further filtering out LCs that contain non-significant eclipse candidates, the ensemble of EBs can be studied on a statistical ground using the two-Gaussian model parameters. For illustrative purposes, we present the distribution of projected eccentricities as a function of orbital period for the OGLE-III set of EBs in the LMC, as well as the distribution of their primary versus secondary eclipse widths. The two-Gaussian models for all the OGLE-III LMC EBs table is only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130
Study on reliability analysis based on multilevel flow models and fault tree method
International Nuclear Information System (INIS)
Chen Qiang; Yang Ming
2014-01-01
Multilevel flow models (MFM) and fault tree method describe the system knowledge in different forms, so the two methods express an equivalent logic of the system reliability under the same boundary conditions and assumptions. Based on this and combined with the characteristics of MFM, a method mapping MFM to fault tree was put forward, thus providing a way to establish fault tree rapidly and realizing qualitative reliability analysis based on MFM. Taking the safety injection system of pressurized water reactor nuclear power plant as an example, its MFM was established and its reliability was analyzed qualitatively. The analysis result shows that the logic of mapping MFM to fault tree is correct. The MFM is easily understood, created and modified. Compared with the traditional fault tree analysis, the workload is greatly reduced and the modeling time is saved. (authors)
Soot modeling of counterflow diffusion flames of ethylene-based binary mixture fuels
Wang, Yu
2015-03-01
A soot model was developed based on the recently proposed PAH growth mechanism for C1-C4 gaseous fuels (KAUST PAH Mechanism 2, KM2) that included molecular growth up to coronene (A7) to simulate soot formation in counterflow diffusion flames of ethylene and its binary mixtures with methane, ethane and propane based on the method of moments. The soot model has 36 soot nucleation reactions from 8 PAH molecules including pyrene and larger PAHs. Soot surface growth reactions were based on a modified hydrogen-abstraction-acetylene-addition (HACA) mechanism in which CH3, C3H3 and C2H radicals were included in the hydrogen abstraction reactions in addition to H atoms. PAH condensation on soot particles was also considered. The experimentally measured profiles of soot volume fraction, number density, and particle size were well captured by the model for the baseline case of ethylene along with the cases involving mixtures of fuels. The simulation results, which were in qualitative agreement with the experimental data in the effects of binary fuel mixing on the sooting structures of the measured flames, showed in particular that 5% addition of propane (ethane) led to an increase in the soot volume fraction of the ethylene flame by 32% (6%), despite the fact that propane and ethane are less sooting fuels than is ethylene, which is in reasonable agreement with experiments of 37% (14%). The model revealed that with 5% addition of methane, there was an increase of 6% in the soot volume fraction. The average soot particle sizes were only minimally influenced while the soot number densities were increased by the fuel mixing. Further analysis of the numerical data indicated that the chemical cross-linking effect between ethylene and the dopant fuels resulted in an increase in PAH formation, which led to higher soot nucleation rates and therefore higher soot number densities. On the other hand, the rates of soot surface growth per unit surface area through the HACA mechanism were
Mulder, Willem H; Crawford, Forrest W
2015-01-07
Efforts to reconstruct phylogenetic trees and understand evolutionary processes depend fundamentally on stochastic models of speciation and mutation. The simplest continuous-time model for speciation in phylogenetic trees is the Yule process, in which new species are "born" from existing lineages at a constant rate. Recent work has illuminated some of the structural properties of Yule trees, but it remains mostly unknown how these properties affect sequence and trait patterns observed at the tips of the phylogenetic tree. Understanding the interplay between speciation and mutation under simple models of evolution is essential for deriving valid phylogenetic inference methods and gives insight into the optimal design of phylogenetic studies. In this work, we derive the probability distribution of interspecies covariance under Brownian motion and Ornstein-Uhlenbeck models of phenotypic change on a Yule tree. We compute the probability distribution of the number of mutations shared between two randomly chosen taxa in a Yule tree under discrete Markov mutation models. Our results suggest summary measures of phylogenetic information content, illuminate the correlation between site patterns in sequences or traits of related organisms, and provide heuristics for experimental design and reconstruction of phylogenetic trees. Copyright © 2014 Elsevier Ltd. All rights reserved.
Calculating the Probability of Returning a Loan with Binary Probability Models
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Julian Vasilev
2014-12-01
Full Text Available The purpose of this article is to give a new approach in calculating the probability of returning a loan. A lot of factors affect the value of the probability. In this article by using statistical and econometric models some influencing factors are proved. The main approach is concerned with applying probit and logit models in loan management institutions. A new aspect of the credit risk analysis is given. Calculating the probability of returning a loan is a difficult task. We assume that specific data fields concerning the contract (month of signing, year of signing, given sum and data fields concerning the borrower of the loan (month of birth, year of birth (age, gender, region, where he/she lives may be independent variables in a binary logistics model with a dependent variable “the probability of returning a loan”. It is proved that the month of signing a contract, the year of signing a contract, the gender and the age of the loan owner do not affect the probability of returning a loan. It is proved that the probability of returning a loan depends on the sum of contract, the remoteness of the loan owner and the month of birth. The probability of returning a loan increases with the increase of the given sum, decreases with the proximity of the customer, increases for people born in the beginning of the year and decreases for people born at the end of the year.
Propagation of action potentials along complex axonal trees. Model and implementation.
Manor, Y; Gonczarowski, J; Segev, I
1991-12-01
Axonal trees are typically morphologically and physiologically complicated structures. Because of this complexity, axonal trees show a large repertoire of behavior: from transmission lines with delay, to frequency filtering devices in both temporal and spatial domains. Detailed theoretical exploration of the electrical behavior of realistically complex axonal trees is notably lacking, mainly because of the absence of a simple modeling tool. AXONTREE is an attempt to provide such a simulator. It is written in C for the SUN workstation and implements both a detailed compartmental modeling of Hodgkin and Huxley-like kinetics, and a more abstract, event-driven, modeling approach. The computing module of AXONTREE is introduced together with its input/output features. These features allow graphical construction of arbitrary trees directly on the computer screen, and superimposition of the results on the simulated structure. Several numerical improvements that increase the computational efficiency by a factor of 5-10 are presented; most notable is a novel method of dynamic lumping of the modeled tree into simpler representations ("equivalent cables"). AXONTREE's performance is examined using a reconstructed terminal of an axon from a Y cell in cat visual cortex. It is demonstrated that realistically complicated axonal trees can be handled efficiently. The application of AXONTREE for the study of propagation delays along axonal trees is presented in the companion paper (Manor et al., 1991).
Mechanical properties of tree roots for soil reinforcement models
Cofie, P.
2001-01-01
Evidence from forestry has shown that part of the forest floor bearing capacity is delivered by tree roots. The beneficial effect however varies and diminishes with increasing number of vehicle passes. Roots potential for reinforcing the soil is known to depend among others on root
Casuarina glauca: A model tree for basic research in actinorhizal ...
Indian Academy of Sciences (India)
Casuarina glauca is a fast-growing multipurpose tree belonging to the Casuarinaceae family and native to Australia. It requires limited use of chemical fertilizers due to the symbiotic association with the nitrogen-fixing actinomycete Frankia and with mycorrhizal fungi, which help improve phosphorous and water uptake by ...
A Application of WD Model to EB Type Contact Binary System
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Su-Yeon Oh
2000-12-01
Full Text Available The EB type contact binaries show large temperature difference ( T 1,000K between two components. Thus we have modified the mode 3 of the WD program to adjust albedos, limb darkening coefficients and gravity darkening exponents for both components of such binaries, while the values for those parameters should be same for both components in the original WD program. Both of the modified and the original versions have been applied to the EB type contact binaries such as DO Cas, GO Cyg, and FS Lup. The computed light curves with modified version fit better to the observations.
Maria Theresa I. Cabaraban; Charles N. Kroll; Satoshi Hirabayashi; David J. Nowak
2013-01-01
A distributed adaptation of i-Tree Eco was used to simulate dry deposition in an urban area. This investigation focused on the effects of varying temperature, LAI, and NO2 concentration inputs on estimated NO2 dry deposition to trees in Baltimore, MD. A coupled modeling system is described, wherein WRF provided temperature...
Predicting the "graduate on time (GOT)" of PhD students using binary logistics regression model
Shariff, S. Sarifah Radiah; Rodzi, Nur Atiqah Mohd; Rahman, Kahartini Abdul; Zahari, Siti Meriam; Deni, Sayang Mohd
2016-10-01
Malaysian government has recently set a new goal to produce 60,000 Malaysian PhD holders by the year 2023. As a Malaysia's largest institution of higher learning in terms of size and population which offers more than 500 academic programmes in a conducive and vibrant environment, UiTM has taken several initiatives to fill up the gap. Strategies to increase the numbers of graduates with PhD are a process that is challenging. In many occasions, many have already identified that the struggle to get into the target set is even more daunting, and that implementation is far too ideal. This has further being progressing slowly as the attrition rate increases. This study aims to apply the proposed models that incorporates several factors in predicting the number PhD students that will complete their PhD studies on time. Binary Logistic Regression model is proposed and used on the set of data to determine the number. The results show that only 6.8% of the 2014 PhD students are predicted to graduate on time and the results are compared wih the actual number for validation purpose.
Highly Accurate Tree Models Derived from Terrestrial Laser Scan Data: A Method Description
Directory of Open Access Journals (Sweden)
Jan Hackenberg
2014-05-01
Full Text Available This paper presents a method for fitting cylinders into a point cloud, derived from a terrestrial laser-scanned tree. Utilizing high scan quality data as the input, the resulting models describe the branching structure of the tree, capable of detecting branches with a diameter smaller than a centimeter. The cylinders are stored as a hierarchical tree-like data structure encapsulating parent-child neighbor relations and incorporating the tree’s direction of growth. This structure enables the efficient extraction of tree components, such as the stem or a single branch. The method was validated both by applying a comparison of the resulting cylinder models with ground truth data and by an analysis between the input point clouds and the models. Tree models were accomplished representing more than 99% of the input point cloud, with an average distance from the cylinder model to the point cloud within sub-millimeter accuracy. After validation, the method was applied to build two allometric models based on 24 tree point clouds as an example of the application. Computation terminated successfully within less than 30 min. For the model predicting the total above ground volume, the coefficient of determination was 0.965, showing the high potential of terrestrial laser-scanning for forest inventories.
3D modeling of olive tree and simulating the harvesting forces
Directory of Open Access Journals (Sweden)
Glăvan Dan Ovidiu
2017-01-01
Full Text Available The paper presents the results of the study regarding the influence of shaking forces on olive tree harvesting systems. Shaking forces can be released through several methods. Important is the end result, namely the shaking force and the cadence of shaking speed. Mechanical and automatic harvesting methods collect more olives than traditional methods but may damage the olive trees. In order to prevent this damage, we need to calculate the necessary shaking force. An original research method is proposed to simulate shaking forces using a 3D olive tree model with Autodesk Inventor software. In the experiments, we use different shaking forces and various shaking speeds. We also use different diameters of the olive tree trunk. We analyze the results from this experiment to determine the optimal shaking force for harvesting olives without damaging the olive tree.
iTree-Hydro: Snow hydrology update for the urban forest hydrology model
Yang Yang; Theodore A. Endreny; David J. Nowak
2011-01-01
This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest EffectsâHydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...
Parametric Generation of Polygonal Tree Models for Rendering on Tessellation-Enabled Hardware
Nystad, Jørgen
2010-01-01
The main contribution of this thesis is a parametric method for generation of single-mesh polygonal tree models that follow natural rules as indicated by da Vinci in his notebooks. Following these rules allow for a relatively simple scheme of connecting branches to parent branches. Proper branch connection is a requirement for gaining the benefits of subdivision. Techniques for proper texture coordinate generation and subdivision are also explored.The result is a tree model generation scheme ...
Baudena, Mara|info:eu-repo/dai/nl/340303867; D'Andrea, Fabio; Provenzale, A.
2010-01-01
1. We discuss a simple implicit-space model for the competition of trees and grasses in an idealized savanna environment. The model represents patch occupancy dynamics within the habitat and introduces life stage structure in the tree population, namely adults and seedlings. A tree can be
A Tree-based Approach for Modelling Interception Loss From Evergreen Oak Mediterranean Savannas
Pereira, Fernando L.; Gash, John H. C.; David, Jorge S.; David, Teresa S.; Monteiro, Paulo R.; Valente, Fernanda
2010-05-01
Evaporation of rainfall intercepted by tree canopies is usually an important part of the overall water balance of forested catchments and there have been many studies dedicated to measuring and modelling rainfall interception loss. These studies have mainly been conducted in dense forests; there have been few studies on the very sparse forests which are common in dry and semi-arid areas. Water resources are scarce in these areas making sparse forests particularly important. Methods for modelling interception loss are thus required to support sustainable water management in those areas. In very sparse forests, trees occur as widely spaced individuals rather than as a continuous forest canopy. We therefore suggest that interception loss for this vegetation type can be more adequately modelled if the overall forest evaporation is derived by scaling up the evaporation from individual trees. The evaporation rate for a single tree can be estimated using a simple Dalton-type diffusion equation for water vapour as long as its surface temperature is known. From theory, this temperature is shown to be dependent upon the available energy and windspeed. However, the surface temperature of a fully saturated tree crown, under rainy conditions, should approach the wet bulb temperature as the radiative energy input to the tree reduces to zero. This was experimentally confirmed from measurements of the radiation balance and surface temperature of an isolated tree crown. Thus, evaporation of intercepted rainfall can be estimated using an equation which only requires knowledge of the air dry and wet bulb temperatures and of the bulk tree-crown aerodynamic conductance. This was taken as the basis of a new approach for modelling interception loss from savanna-type woodland, i.e. by combining the Dalton-type equation with the Gash's analytical model to estimate interception loss from isolated trees. This modelling approach was tested using data from two Mediterranean savanna-type oak
Li, Baoyue; Lingsma, Hester F; Steyerberg, Ewout W; Lesaffre, Emmanuel
2011-05-23
Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI) enrolled in eight Randomized Controlled Trials (RCTs) and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS) as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4), Stata (GLLAMM), SAS (GLIMMIX and NLMIXED), MLwiN ([R]IGLS) and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC), R package MCMCglmm and SAS experimental procedure MCMC.Three data sets (the full data set and two sub-datasets) were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal) models for the main study and when based on a relatively large number of level-1 (patient level) data compared to the number of level-2 (hospital level) data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in the availability of additional tools for model
Directory of Open Access Journals (Sweden)
Steyerberg Ewout W
2011-05-01
Full Text Available Abstract Background Logistic random effects models are a popular tool to analyze multilevel also called hierarchical data with a binary or ordinal outcome. Here, we aim to compare different statistical software implementations of these models. Methods We used individual patient data from 8509 patients in 231 centers with moderate and severe Traumatic Brain Injury (TBI enrolled in eight Randomized Controlled Trials (RCTs and three observational studies. We fitted logistic random effects regression models with the 5-point Glasgow Outcome Scale (GOS as outcome, both dichotomized as well as ordinal, with center and/or trial as random effects, and as covariates age, motor score, pupil reactivity or trial. We then compared the implementations of frequentist and Bayesian methods to estimate the fixed and random effects. Frequentist approaches included R (lme4, Stata (GLLAMM, SAS (GLIMMIX and NLMIXED, MLwiN ([R]IGLS and MIXOR, Bayesian approaches included WinBUGS, MLwiN (MCMC, R package MCMCglmm and SAS experimental procedure MCMC. Three data sets (the full data set and two sub-datasets were analysed using basically two logistic random effects models with either one random effect for the center or two random effects for center and trial. For the ordinal outcome in the full data set also a proportional odds model with a random center effect was fitted. Results The packages gave similar parameter estimates for both the fixed and random effects and for the binary (and ordinal models for the main study and when based on a relatively large number of level-1 (patient level data compared to the number of level-2 (hospital level data. However, when based on relatively sparse data set, i.e. when the numbers of level-1 and level-2 data units were about the same, the frequentist and Bayesian approaches showed somewhat different results. The software implementations differ considerably in flexibility, computation time, and usability. There are also differences in
Lee, Saro; Park, Inhye
2013-09-30
Subsidence of ground caused by underground mines poses hazards to human life and property. This study analyzed the hazard to ground subsidence using factors that can affect ground subsidence and a decision tree approach in a geographic information system (GIS). The study area was Taebaek, Gangwon-do, Korea, where many abandoned underground coal mines exist. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 50/50 for training and validation of the models. A data-mining classification technique was applied to the GSH mapping, and decision trees were constructed using the chi-squared automatic interaction detector (CHAID) and the quick, unbiased, and efficient statistical tree (QUEST) algorithms. The frequency ratio model was also applied to the GSH mapping for comparing with probabilistic model. The resulting GSH maps were validated using area-under-the-curve (AUC) analysis with the subsidence area data that had not been used for training the model. The highest accuracy was achieved by the decision tree model using CHAID algorithm (94.01%) comparing with QUEST algorithms (90.37%) and frequency ratio model (86.70%). These accuracies are higher than previously reported results for decision tree. Decision tree methods can therefore be used efficiently for GSH analysis and might be widely used for prediction of various spatial events. Copyright © 2013. Published by Elsevier Ltd.
Jaubert, Jean-Noël; Privat, Romain
2014-01-01
The double-tangent construction of coexisting phases is an elegant approach to visualize all the multiphase binary systems that satisfy the equality of chemical potentials and to select the stable state. In this paper, we show how to perform the double-tangent construction of coexisting phases for binary systems modeled with the gamma-phi…
Canary, Jana D; Blizzard, Leigh; Barry, Ronald P; Hosmer, David W; Quinn, Stephen J
2016-05-01
Generalized linear models (GLM) with a canonical logit link function are the primary modeling technique used to relate a binary outcome to predictor variables. However, noncanonical links can offer more flexibility, producing convenient analytical quantities (e.g., probit GLMs in toxicology) and desired measures of effect (e.g., relative risk from log GLMs). Many summary goodness-of-fit (GOF) statistics exist for logistic GLM. Their properties make the development of GOF statistics relatively straightforward, but it can be more difficult under noncanonical links. Although GOF tests for logistic GLM with continuous covariates (GLMCC) have been applied to GLMCCs with log links, we know of no GOF tests in the literature specifically developed for GLMCCs that can be applied regardless of link function chosen. We generalize the Tsiatis GOF statistic originally developed for logistic GLMCCs, (TG), so that it can be applied under any link function. Further, we show that the algebraically related Hosmer-Lemeshow (HL) and Pigeon-Heyse (J(2) ) statistics can be applied directly. In a simulation study, TG, HL, and J(2) were used to evaluate the fit of probit, log-log, complementary log-log, and log models, all calculated with a common grouping method. The TG statistic consistently maintained Type I error rates, while those of HL and J(2) were often lower than expected if terms with little influence were included. Generally, the statistics had similar power to detect an incorrect model. An exception occurred when a log GLMCC was incorrectly fit to data generated from a logistic GLMCC. In this case, TG had more power than HL or J(2) . © 2015 John Wiley & Sons Ltd/London School of Economics.
International Nuclear Information System (INIS)
Hobler, Gerhard
2015-01-01
Many experiments indicate the importance of stress and stress relaxation upon ion implantation. In this paper, a model is proposed that is capable of describing ballistic effects as well as stress relaxation by viscous flow. It combines atomistic binary collision simulation with continuum mechanics. The only parameters that enter the continuum model are the bulk modulus and the radiation-induced viscosity. The shear modulus can also be considered but shows only minor effects. A boundary-fitted grid is proposed that is usable both during the binary collision simulation and for the spatial discretization of the force balance equations. As an application, the milling of a slit into an amorphous silicon membrane with a 30 keV focused Ga beam is studied, which demonstrates the relevance of the new model compared to a more heuristic approach used in previous work
Application of the regular associated solution model to the Cd-Te and Hg-Te binary systems
Kelley, J. D.; Martin, B. G.; Szofran, F. R.; Lehoczky, S. L.
1982-01-01
The regular associated solution model is used to treat the phase diagrams of the binary II-VI semiconductor alloy systems Hg-Te and Cd-Te. The equations for the species activity coefficients are used without approximations regarding the magnitudes of the various binary interchange energies or the functional dependence on component mol fraction. The values of the four-adjustable parameters required for description of each system are fixed by fitting liquidus data, and the resulting activity coefficients are used to calculate component partial pressures, which are compared with experimental values as an indpendent check of the validity of the model. The results show that the regular associated solution model provides a usefully accurate, but not complete, description for both the Hg-Te and Cd-Te systems. The relationship of this work to previous investigations is discussed.
Modeling solid-state dewetting of a single-crystal binary alloy thin films
Khenner, Mikhail
2018-01-01
Dewetting of a binary alloy thin film is studied using a continuum many-parameter model that accounts for the surface and bulk diffusion, the bulk phase separation, the surface segregation, and the particle formation. An analytical solution is found for the quasistatic equilibrium concentration of a surface-segregated atomic species. This solution is factored into the nonlinear and coupled evolution partial differential equations (PDEs) for the bulk composition and surface morphology. The stability of a planar film surface with respect to small perturbations of shape and composition is analyzed, revealing the dependence of the particle size on major physical parameters. The computations show various scenarios of the particle formation and the redistribution of the alloy components inside the particles and on their surface. In most situations, for the alloy film composed initially of 50% A and 50% B atoms, core-shell particles are formed, and they are located atop a wetting layer that is modestly rich in the B phase. Then the particle shell is the nanometric segregated layer of the A phase, and the core is the alloy that is modestly rich in the A phase.
Sze, N N; Wong, S C; Lee, C Y
2014-12-01
In past several decades, many countries have set quantified road safety targets to motivate transport authorities to develop systematic road safety strategies and measures and facilitate the achievement of continuous road safety improvement. Studies have been conducted to evaluate the association between the setting of quantified road safety targets and road fatality reduction, in both the short and long run, by comparing road fatalities before and after the implementation of a quantified road safety target. However, not much work has been done to evaluate whether the quantified road safety targets are actually achieved. In this study, we used a binary logistic regression model to examine the factors - including vehicle ownership, fatality rate, and national income, in addition to level of ambition and duration of target - that contribute to a target's success. We analyzed 55 quantified road safety targets set by 29 countries from 1981 to 2009, and the results indicate that targets that are in progress and with lower level of ambitions had a higher likelihood of eventually being achieved. Moreover, possible interaction effects on the association between level of ambition and the likelihood of success are also revealed. Copyright © 2014 Elsevier Ltd. All rights reserved.
Modeling Gamma-Ray Emission From the High-Mass X-Ray Binary LS 5039
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Stan Owocki
2012-03-01
Full Text Available A few high-mass X-ray binaries–consisting of an OB star plus compact companion– have been observed by Fermi and ground-based Cerenkov telescopes like High Energy Stereoscopic System (HESS to be sources of very high energy (VHE; up to 30 TeV γ-rays. This paper focuses on the prominent γ-ray source, LS 5039, which consists of a massive O6.5V star in a 3.9-day-period, mildly elliptical (e ≈ 0.24 orbit with its companion, assumed here to be an unmagnetized compact object (e.g., black hole. Using three dimensional smoothed particle hydrodynamics simulations of the Bondi-Hoyle accretion of the O-star wind onto the companion, we find that the orbital phase variation of the accretion follows very closely the simple Bondi-Hoyle-Lyttleton (BHL rate for the local radius and wind speed. Moreover, a simple model, wherein intrinsic emission of γ-rays is assumed to track this accretion rate, reproduces quite well Fermi observations of the phase variation of γ-rays in the energy range 0.1-10 GeV. However for the VHE (0.1-30 TeV radiation observed by the HESS Cerenkov telescope, it is important to account also for photon-photon interactions between the γ-rays and the stellar optical/UV radiation, which effectively attenuates much of the strong emission near periastron. When this is included, we find that this simple BHL accretion model also quite naturally fits the HESS light curve, thus making it a strong alternative to the pulsar-wind-shock models commonly invoked to explain such VHE γ-ray emission in massive-star binaries.
Empirical tests of pre-main-sequence stellar evolution models with eclipsing binaries
Stassun, Keivan G.; Feiden, Gregory A.; Torres, Guillermo
2014-06-01
We examine the performance of standard pre-main-sequence (PMS) stellar evolution models against the accurately measured properties of a benchmark sample of 26 PMS stars in 13 eclipsing binary (EB) systems having masses 0.04-4.0 M⊙ and nominal ages ≈1-20 Myr. We provide a definitive compilation of all fundamental properties for the EBs, with a careful and consistent reassessment of observational uncertainties. We also provide a definitive compilation of the various PMS model sets, including physical ingredients and limits of applicability. No set of model isochrones is able to successfully reproduce all of the measured properties of all of the EBs. In the H-R diagram, the masses inferred for the individual stars by the models are accurate to better than 10% at ≳1 M⊙, but below 1 M⊙ they are discrepant by 50-100%. Adjusting the observed radii and temperatures using empirical relations for the effects of magnetic activity helps to resolve the discrepancies in a few cases, but fails as a general solution. We find evidence that the failure of the models to match the data is linked to the triples in the EB sample; at least half of the EBs possess tertiary companions. Excluding the triples, the models reproduce the stellar masses to better than ∼10% in the H-R diagram, down to 0.5 M⊙, below which the current sample is fully contaminated by tertiaries. We consider several mechanisms by which a tertiary might cause changes in the EB properties and thus corrupt the agreement with stellar model predictions. We show that the energies of the tertiary orbits are comparable to that needed to potentially explain the scatter in the EB properties through injection of heat, perhaps involving tidal interaction. It seems from the evidence at hand that this mechanism, however it operates in detail, has more influence on the surface properties of the stars than on their internal structure, as the lithium abundances are broadly in good agreement with model predictions. The
Modelling of asymmetrical interconnect T-tree laminated on flexible substrate
Ravelo, Blaise
2015-11-01
A fast and accurate behavioral modelling of asymmetrical microstrip tree printed on plastic substrate is investigated. The methodology for extracting the asymmetrical tree transfer responses based on the ABCD-matrix analysis is presented. The elements of the interconnect T-tree are constituted by transmission lines (TLs) defined by their characteristic impedance and physical length. The distributed tree network can be assumed as a single input multiple output (SIMO) topology. By considering the circuit equivalent between the electrical path from the tree input and output, the single input single output (SISO) simplified circuit can be established. In order to determine the frequency response of the interconnect tree system, the elementary TLs constituting the tree branches are modelled with their equivalent frequency dependent RLCG network. The novelty of the present paper is the application of the model to the microstrip structure printed on the plastic substrate by analyzing the influence of the metallization conductivity. As proof of concept (POC), a single input and three output distributed interconnect T-tree having branches presented physical lengths from 3 cm to 20 cm was designed. The POC was printed on the Cu metal deposited plastic Kapton substrate. Then, the frequency dependent per unit length resistance, inductance, capacitance and conductance of the elementary branches of the T-tree from DC to 10 GHz were extracted. By implementing the behavioral model of the circuit, the frequency- and time-domain responses of the proposed asymmetrical T-tree are computed. Then, the analyses of the asymmetrical T-tree responses in function of the thin film conductivity of the microstrip interconnect lines were discussed. In addition, time domain analysis enabling to predict the influence of the deposited metallic ink conductivity on the signal integrity is realized by considering a mixed signal corresponding to the digital data "010110000" having 0.5 Gbps rate
[Biomass dynamics of tree branches of higher order. A model analysis].
Galitskiĭ, V V
2012-01-01
The sectional model of biomass dynamics of freely growing tree brahcnes of all orders is presented. The model is an extension of the sectional tree biomass model proposed earlier. The branches model showed bell-shaped dynamics of a branches biomass and, accordingly, boundedness of branch orders number. The important element of the model of branches system is the inter-verticil green biomass. The model is parameterized on the basis of published data on lifespan of branches of different orders and age in which the biomass of skeletal branches of spruce, Picea abies (L.) Karst, reaches the maximum. When adding known peculiarities of spruce growth (such as the initial growth inhibiton and presence of the inter-verticil branches) to the model of biomass dynamics of regular branches system, good appproximation of all natural data by model values is obtained. The possible mechanism of inter-verticil branches appearance in response to improvement of a tree growth conditions, and also their function in a tree growth process, namely replacement of regular branches incapable of appropriate response, is described. Initiation of appearing and/or waking of the sleeping (adventive) buds which give rise to inter-verticil branches is probably caused by rise of pressure of photosynthates in a tree phloem what the published results of experiments on a decapitaion of branches of Wollemia nobilis (Araucariaceae) also testify.
MRI-based decision tree model for diagnosis of biliary atresia.
Kim, Yong Hee; Kim, Myung-Joon; Shin, Hyun Joo; Yoon, Haesung; Han, Seok Joo; Koh, Hong; Roh, Yun Ho; Lee, Mi-Jung
2018-02-23
To evaluate MRI findings and to generate a decision tree model for diagnosis of biliary atresia (BA) in infants with jaundice. We retrospectively reviewed features of MRI and ultrasonography (US) performed in infants with jaundice between January 2009 and June 2016 under approval of the institutional review board, including the maximum diameter of periportal signal change on MRI (MR triangular cord thickness, MR-TCT) or US (US-TCT), visibility of common bile duct (CBD) and abnormality of gallbladder (GB). Hepatic subcapsular flow was reviewed on Doppler US. We performed conditional inference tree analysis using MRI findings to generate a decision tree model. A total of 208 infants were included, 112 in the BA group and 96 in the non-BA group. Mean age at the time of MRI was 58.7 ± 36.6 days. Visibility of CBD, abnormality of GB and MR-TCT were good discriminators for the diagnosis of BA and the MRI-based decision tree using these findings with MR-TCT cut-off 5.1 mm showed 97.3 % sensitivity, 94.8 % specificity and 96.2 % accuracy. MRI-based decision tree model reliably differentiates BA in infants with jaundice. MRI can be an objective imaging modality for the diagnosis of BA. • MRI-based decision tree model reliably differentiates biliary atresia in neonatal cholestasis. • Common bile duct, gallbladder and periportal signal changes are the discriminators. • MRI has comparable performance to ultrasonography for diagnosis of biliary atresia.
Numerical study of a cylinder model of the diffusion MRI signal for neuronal dendrite trees
Van Nguyen, Dang; Grebenkov, Denis; Le Bihan, Denis; Li, Jing-Rebecca
2015-03-01
We study numerically how the neuronal dendrite tree structure can affect the diffusion magnetic resonance imaging (dMRI) signal in brain tissue. For a large set of randomly generated dendrite trees, synthetic dMRI signals are computed and fitted to a cylinder model to estimate the effective longitudinal diffusivity DL in the direction of neurites. When the dendrite branches are short compared to the diffusion length, DL depends significantly on the ratio between the average branch length and the diffusion length. In turn, DL has very weak dependence on the distribution of branch lengths and orientations of a dendrite tree, and the number of branches per node. We conclude that the cylinder model which ignores the connectivity of the dendrite tree, can still be adapted to describe the apparent diffusion coefficient in brain tissue.
Kenyon, Amy; Gavriouchkina, Daria; Zorman, Jernej; Chong-Morrison, Vanessa; Napolitani, Giorgio; Cerundolo, Vincenzo; Sauka-Spengler, Tatjana
2018-04-06
A complex network of inflammatory genes is closely linked to somatic cell transformation and malignant disease. Immune cells and their associated molecules are responsible for detecting and eliminating cancer cells as they establish themselves as the precursors of a tumour. By the time a patient has a detectable solid tumour, cancer cells have escaped the initial immune response mechanisms. Here, we describe the development of a double binary zebrafish model that enables regulatory programming of the myeloid cells as they respond to oncogene-activated melanocytes to be explored, focussing on the initial phase when cells become the precursors of cancer. A hormone-inducible binary system allows for temporal control of expression of different Ras oncogenes ( NRas Q61K , HRas G12V and KRas G12V ) in melanocytes, leading to proliferation and changes in morphology of the melanocytes. This model was coupled to binary cell-specific biotagging models allowing in vivo biotinylation and subsequent isolation of macrophage or neutrophil nuclei for regulatory profiling of their active transcriptomes. Nuclear transcriptional profiling of neutrophils, performed as they respond to the earliest precursors of melanoma in vivo , revealed an intricate landscape of regulatory factors that may promote progression to melanoma, including Serpinb1l4, Fgf1, Fgf6, Cathepsin H, Galectin 1 and Galectin 3. The model presented here provides a powerful platform to study the myeloid response to the earliest precursors of melanoma. © 2018. Published by The Company of Biologists Ltd.
Effect of different tree mortality patterns on stand development in the forest model SIBYLA
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Trombik Jiří
2016-09-01
Full Text Available Forest mortality critically affects stand structure and the quality of ecosystem services provided by forests. Spruce bark beetle (Ips typographus generates rather complex infestation and mortality patterns, and implementation of such patterns in forest models is challenging. We present here the procedure, which allows to simulate the bark beetle-related tree mortality in the forest dynamics model Sibyla. We explored how sensitive various production and stand structure indicators are to tree mortality patterns, which can be generated by bark beetles. We compared the simulation outputs for three unmanaged forest stands with 40, 70 and 100% proportion of spruce as affected by the disturbance-related mortality that occurred in a random pattern and in a patchy pattern. The used tree species and age class-specific mortality rates were derived from the disturbance-related mortality records from Slovakia. The proposed algorithm was developed in the SQLite using the Python language, and the algorithm allowed us to define the degree of spatial clustering of dead trees ranging from a random distribution to a completely clustered distribution; a number of trees that died in either mode is set to remain equal. We found significant differences between the long-term developments of the three investigated forest stands, but we found very little effect of the tested mortality modes on stand increment, tree species composition and diversity, and tree size diversity. Hence, our hypothesis that the different pattern of dead trees emergence should affect the competitive interactions between trees and regeneration, and thus affect selected productivity and stand structure indicators was not confirmed.
Dong, Li-hu; Li, Feng-ri; Jia, Wei-wei; Liu, Fu-xiang; Wang, He-zhi
2011-10-01
Based on the biomass data of 516 sampling trees, and by using non-linear error-in-variable modeling approach, the compatible models for the total biomass and the biomass of six components including aboveground part, underground part, stem, crown, branch, and foliage of 15 major tree species (or groups) in Heilongjiang Province were established, and the best models for the total biomass and components biomass were selected. The compatible models based on total biomass were developed by adopting the method of joint control different level ratio function. The heteroscedasticity of the models for total biomass was eliminated with log transformation, and the weighted regression was applied to the models for each individual component. Among the compatible biomass models established for the 15 major species (or groups) , the model for total biomass had the highest prediction precision (90% or more), followed by the models for aboveground part and stem biomass, with a precision of 87.5% or more. The prediction precision of the biomass models for other components was relatively low, but it was still greater than 80% for most test tree species. The modeling efficiency (EF) values of the total, aboveground part, and stem biomass models for all the tree species (or groups) were over 0.9, and the EF values of the underground part, crown, branch, and foliage biomass models were over 0.8.
Modeling transcriptional networks regulating secondary growth and wood formation in forest trees.
Liu, Lijun; Filkov, Vladimir; Groover, Andrew
2014-06-01
The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary growth), but a comprehensive understanding of how these genes interact to influence woody growth is currently lacking. Modeling transcriptional networks has recently been made tractable by next-generation sequencing-based technologies that can comprehensively catalog gene expression and transcription factor-binding genome-wide, but has not yet been extensively applied to undomesticated tree species or woody growth. Here we discuss basic features of transcriptional networks, approaches for modeling biological networks, and examples of biological network models developed for forest trees to date. We discuss how transcriptional network research is being developed in the model forest tree genus, Populus, and how this research area can be further developed and applied. Transcriptional network models for forest tree secondary growth and wood formation could ultimately provide new predictive models to accelerate hypothesis-driven research and develop new breeding applications. © 2013 Scandinavian Plant Physiology Society.
Above- and Belowground Biomass Models for Trees in the Miombo Woodlands of Malawi
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Daud J. Kachamba
2016-02-01
Full Text Available In this study we present general (multiple tree species from several sites above- and belowground biomass models for trees in the miombo woodlands of Malawi. Such models are currently lacking in the country. The modelling was based on 74 trees comprising 33 different species with diameters at breast height (dbh and total tree height (ht ranging from 5.3 to 2 cm and from 3.0 to 25.0 m, respectively. Trees were collected from four silvicultural zones covering a wide range of conditions. We tested different models including dbh, ht and wood specific gravity ( ρ as independent variables. We evaluated model performance using pseudo-R2, root mean square error (RMSE, a covariance matrix for the parameter estimates, mean prediction error (MPE and relative mean prediction error (MPE%. Computation of MPE% was based on leave-one-out cross-validation. Values of pseudo-R2 and MPE% ranged 0.82–0.97 and 0.9%–2.8%, respectively. Model performance indicated that the models can be used over a wide range of geographical and ecological conditions in Malawi.
Shore, S N; van den Heuvel, EPJ
1994-01-01
This volume contains lecture notes presented at the 22nd Advanced Course of the Swiss Society for Astrophysics and Astronomy. The contributors deal with symbiotic stars, cataclysmic variables, massive binaries and X-ray binaries, in an attempt to provide a better understanding of stellar evolution.
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Igor B. Krasnyuk
2009-01-01
Full Text Available The asymptotical behavior of order parameter in confined binary mixture is considered in one-dimensional geometry. The interaction between bulk and surface forces in the mixture is investigated. Its established conditions are when the bulk spinodal decomposition may be ignored and when the main role in the process of formation of the oscillating asymptotic periodic spatiotemporal structures plays the surface-directed spinodal decomposition which is modelled by nonlinear dynamical boundary conditions.
Inverse modeling and animation of growing single-stemmed trees at interactive rates
S. Rudnick; L. Linsen; E.G. McPherson
2007-01-01
For city planning purposes, animations of growing trees of several species can be used to deduce which species may best fit a particular environment. The models used for the animation must conform to real measured data. We present an approach for inverse modeling to fit global growth parameters. The model comprises local production rules, which are iteratively and...
An object-oriented forest landscape model and its representation of tree species
Hong S. He; David J. Mladenoff; Joel Boeder
1999-01-01
LANDIS is a forest landscape model that simulates the interaction of large landscape processes and forest successional dynamics at tree species level. We discuss how object-oriented design (OOD) approaches such as modularity, abstraction and encapsulation are integrated into the design of LANDIS. We show that using OOD approaches, model decisions (olden as model...
Estimating the weight of Douglas-fir tree boles and logs with an iterative computer model.
Dale R. Waddell; Dale L Weyermann; Michael B. Lambert
1987-01-01
A computer model that estimates the green weights of standing trees was developed and validated for old-growth Douglas-fir. The model calculates the green weight for the entire bole, for the bole to any merchantable top, and for any log length within the bole. The model was validated by estimating the bias and accuracy of an independent subsample selected from the...
Don C. Bragg
2002-01-01
This article is an introduction to the computer software used by the Potential Relative Increment (PRI) approach to optimal tree diameter growth modeling. These DOS programs extract qualified tree and plot data from the Eastwide Forest Inventory Data Base (EFIDB), calculate relative tree increment, sort for the highest relative increments by diameter class, and...
International Nuclear Information System (INIS)
Mukhamedov, Farrukh; Saburov, Mansoor
2010-06-01
In the present paper we study forward Quantum Markov Chains (QMC) defined on a Cayley tree. Using the tree structure of graphs, we give a construction of quantum Markov chains on a Cayley tree. By means of such constructions we prove the existence of a phase transition for the XY-model on a Cayley tree of order three in QMC scheme. By the phase transition we mean the existence of two distinct QMC for the given family of interaction operators {K }. (author)
Development of a model of the coronary arterial tree for the 4D XCAT phantom
Fung, George S. K.; Segars, W. Paul; Gullberg, Grant T.; Tsui, Benjamin M. W.
2011-09-01
A detailed three-dimensional (3D) model of the coronary artery tree with cardiac motion has great potential for applications in a wide variety of medical imaging research areas. In this work, we first developed a computer-generated 3D model of the coronary arterial tree for the heart in the extended cardiac-torso (XCAT) phantom, thereby creating a realistic computer model of the human anatomy. The coronary arterial tree model was based on two datasets: (1) a gated cardiac dual-source computed tomography (CT) angiographic dataset obtained from a normal human subject and (2) statistical morphometric data of porcine hearts. The initial proximal segments of the vasculature and the anatomical details of the boundaries of the ventricles were defined by segmenting the CT data. An iterative rule-based generation method was developed and applied to extend the coronary arterial tree beyond the initial proximal segments. The algorithm was governed by three factors: (1) statistical morphometric measurements of the connectivity, lengths and diameters of the arterial segments; (2) avoidance forces from other vessel segments and the boundaries of the myocardium, and (3) optimality principles which minimize the drag force at the bifurcations of the generated tree. Using this algorithm, the 3D computational model of the largest six orders of the coronary arterial tree was generated, which spread across the myocardium of the left and right ventricles. The 3D coronary arterial tree model was then extended to 4D to simulate different cardiac phases by deforming the original 3D model according to the motion vector map of the 4D cardiac model of the XCAT phantom at the corresponding phases. As a result, a detailed and realistic 4D model of the coronary arterial tree was developed for the XCAT phantom by imposing constraints of anatomical and physiological characteristics of the coronary vasculature. This new 4D coronary artery tree model provides a unique simulation tool that can be
Effect of CO and H adsorption on the compositional structure of binary nanoalloys via DFT modeling
West, Paul S.; Johnston, Roy L.; Barcaro, Giovanni; Fortunelli, Alessandro
2013-08-01
A theoretical approach to investigate the influence of CO and H adsorption on the compositional structure or chemical ordering of binary metal nanoclusters is applied to selected representative pairs: AuPd, PdPt, CuPt and PdRh. The truncated octahedral (TO) 38-atom cluster is chosen as a model of small fcc nanoclusters because its high-symmetry allows a simpler analysis and a reduced computational effort. A number of CO and H ligands (ranging from 1 to 8) are adsorbed on atop sites at the centre of (111) facets of the cluster, and the corresponding energetics are analyzed in detail. A strong tendency to segregation inversion from AuPd shell/core to core/shell is found upon CO adsorption, qualitatively very similar even though more pronounced than that found for the PdRh pair (where Pd plays the role of Au and Rh that of Pd). This effect is still present, but quantitatively modest, in PdPt. The value of the CO binding energy decreases in the sequence: Rh > Pt > Pd > Au, and is scarcely affected by the presence of neighbouring hetero-species (minor electronic effect). A clear electronic effect is instead found in the CuPt case, in which the strengthening of Pt-CO bonds when Cu neighbours surround the interacting Pt atom brings Cu from the centres to the edges of (111) facets in Pt-rich clusters upon CO adsorption. H adsorption brings about qualitatively similar effects, although to a much smaller degree, so that a definite segregation inversion is only predicted for the AuPd pair. The predicted trends are found to be in good agreement with available experimental results.
Kim, Inyoung; Pang, Herbert; Zhao, Hongyu
2013-01-01
Many statistical methods for microarray data analysis consider one gene at a time, and they may miss subtle changes at the single gene level. This limitation may be overcome by considering a set of genes simultaneously where the gene sets are derived from prior biological knowledge. Limited work has been carried out in the regression setting to study the effects of clinical covariates and expression levels of genes in a pathway either on a continuous or on a binary clinical outcome. Hence, we propose a Bayesian approach for identifying pathways related to both types of outcomes. We compare our Bayesian approaches with a likelihood-based approach that was developed by relating a least squares kernel machine for nonparametric pathway effect with a restricted maximum likelihood for variance components. Unlike the likelihood-based approach, the Bayesian approach allows us to directly estimate all parameters and pathway effects. It can incorporate prior knowledge into Bayesian hierarchical model formulation and makes inference by using the posterior samples without asymptotic theory. We consider several kernels (Gaussian, polynomial, and neural network kernels) to characterize gene expression effects in a pathway on clinical outcomes. Our simulation results suggest that the Bayesian approach has more accurate coverage probability than the likelihood-based approach, and this is especially so when the sample size is small compared with the number of genes being studied in a pathway. We demonstrate the usefulness of our approaches through its applications to a type II diabetes mellitus data set. Our approaches can also be applied to other settings where a large number of strongly correlated predictors are present. PMID:22438129
Modeling non-linear growth responses to temperature and hydrology in wetland trees
Keim, R.; Allen, S. T.
2016-12-01
Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.
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Marijke van Kuijk
2014-07-01
Full Text Available Excessive growth of non-woody plants and shrubs on degraded lands can strongly hamper tree growth and thus secondary forest succession. A common method to accelerate succession, called liberation, involves opening up the vegetation canopy around young target trees. This can increase growth of target trees by reducing competition for light with neighboring plants. However, liberation has not always the desired effect, likely due to differences in light requirement between tree species. Here we present a 3D-model, which calculates photosynthetic rate of individual trees in a vegetation stand. It enables us to examine how stature, crown structure and physiological traits of target trees and characteristics of the surrounding vegetation together determine effects of light on tree growth. The model was applied to a liberation experiment conducted with three pioneer species in a young secondary forest in Vietnam. Species responded differently to the treatment depending on their height, crown structure and their shade-tolerance level. Model simulations revealed practical thresholds over which the tree growth response is heavily influenced by the height and density of surrounding vegetation and gap radius. There were strong correlations between calculated photosynthetic rates and observed growth: the model was well able to predict growth of trees in young forests and the effects of liberation there upon. Thus our model serves as a useful tool to analyze light competition between young trees and surrounding vegetation and may help assess the potential effect of tree liberation.
van Kuijk, Marijke; Anten, Niels P R; Oomen, Roelof J; Schieving, Feike
2014-01-01
Excessive growth of non-woody plants and shrubs on degraded lands can strongly hamper tree growth and thus secondary forest succession. A common method to accelerate succession, called liberation, involves opening up the vegetation canopy around young target trees. This can increase growth of target trees by reducing competition for light with neighboring plants. However, liberation has not always had the desired effect, likely due to differences in light requirement between tree species. Here we present a 3D-model, which calculates photosynthetic rate of individual trees in a vegetation stand. It enables us to examine how stature, crown structure, and physiological traits of target trees and characteristics of the surrounding vegetation together determine effects of light on tree growth. The model was applied to a liberation experiment conducted with three pioneer species in a young secondary forest in Vietnam. Species responded differently to the treatment depending on their height, crown structure and their shade-tolerance level. Model simulations revealed practical thresholds over which the tree growth response is heavily influenced by the height and density of surrounding vegetation and gap radius. There were strong correlations between calculated photosynthetic rates and observed growth: the model was well able to predict growth of trees in young forests and the effects of liberation there upon. Thus, our model serves as a useful tool to analyze light competition between young trees and surrounding vegetation and may help assess the potential effect of tree liberation.
Efficient modelling of foliage distribution and crown dynamics in monolayer tree species.
Beyer, Robert
2017-12-01
In response to the computational limitations of individual leaf-based tree growth models, this article presents a new approach for the efficient characterisation of the spatial distribution of foliage in monolayered trees in terms of 2D foliage surfaces. Much like the recently introduced 3D leaf area density, this concept accommodates local crown plasticity, which is a common weak point in large-scale growth models. Recognizing phototropism as the predominant driver of spatial crown expansion, we define the local light gradient on foliage surfaces. We consider the partial differential equation describing the evolution of a curve expanding along the light gradient and present an explicit solution. The article concludes with an illustration of the incorporation of foliage surfaces in a simple tree growth model for European beech (Fagus sylvatica L.), and discusses perspectives for applications in functional-structural models.
Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree.
Kim, Jaekwon; Lee, Jongsik; Lee, Youngho
2015-07-01
The importance of the prediction of coronary heart disease (CHD) has been recognized in Korea; however, few studies have been conducted in this area. Therefore, it is necessary to develop a method for the prediction and classification of CHD in Koreans. A model for CHD prediction must be designed according to rule-based guidelines. In this study, a fuzzy logic and decision tree (classification and regression tree [CART])-driven CHD prediction model was developed for Koreans. Datasets derived from the Korean National Health and Nutrition Examination Survey VI (KNHANES-VI) were utilized to generate the proposed model. The rules were generated using a decision tree technique, and fuzzy logic was applied to overcome problems associated with uncertainty in CHD prediction. The accuracy and receiver operating characteristic (ROC) curve values of the propose systems were 69.51% and 0.594, proving that the proposed methods were more efficient than other models.
Risk Modelling of Late Spring Frost Damage on Fruit Trees, Case Study; Apple Tree, Mashhad Plain
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M Rahimi
2012-02-01
Full Text Available Mashhad plain is one of the most important regions of Apple cultivated areas. Occurring spring late frost creates a lot of damages on bud and decreasing the yield of Apple in this region. Assessment and risk modeling of frost damage would be useful to manage and decrease the damage. The study area is a part of Khorasan Razavi province which is located in Mashhad plain. This region is located in Northeast Iran (36º to 37 º N, 58 º 30' to 60 º E. The area of this region is about 13000 square km which is about one tenth of Khorasan province area. In order to modeling frost damage risk 12 affective parameters including climatological(Minimum temperature, temperature decreasing rate, temperature Increasing rate, Julian days of frost, cumulative degree days, Area under zero line, and frost duration and geographical parameters (Elevation, Longitude, Latitude, Aspect, and slope were selected. 3 damage full radiative frosts were selected in the period of Apple flowering time which was dated 20 April 2003, 8 April 2005, and 28 March 2005. Required meteorological data were collected from 9 meteorological standard stations inside and outside of study area. Linear multiple regression were used to modeling the relationship. The map for each parameter was plotted by using suitable interpolation method including IDW; Spline; Kriging. A grid map was defined with 5 by 5 kilometers to extract enough data for entering to the model. The regression equation was significant at the level of 99% significance. By using this equation the predicted amounts of frost risk damage were calculated for each point of grid and also the map was plotted. The regression equation of observed and predicted frost damage risk was provided by correlation of 0.93 and the error map also was prepared. According to this study in frost of 31 Farvardin 1388 South West parts of the plain estimated as the most frost risk areas by %53.19 and the southeast parts were estimated as the least
International Nuclear Information System (INIS)
Santos, Ivan; Marques, Luis A.; Pelaz, Lourdes; Lopez, Pedro
2007-01-01
In this paper, we present classical molecular dynamics results about the formation of amorphous pockets in silicon for energy transfers below the displacement threshold. While in binary collision simulations ions with different masses generate the same number of Frenkel pairs for the same deposited nuclear energy, in molecular dynamics simulations the amount of damage and its complexity increase with ion mass. We demonstrate that low-energy transfers to target atoms are able to generate complex damage structures. We have determined the conditions that have to be fulfilled to produce amorphous pockets, showing that the order-disorder transition depends on the particular competition between melting and heat diffusion processes. We have incorporated these molecular dynamics results in an improved binary collision model that is able to provide a good description of damage with a very low computational cost
Directory of Open Access Journals (Sweden)
Xiliang Ni
2014-04-01
Full Text Available The ultimate goal of our multi-article series is to demonstrate the Allometric Scaling and Resource Limitation (ASRL approach for mapping tree heights and biomass. This third article tests the feasibility of the optimized ASRL model over China at both site (14 meteorological stations and continental scales. Tree heights from the Geoscience Laser Altimeter System (GLAS waveform data are used for the model optimizations. Three selected ASRL parameters (area of single leaf, α; exponent for canopy radius, η; and root absorption efficiency, γ are iteratively adjusted to minimize differences between the references and predicted tree heights. Key climatic variables (e.g., temperature, precipitation, and solar radiation are needed for the model simulations. We also exploit the independent GLAS and in situ tree heights to examine the model performance. The predicted tree heights at the site scale are evaluated against the GLAS tree heights using a two-fold cross validation (RMSE = 1.72 m; R2 = 0.97 and bootstrapping (RMSE = 4.39 m; R2 = 0.81. The modeled tree heights at the continental scale (1 km spatial resolution are compared to both GLAS (RMSE = 6.63 m; R2 = 0.63 and in situ (RMSE = 6.70 m; R2 = 0.52 measurements. Further, inter-comparisons against the existing satellite-based forest height maps have resulted in a moderate degree of agreements. Our results show that the optimized ASRL model is capable of satisfactorily retrieving tree heights over continental China at both scales. Subsequent studies will focus on the estimation of woody biomass after alleviating the discussed limitations.
An analytic model for the evolution of a close binary system of neutron (degenerate) stars
Imshennik, V. S.; Popov, D. V.
1998-03-01
The evolution of a close binary system of neutron stars is studied in the point-mass approximation with allowance for gravitational radiation and mass exchange between the components of the system. The calculation of mass transfer from the low-mass component of the system based on the known approximations for the radii of the Roche lobe and the low-mass component provides the reliable determination of the characteristics of the system by the end of its evolution, which are virtually independent of the initial ratio of the component masses. The evolution of the system is accompanied by the mass loss from the low-mass component and ends in the explosion of this component at the time when its mass reaches the lower limit for neutron stars (close to 0.1 M_solar). After the explosion, the second component of the system leaves the supernova remnant with the speed and rotation period which are determined almost entirely by the total mass of the system M_t. The assumption about the explosion of the low-mass component and subsequent escape of the high-mass component (pulsar or black hole) from the system have been made in the recently proposed scenario of the explosion of collapsing supernovae with allowance for rotational effects (Imshennik 1992; Imshennik and Nadezhin 1992; Imshennik and Popov 1996). We formulate and substantiate an analytic model for the evolution of the system under consideration, in which virtually all mass exchange between the components occurs under the assumption of quasi-stationary circular orbits with significant energy and angular momentum losses related to gravitational radiation. Such character of the evolution persists until the time the mass of the low-mass component reaches the value of order ~ 0.15 M_solar. The remaining mass (~0.05 M_solar) is lost by this component in the dynamical regime and the given analytic model takes on, strictly speaking, the character of a crude estimate. On the basis of this model, the main features of
Improved allometric models to estimate the aboveground biomass of tropical trees.
Chave, Jérôme; Réjou-Méchain, Maxime; Búrquez, Alberto; Chidumayo, Emmanuel; Colgan, Matthew S; Delitti, Welington B C; Duque, Alvaro; Eid, Tron; Fearnside, Philip M; Goodman, Rosa C; Henry, Matieu; Martínez-Yrízar, Angelina; Mugasha, Wilson A; Muller-Landau, Helene C; Mencuccini, Maurizio; Nelson, Bruce W; Ngomanda, Alfred; Nogueira, Euler M; Ortiz-Malavassi, Edgar; Pélissier, Raphaël; Ploton, Pierre; Ryan, Casey M; Saldarriaga, Juan G; Vieilledent, Ghislain
2014-10-01
Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven-dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter-height relationship depended linearly on a bioclimatic stress variable E, which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter-height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development. © 2014 John Wiley & Sons Ltd.
Coupled 0D-1D CFD Modeling of Right Heart and Pulmonary Artery Morphometry Tree
Dong, Melody; Yang, Weiguang; Feinstein, Jeffrey A.; Marsden, Alison
2017-11-01
Pulmonary arterial hypertension (PAH) is characterized by elevated pulmonary artery (PA) pressure and remodeling of the distal PAs resulting in right ventricular (RV) dysfunction and failure. It is hypothesized that patients with untreated ventricular septal defects (VSD) may develop PAH due to elevated flows and pressures in the PAs. Wall shear stress (WSS), due to elevated flows, and circumferential stress, due to elevated pressures, are known to play a role in vascular mechanobiology. Thus, simulating VSD hemodynamics and wall mechanics may facilitate our understanding of mechanical stimuli leading to PAH initiation and progression. Although 3D CFD models can capture detailed hemodynamics in the proximal PAs, they cannot easily model hemodynamics and wave propagation in the distal PAs, where remodeling occurs. To improve current PA models, we will present a new method that couples distal PA hemodynamics with RV function. Our model couples a 0D lumped parameter model of the RV to a 1D model of the PA tree, based on human PA morphometry data, to characterize RV performance and WSS changes in the PA tree. We will compare a VSD 0D-1D model and a 0D-3D model coupled to a mathematical morphometry tree model to quantify WSS in the entire PA vascular tree.
Modeling and optimization of geothermal power plants using the binary fluid cycle
Energy Technology Data Exchange (ETDEWEB)
Walter, R.A.
1976-09-01
A computer simulation of a binary fluid cycle power plant for use with geothermal energy sources, and the subsequent optimization of this power plant type over a range of geothermal source conditions are described. The optimization technique employed for this analysis was based upon the principle of maximum use of geothermal energy.
Aasi, J.; Agathos, M.; Beker, M.G.; Bertolini, A.; Blom, M.R.; Bulten, H.J.; Del Pozzo, W.; Jonker, R.; Li, T.G.F.; Meidam, J.; van den Brand, J.F.J.; van der Putten, S.
2014-01-01
The Numerical INJection Analysis (NINJA) project is a collaborative effort between members of the numerical relativity and gravitational-wave (GW) astrophysics communities. The purpose of NINJA is to study the ability to detect GWs emitted from merging binary black holes (BBH) and recover their
Yang, H.; Doll, Robert; Meijer, Hil Gaétan Ellart; Buitenweg, Jan R.; Nyssen, M.
2011-01-01
In psychophysics, the response to a stimulus is usually limited to a single value during some time interval. Moreover, the response is usually quantified, e.g., binary (yes or no). Such data is very limited information for parameter estimation. A particular example is the response to a sensory
Xiao, Guoqiang; Jiang, Yang; Song, Gang; Jiang, Jianmin
2010-12-01
We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.
Behavior and sensitivity of an optimal tree diameter growth model under data uncertainty
Don C. Bragg
2005-01-01
Using loblolly pine, shortleaf pine, white oak, and northern red oak as examples, this paper considers the behavior of potential relative increment (PRI) models of optimal tree diameter growth under data uncertainity. Recommendations on intial sample size and the PRI iteractive curve fitting process are provided. Combining different state inventories prior to PRI model...
Rich Interfaces for Dependability: Compositional Methods for Dynamic Fault Trees and Arcade models
Boudali, H.; Crouzen, Pepijn; Haverkort, Boudewijn R.H.M.; Kuntz, G.W.M.; Stoelinga, Mariëlle Ida Antoinette
This paper discusses two behavioural interfaces for reliability analysis: dynamic fault trees, which model the system reliability in terms of the reliability of its components and Arcade, which models the system reliability at an architectural level. For both formalisms, the reliability is analyzed
Tree root systems competing for soil moisture in a 3D soil–plant model
Gabriele Manoli; Sara Bonetti; Jean-Christophe Domec; Mario Putti; Gabriel Katul; Marco Marani
2014-01-01
Competition for water among multiple tree rooting systems is investigated using a soilâplant model that accounts for soil moisture dynamics and root water uptake (RWU), whole plant transpiration, and leaflevel photosynthesis. The model is based on a numerical solution to the 3D Richards equation modified to account for a 3D RWU, trunk xylem, and stomatal conductances....
New efficient utility upper bounds for the fully adaptive model of attack trees
Buldas, Ahto; Lenin, Aleksandr
2013-01-01
We present a new fully adaptive computational model for attack trees that allows attackers to repeat atomic attacks if they fail and to play on if they are caught and have to pay penalties. The new model allows safer conclusions about the security of real-life systems and is somewhat
Czech Academy of Sciences Publication Activity Database
Svoboda, Jiří; Gamsjäger, E.
2011-01-01
Roč. 102, č. 6 (2011), s. 666-673 ISSN 1862-5282 R&D Projects: GA MŠk(CZ) OC10029 Institutional research plan: CEZ:AV0Z20410507 Keywords : modelling * phase transformation * ediffusion Subject RIV: BJ - Thermodynamics Impact factor: 0.830, year: 2011
Hipsometric relationship modeling using data sampled in tree scaling and inventory plots
Directory of Open Access Journals (Sweden)
Valdir Carlos Lima de Andrade
2011-02-01
Full Text Available This work evaluated eight hypsometric models to represent tree height-diameter relationship, using data obtained from the scaling of 118 trees and 25 inventory plots. Residue graphic analysis and percent deviation mean criteria, qui-square test precision, residual standard error between real and estimated heights and the graybill f test were adopted. The identity of the hypsometric models was also verified by applying the F(Ho test on the plot data grouped to the scaling data. It was concluded that better accuracy can be obtained by using the model prodan, with h and d1,3 data measured in 10 trees by plots grouped into these scaling data measurements of even-aged forest stands.
A method for generating stochastic 3D tree models with Python in Autodesk Maya
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Nemanja Stojanović
2016-12-01
Full Text Available This paper introduces a method for generating 3D tree models using stochastic L-systems with stochastic parameters and Perlin noise. L-system is the most popular method for plant modeling and Perlin noise is extensively used for generating high detailed textures. Our approach is probabilistic. L-systems with a random choice of parameters can represent observed objects quite well and they are used for modeling and generating realistic plants. Textures and normal maps are generated with combinations of Perlin noises what make these trees completely unique. Script for generating these trees, textures and normal maps is written with Python/PyMEL/NumPy in Autodesk Maya.
Directory of Open Access Journals (Sweden)
X. Zhou
2017-12-01
Full Text Available Forest plantations have been widely used as an effective measure for increasing soil carbon (C, and nitrogen (N stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species–enzyme–C∕N model to investigate how temperature and tree species influence soil C∕N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG, N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP and phosphorus acquisition enzymes (acid phosphatases. The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01–2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99–2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii and hoop pine (Araucaria cunninghamii Ait., increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22–1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native
Zhou, Xiaoqi; Wang, Shen S. J.; Chen, Chengrong
2017-12-01
Forest plantations have been widely used as an effective measure for increasing soil carbon (C), and nitrogen (N) stocks and soil enzyme activities play a key role in soil C and N losses during decomposition of soil organic matter. However, few studies have been carried out to elucidate the mechanisms behind the differences in soil C and N cycling by different tree species in response to climate warming. Here, we measured the responses of soil's extracellular enzyme activity (EEA) to a gradient of temperatures using incubation methods in 78-year-old forest plantations with different tree species. Based on a soil enzyme kinetics model, we established a new statistical model to investigate the effects of temperature and tree species on soil EEA. In addition, we established a tree species-enzyme-C/N model to investigate how temperature and tree species influence soil C/N contents over time without considering plant C inputs. These extracellular enzymes included C acquisition enzymes (β-glucosidase, BG), N acquisition enzymes (N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) and phosphorus acquisition enzymes (acid phosphatases). The results showed that incubation temperature and tree species significantly influenced all soil EEA and Eucalyptus had 1.01-2.86 times higher soil EEA than coniferous tree species. Modeling showed that Eucalyptus had larger soil C losses but had 0.99-2.38 times longer soil C residence time than the coniferous tree species over time. The differences in the residual soil C and N contents between Eucalyptus and coniferous tree species, as well as between slash pine (Pinus elliottii Engelm. var. elliottii) and hoop pine (Araucaria cunninghamii Ait.), increase with time. On the other hand, the modeling results help explain why exotic slash pine can grow faster, as it has 1.22-1.38 times longer residual soil N residence time for LAP, which mediate soil N cycling in the long term, than native coniferous tree species like hoop pine and
Lynch, John James
1990-01-01
The modified Leung-Griffiths model is a corresponding states theory applied to mixtures that successfully correlates, evaluates, and predicts vapor-liquid equilibrium (VLE) boundaries for binary fluid mixtures. The strength of the model lies in its excellent performance at and near the critical locus down to about half of the critical pressures. Conventional phase equilibrium algorithms based on classical equations of state generally fail to converge or are inaccurate near the critical locus. The modified Leung-Griffiths model, however, incorporates nonclassical, scaling-law critical exponents. Because of the universality of critical behavior, the technique is relatively insensitive to phenomena such as polarity or hydrogen bonding which usually cause severe calculation problems. This thesis covers several topics. The first is an investigation into some of the near-critical phenomena of binary fluid mixtures using asymptotic expansions. Dew -bubble curves are expanded through five orders about the critical locus within the formalism of the model. Explicit mathematical representations of the curves are obtained and the coefficients of the expansions are closely evaluated. Another subject, one that has had a significant impact on the progress of the remainder of the work, is the problem of fitting VLE data to non-linear functions. This problem is discussed and examples of systematic non-linear fits are presented. The next topic is the incorporation of "extended scaling," the Wegner correction, into the theory. This extension improves the performance of the model for binary mixtures with wide dew-bubble curves, that is mixtures with two highly dissimilar components. Finally, a study of the predictive capabilities and limitations of the model is presented.
Qiu, Xuchun; Tanoue, Wataru; Kawaguchi, Atsushi; Yanagawa, Takashi; Seki, Masanori; Shimasaki, Yohei; Honjo, Tsuneo; Oshima, Yuji
2017-12-31
Organisms in natural environments are often exposed to a broad variety of chemicals, and the multi-chemical mixtures exposure may produce significant toxic effects, even though the individual chemicals are present at concentrations below their no-observed-effect concentrations. This study represents the first attempt that uses the accelerated failure time (AFT) model to quantify the interaction and toxicity of multi-chemical mixtures in environmental toxicology. We firstly conducted the acute immobilization tests with Daphnia magna exposed to mixtures of diazinon (DZN), fenitrothion (MEP); and thiobencarb (TB) in single, binary, and ternary formulations, and then fitted the results to the AFT model. The 48-h EC 50 (concentration required to immobilize 50% of the daphnids at 48h) values for each pesticide obtained from the AFT model are within a factor of 2 of the corresponding values calculated from the single pesticide exposure tests, indicating the methodology is able to provide credible toxicity values. The AFT model revealed either significant synergistic (DZN and MEP; DZN and TB) or antagonistic (MEP and TB) interactions in binary mixtures, while the interaction pattern of ternary mixture depended on both the concentration levels and concentration ratios of pesticides. With a factor of 2, the AFT model accurately estimated the toxicities for 78% of binary mixture formulations that exhibited significant synergistic effects, and the toxicities for all the ternary formulations. Our results showed that the AFT model can provide a simple and efficient way to quantify the interactions between pesticides and to assess the toxicity of their mixtures. This ability may greatly facilitate the ecotoxicological risk assessment of exposure to multi-chemical mixtures. Copyright © 2017 Elsevier B.V. All rights reserved.
Event and fault tree model for reliability analysis of the greek research reactor
International Nuclear Information System (INIS)
Fault trees and event trees are widely used in industry to model and to evaluate the reliability of safety systems. Detailed analyzes in nuclear installations require the combination of these two techniques. This work uses the methods of fault tree (FT) and event tree (ET) to perform the Probabilistic Safety Assessment (PSA) in research reactors. The PSA according to IAEA (International Atomic Energy Agency) is divided into Level 1, Level 2 and level 3. At Level 1, conceptually safety systems act to prevent the accident, at Level 2, the accident occurred and seeks to minimize the consequences, known as stage management of the accident, and at Level 3 are determined consequences. This paper focuses on Level 1 studies, and searches through the acquisition of knowledge consolidation of methodologies for future reliability studies. The Greek Research Reactor, GRR - 1, was used as a case example. The LOCA (Loss of Coolant Accident) was chosen as the initiating event and from there were developed the possible accident sequences, using event tree, which could lead damage to the core. Furthermore, for each of the affected systems, the possible accidents sequences were made fault tree and evaluated the probability of each event top of the FT. The studies were conducted using a commercial computational tool SAPHIRE. The results thus obtained, performance or failure to act of the systems analyzed were considered satisfactory. This work is directed to the Greek Research Reactor due to data availability. (author)
Modelling Water Uptake Provides a New Perspective on Grass and Tree Coexistence.
Directory of Open Access Journals (Sweden)
Michael G Mazzacavallo
Full Text Available Root biomass distributions have long been used to infer patterns of resource uptake. These patterns are used to understand plant growth, plant coexistence and water budgets. Root biomass, however, may be a poor indicator of resource uptake because large roots typically do not absorb water, fine roots do not absorb water from dry soils and roots of different species can be difficult to differentiate. In a sub-tropical savanna, Kruger Park, South Africa, we used a hydrologic tracer experiment to describe the abundance of active grass and tree roots across the soil profile. We then used this tracer data to parameterize a water movement model (Hydrus 1D. The model accounted for water availability and estimated grass and tree water uptake by depth over a growing season. Most root biomass was found in shallow soils (0-20 cm and tracer data revealed that, within these shallow depths, half of active grass roots were in the top 12 cm while half of active tree roots were in the top 21 cm. However, because shallow soils provided roots with less water than deep soils (20-90 cm, the water movement model indicated that grass and tree water uptake was twice as deep as would be predicted from root biomass or tracer data alone: half of grass and tree water uptake occurred in the top 23 and 43 cm, respectively. Niche partitioning was also greater when estimated from water uptake rather than tracer uptake. Contrary to long-standing assumptions, shallow grass root distributions absorbed 32% less water than slightly deeper tree root distributions when grasses and trees were assumed to have equal water demands. Quantifying water uptake revealed deeper soil water uptake, greater niche partitioning and greater benefits of deep roots than would be estimated from root biomass or tracer uptake data alone.
Predictive models of tree-growth: preliminary results in the French Alps
Tessier, Lucien; Keller, Thierry; Guiot, Joel; Edouard, Jean-Louis; Guibal, Frédéric
The analysis of tree-ring-climate relationships provides models (response functions) of tree-growth calibrated on the inter-annual variability of climate. Output of GCMs can be used as inputs of these models in order to evaluate the change in radial growth induced by climatic change. A spatiotemporal approach applied to a large data set of ring-width chronologies and meteorological data allows the response of trees to be evaluated for different populations of various species in numerous habitats. Such a study was carried out, firstly on ten populations in south-eastern France, then on populations at high-altitude sites. The species involved were Larix decidua, Mill., Pinus sylvestris, L., Abies alba, Mill., and Picea abies Karst. The calibration of tree ring to climate relationships was based on the monthly values of precipitation and temperature provided by meteorological stations more or less distant from the tree sites. Outputs of GCMs were obtained from the ARPEGE model of Météo-France with a simulation on a large grid (2°79 in latitude and 3° in longitude) for the hypothesis of a CO2 doubling. Results show that climatic change can induce either an increase or a decrease in the mean radial growth. For most of the tree-populations, no significant change was apparent. The results suffer from insufficient data related to the spatial representation of climate (i.e. stations that are too far from the tree populations, only two grid points available from the GCMs, etc.).
Lee, Seung-Mi; Kang, Jin-Oh; Suh, Yong-Moo
2004-10-01
Analysis and prediction of the care charges related to colorectal cancer in Korea are important for the allocation of medical resources and the establishment of medical policies because the incidence and the hospital charges for colorectal cancer are rapidly increasing. But the previous studies based on statistical analysis to predict the hospital charges for patients did not show satisfactory results. Recently, data mining emerges as a new technique to extract knowledge from the huge and diverse medical data. Thus, we built models using data mining techniques to predict hospital charge for the patients. A total of 1,022 admission records with 154 variables of 492 patients were used to build prediction models who had been treated from 1999 to 2002 in the Kyung Hee University Hospital. We built an artificial neural network (ANN) model and a classification and regression tree (CART) model, and compared their prediction accuracy. Linear correlation coefficients were high in both models and the mean absolute errors were similar. But ANN models showed a better linear correlation than CART model (0.813 vs. 0.713 for the hospital charge paid by insurance and 0.746 vs. 0.720 for the hospital charge paid by patients). We suggest that ANN model has a better performance to predict charges of colorectal cancer patients.
Directory of Open Access Journals (Sweden)
A. C. D. Freitas
2013-03-01
Full Text Available Ionic liquids (IL have been described as novel environmentally benign solvents because of their remarkable characteristics. Numerous applications of these solvents continue to grow at an exponential rate. In this work, high pressure vapor liquid equilibria for 17 different IL + gas binary systems were modeled at different temperatures with Peng-Robinson (PR and Soave-Redlich-Kwong (SRK equations of state, combined with the van der Waals mixing rule with two binary interaction parameters (vdW-2. The experimental data were taken from the literature. The optimum binary interaction parameters were estimated by minimization of an objective function based on the average absolute relative deviation of liquid and vapor phases, using the modified Simplex algorithm. The solubilities of all gases studied in this work decrease as the temperature increases and increase with increasing pressure. The correlated results were highly satisfactory, with average absolute relative deviations of 2.10% and 2.25% for PR-vdW-2 and SRK-vdW-2, respectively.
By, Kunthel; Qaqish, Bahjat F; Preisser, John S; Perin, Jamie; Zink, Richard C
2014-02-01
This article describes a new software for modeling correlated binary data based on orthogonalized residuals, a recently developed estimating equations approach that includes, as a special case, alternating logistic regressions. The software is flexible with respect to fitting in that the user can choose estimating equations for association models based on alternating logistic regressions or orthogonalized residuals, the latter choice providing a non-diagonal working covariance matrix for second moment parameters providing potentially greater efficiency. Regression diagnostics based on this method are also implemented in the software. The mathematical background is briefly reviewed and the software is applied to medical data sets. Published by Elsevier Ireland Ltd.
Can plasticity make spatial structure irrelevant in individual-tree models?
Directory of Open Access Journals (Sweden)
Oscar García
2014-08-01
Full Text Available Background Distance-dependent individual-tree models have commonly been found to add little predictive power to that of distance-independent ones. One possible reason is plasticity, the ability of trees to lean and to alter crown and root development to better occupy available growing space. Being able to redeploy foliage (and roots into canopy gaps and less contested areas can diminish the importance of stem ground locations. Methods Plasticity was simulated for 3 intensively measured forest stands, to see to what extent and under what conditions the allocation of resources (e.g., light to the individual trees depended on their ground coordinates. The data came from 50 × 60 m stem-mapped plots in natural monospecific stands of jack pine, trembling aspen and black spruce from central Canada. Explicit perfect-plasticity equations were derived for tessellation-type models. Results Qualitatively similar simulation results were obtained under a variety of modelling assumptions. The effects of plasticity varied somewhat with stand uniformity and with assumed plasticity limits and other factors. Stand-level implications for canopy depth, distribution modelling and total productivity were examined. Conclusions Generally, under what seem like conservative maximum plasticity constraints, spatial structure accounted for less than 10% of the variance in resource allocation. The perfect-plasticity equations approximated well the simulation results from tessellation models, but not those from models with less extreme competition asymmetry. Whole-stand perfect plasticity approximations seem an attractive alternative to individual-tree models.
Reconstruction of late Holocene climate based on tree growth and mechanistic hierarchical models
Tipton, John; Hooten, Mevin B.; Pederson, Neil; Tingley, Martin; Bishop, Daniel
2016-01-01
Reconstruction of pre-instrumental, late Holocene climate is important for understanding how climate has changed in the past and how climate might change in the future. Statistical prediction of paleoclimate from tree ring widths is challenging because tree ring widths are a one-dimensional summary of annual growth that represents a multi-dimensional set of climatic and biotic influences. We develop a Bayesian hierarchical framework using a nonlinear, biologically motivated tree ring growth model to jointly reconstruct temperature and precipitation in the Hudson Valley, New York. Using a common growth function to describe the response of a tree to climate, we allow for species-specific parameterizations of the growth response. To enable predictive backcasts, we model the climate variables with a vector autoregressive process on an annual timescale coupled with a multivariate conditional autoregressive process that accounts for temporal correlation and cross-correlation between temperature and precipitation on a monthly scale. Our multi-scale temporal model allows for flexibility in the climate response through time at different temporal scales and predicts reasonable climate scenarios given tree ring width data.
Proxy system modeling of tree-ring isotope chronologies over the Common Era
Anchukaitis, K. J.; LeGrande, A. N.
2017-12-01
The Asian monsoon can be characterized in terms of both precipitation variability and atmospheric circulation across a range of spatial and temporal scales. While multicentury time series of tree-ring widths at hundreds of sites across Asia provide estimates of past rainfall, the oxygen isotope ratios of annual rings may reveal broader regional hydroclimate and atmosphere-ocean dynamics. Tree-ring oxygen isotope chronologies from Monsoon Asia have been interpreted to reflect a local 'amount effect', relative humidity, source water and seasonality, and winter snowfall. Here, we use an isotope-enabled general circulation model simulation from the NASA Goddard Institute for Space Science (GISS) Model E and a proxy system model of the oxygen isotope composition of tree-ring cellulose to interpret the large-scale and local climate controls on δ 18O chronologies. Broad-scale dominant signals are associated with a suite of covarying hydroclimate variables including growing season rainfall amounts, relative humidity, and vapor pressure deficit. Temperature and source water influences are region-dependent, as are the simulated tree-ring isotope signals associated with the El Nino Southern Oscillation (ENSO) and large-scale indices of the Asian monsoon circulation. At some locations, including southern coastal Viet Nam, local precipitation isotope ratios and the resulting simulated δ 18O tree-ring chronologies reflect upstream rainfall amounts and atmospheric circulation associated with monsoon strength and wind anomalies.
Samadi Ghadim, A.; Lampens, P.; Jassur, M.
2018-03-01
The A-F-type stars and pulsators (δ Scuti-γ Dor) are in a critical regime where they experience a transition from radiative to convective transport of energy in their envelopes. Such stars can pulsate in both gravity and acoustic modes. Hence, the knowledge of their fundamental parameters along with their observed pulsation characteristics can help in improving the stellar models. When residing in a binary system, these pulsators provide more accurate and less model-dependent stellar parameters than in the case of their single counterparts. We present a light-curve model for the eclipsing system KIC 6048106 based on the Kepler photometry and the code PHOEBE. We aim to obtain accurate physical parameters and tough constraints for the stellar modelling of this intermediate-mass hybrid pulsator. We performed a separate modelling of three light-curve segments which show a distinct behaviour due to a difference in activity. We also analysed the Kepler Eclipse Time Variations (ETVs). KIC 6048106 is an Algol-type binary with F5-K5 components, a near-circular orbit and a 1.56-d period undergoing variations of the order of Δ P/P˜eq 3.60× 10^{-7} in 287 ± 7 d. The primary component is a main-sequence star with M1 = 1.55 ± 0.11 M⊙, R1 = 1.57 ± 0.12 R⊙. The secondary is a much cooler subgiant with M2 = 0.33 ± 0.07 M⊙, R2 = 1.77 ± 0.16 R⊙. Many small near-polar spots are active on its surface. The second quadrature phase shows a brightness modulation on a time-scale 290 ± 7 d, in good agreement with the ETV modulation. This study reveals a stable binary configuration along with clear evidence of a long-term activity of the secondary star.
International Nuclear Information System (INIS)
Larsson-Leander, G.
1979-01-01
Studies of close binary stars are being persued more vigorously than ever, with about 3000 research papers and notes pertaining to the field being published during the triennium 1976-1978. Many major advances and spectacular discoveries were made, mostly due to increased observational efficiency and precision, especially in the X-ray, radio, and ultraviolet domains. Progress reports are presented in the following areas: observational techniques, methods of analyzing light curves, observational data, physical data, structure and models of close binaries, statistical investigations, and origin and evolution of close binaries. Reports from the Coordinates Programs Committee, the Committee for Extra-Terrestrial Observations and the Working Group on RS CVn binaries are included. (Auth./C.F.)
Directory of Open Access Journals (Sweden)
Freddy Mora
2008-10-01
Full Text Available This study aimed at applying the generalized linear models (GLM for the analysis of a germination experiment of Cattleya bicolor in which the response variable was binary. The purpose of this experiment was to assess the effects of the storage temperatures and culture mediums on the seed viability. The analyses of variance was also carried out either with or without the data transformation. All the statistical approaches indicated the importance of the storage temperature on the seed viability. But, the culture media and interaction effects were significant only by the GLM. Based on the GLM, the seeds stored at 10°C increased viability, in which the coconut medium achieved the best performance. The results emphasized the importance of adopting the GLM to improve the reliability in many situations where the response variable followed a non-normal distribution.A técnica de propagação in vitro é considerada efetiva para fins comerciais e de conservação de orquídeas. A metodologia de modelos lineares generalizados (MLG foi usada para analisar um experimento de germinação de Cattleya bicolor. O propósito do experimento foi avaliar os efeitos da temperatura de armazenamento e dos meios de cultivo sobre a germinação, cuja resposta foi considerada binária. Análise convencional com ou sem transformação de dados foram também realizados. Todas as abordagens estatísticas indicaram a importância da temperatura sobre a viabilidade das sementes. Entretanto, os efeitos de meios de cultivo e interação foram significativos apenas para MLG. As sementes armazenadas a 10°C incrementaram sua viabilidade, onde o meio a base de coco atingiu o melhor desempenho. Os resultados enfatizam a importância de adotar MLG, para melhorar a confiabilidade em situações onde a variável resposta segue uma distribuição distinta à normal.
Modeling the temporal dynamics of nonstructural carbohydrate pools in forest trees
Energy Technology Data Exchange (ETDEWEB)
Richardson, Andrew [Northern Arizona Univ., Flagstaff, AZ (United States); Harvard Univ., Cambridge, MA (United States)
2017-11-09
Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. In this project, we measured the size of carbon reserves in forest trees, and determined how quickly these reserves are used and replaced—i.e., their “turnover time”. Our work was conducted at Harvard Forest, a temperate deciduous forest in central Massachusetts. Through field sampling, laboratory-based chemical analyses, and allometric modeling, we scaled these measurements up to whole-tree NSC budgets. We used these data to test and improve computer simulation models of carbon flow through forest ecosystems. Our modeling focused on the mathematical representation of these stored carbon reserves, and we examined the sensitivity of model performance to different model structures. This project contributes to DOE’s goal to improve next-generation models of the earth system, and to understand the impacts of climate change on terrestrial ecosystems.
Rapid method for interconversion of binary and decimal numbers
Lim, R. S.
1970-01-01
Decoding tree consisting of 40-bit semiconductor read-only memories interconverts binary and decimal numbers 50 to 100 times faster than current methods. Decimal-to-binary conversion algorithm is based on a divided-by-2 iterative equation, binary-to-decimal conversion algorithm utilizes multiplied-by-2 iterative equation.
MB3-Miner: efficiently mining eMBedded subTREEs using Tree Model Guided candidate generation
Tan, H.; Dillon, T.; Hadzic, F.; Chang, E.; Feng, L.
2005-01-01
Tree mining has many useful applications in areas such as Bioinformatics, XML mining, Web mining, etc. In general, most of the formally represented information in these domains is a tree structured form. In this paper we focus on mining frequent embedded subtrees from databases of rooted labeled
Rahmati, Mitra; Mirás-Avalos, José M; Valsesia, Pierre; Lescourret, Françoise; Génard, Michel; Davarynejad, Gholam H; Bannayan, Mohammad; Azizi, Majid; Vercambre, Gilles
2018-01-01
Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree) was adapted for describing the water stress effects on peach ( Prunus persica L. Batsch) vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar ("Elberta") under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on its sink strength
Directory of Open Access Journals (Sweden)
Mitra Rahmati
2018-01-01
Full Text Available Climate change projections predict warmer and drier conditions. In general, moderate to severe water stress reduce plant vegetative growth and leaf photosynthesis. However, vegetative and reproductive growths show different sensitivities to water deficit. In fruit trees, water restrictions may have serious implications not only on tree growth and yield, but also on fruit quality, which might be improved. Therefore, it is of paramount importance to understand the complex interrelations among the physiological processes involved in within-tree carbon acquisition and allocation, water uptake and transpiration, organ growth, and fruit composition when affected by water stress. This can be studied using process-based models of plant functioning, which allow assessing the sensitivity of various physiological processes to water deficit and their relative impact on vegetative growth and fruit quality. In the current study, an existing fruit-tree model (QualiTree was adapted for describing the water stress effects on peach (Prunus persica L. Batsch vegetative growth, fruit size and composition. First, an energy balance calculation at the fruit-bearing shoot level and a water transfer formalization within the plant were integrated into the model. Next, a reduction function of vegetative growth according to tree water status was added to QualiTree. Then, the model was parameterized and calibrated for a late-maturing peach cultivar (“Elberta” under semi-arid conditions, and for three different irrigation practices. Simulated vegetative and fruit growth variability over time was consistent with observed data. Sugar concentrations in fruit flesh were well simulated. Finally, QualiTree allowed for determining the relative importance of photosynthesis and vegetative growth reduction on carbon acquisition, plant growth and fruit quality under water constrains. According to simulations, water deficit impacted vegetative growth first through a direct effect on
International Nuclear Information System (INIS)
Cokelaer, T
2007-01-01
Matched filtering is used to search for gravitational waves emitted by inspiralling compact binaries in data from ground-based interferometers. One of the key aspects of the detection process is the deployment of a set of templates, also called a template bank, to cover the astrophysically interesting region of the parameter space. In a companion paper, we described the template bank algorithm used in the analysis of Laser Interferometer Gravitational-Wave Observatory (LIGO) data to search for signals from non-spinning binaries made of neutron star and/or stellar-mass black holes; this template bank is based upon physical template families. In this paper, we describe the phenomenological template bank that was used to search for gravitational waves from non-spinning black hole binaries (from stellar mass formation) in the second, third and fourth LIGO science runs. We briefly explain the design of the bank, whose templates are based on a phenomenological detection template family. We show that this template bank gives matches greater than 95% with the physical template families that are expected to be captured by the phenomenological templates
Allometric models for aboveground biomass of ten tree species in northeast China
Directory of Open Access Journals (Sweden)
Shuo Cai
2013-07-01
Full Text Available China contains 119 million hectares of natural forest, much of which is secondary forest. An accurate estimation of the biomass of these forests is imperative because many studies conducted in northeast China have only used primary forest and this may have resulted in biased estimates. This study analyzed secondary forest in the area using information from a forest inventory to develop allometric models of the aboveground biomass (AGB. The parameter values of the diameter at breast height (DBH, tree height (H, and crown length (CL were derived from a forest inventory of 2,733 trees in a 3.5 ha plot. The wood-specific gravity (WSG was determined for 109 trees belonging to ten species. A partial sampling method was also used to determine the biomass of branches (including stem, bark and foliage in 120 trees, which substantially easy the field works. The mean AGB was 110,729 kg ha1. We developed four allometric models from the investigation and evaluated the utility of other 19 published ones for AGB in the ten tree species. Incorporation of full range of variables with WSG-DBH-H-CL, significantly improved the precision of the models. Some of models were chosen that best fitted each tree species with high precision (R2 = 0.939, SEE 0.167. At the latitude level, the estimated AGBof secondary forest was lower than that in mature primary forests, but higher than that in primary broadleaf forest and the average level in other types of forest likewise.
Hydrodynamics of isohydric and anisohydric trees: insights from models and measurements
Novick, K. A.; Oishi, A. C.; Roman, D. T.; Benson, M. C.; Miniat, C.
2016-12-01
In an effort to understand and predict the mechanisms that govern tree response to hydrologic stress, plant hydraulic theory, which classifies trees along a continuum of isohydric to anisohydric water use strategies, is increasingly being used. Isohydry maintains relatively constant leaf water potential during periods of water stress, promoting wide hydraulic safety margins that reduce the risk of xylem cavitation. In contrast, anisohydry allows leaf water potential to fall as soil water potential falls, but in doing so trees incur a greater risk of hydraulic failure. As a result, unique patterns of stomatal functioning between isohydric and anisohydric species are both predicted and observed in leaf-, tree-, and stand-level water use. We use a novel model formulation to examine the dynamics of three mechanisms that are potentially limiting to leaf-level gas exchange in trees during drought: (1) a `demand limitation' driven by an assumption of stomatal optimization of water loss and carbon uptake; (2) `hydraulic limitation' of water movement from the roots to the leaves; and (3) `non-stomatal' limitations imposed by declining leaf water status within the leaf. Model results suggest that species-specific `economics' of stomatal behavior may play an important role in differentiating species along the continuum of isohydric to anisohydric behavior; specifically, we show that non-stomatal and demand limitations may reduce stomatal conductance and increase leaf water potential, promoting wide safety margins characteristic of isohydric species. Direct comparisons of modeled and measured stomatal conductance further indicated that non-stomatal and demand limitations reproduced observed patterns of tree water use well for an isohydric species but that a hydraulic limitation likely applies in the case of an anisohydric species. This modeling framework used in concert with climate data may help land managers and scientists predict when and what forest species and communities
Development of a dynamic model for the lung lobes and airway tree in the NCAT phantom
Garrity, J. M.; Segars, W. P.; Knisley, S. B.; Tsui, B. M. W.
2003-06-01
The four-dimensional (4-D) NCAT phantom was developed to realistically model human anatomy based on the visible human data and cardiac and respiratory motions based on 4-D tagged magnetic resonance imaging and respiratory-gated CT data from normal human subjects. Currently, the 4-D NCAT phantom does not include the airway tree or its motion within the lungs. Also, each lung is defined with a single surface; the individual lobes are not distinguished. The authors further the development of the phantom by creating dynamic models for the individual lung lobes and for the airway tree in each lobe. NURBS surfaces for the lobes and an initial airway tree model (/spl sim/ 4 generations) were created through manual segmentation of the visible human data. A mathematical algorithm with physiological constraints was used to extend the original airway model to fill each lobe. For each parent airway branch inside a lobe, the algorithm extends the airway tree by creating two daughter branches modeled with cylindrical tubes. Parameters for the cylindrical tubes such as diameter, length, and angle are constrained based on flow parameters and available lung space.
Martin-StPaul, N. K.; Ay, J. S.; Guillemot, J.; Doyen, L.; Leadley, P.
2014-12-01
Species distribution models (SDMs) are widely used to study and predict the outcome of global changes on species. In human dominated ecosystems the presence of a given species is the result of both its ecological suitability and human footprint on nature such as land use choices. Land use choices may thus be responsible for a selection bias in the presence/absence data used in SDM calibration. We present a structural modelling approach (i.e. based on structural equation modelling) that accounts for this selection bias. The new structural species distribution model (SSDM) estimates simultaneously land use choices and species responses to bioclimatic variables. A land use equation based on an econometric model of landowner choices was joined to an equation of species response to bioclimatic variables. SSDM allows the residuals of both equations to be dependent, taking into account the possibility of shared omitted variables and measurement errors. We provide a general description of the statistical theory and a set of applications on forest trees over France using databases of climate and forest inventory at different spatial resolution (from 2km to 8km). We also compared the outputs of the SSDM with outputs of a classical SDM (i.e. Biomod ensemble modelling) in terms of bioclimatic response curves and potential distributions under current climate and climate change scenarios. The shapes of the bioclimatic response curves and the modelled species distribution maps differed markedly between SSDM and classical SDMs, with contrasted patterns according to species and spatial resolutions. The magnitude and directions of these differences were dependent on the correlations between the errors from both equations and were highest for higher spatial resolutions. A first conclusion is that the use of classical SDMs can potentially lead to strong miss-estimation of the actual and future probability of presence modelled. Beyond this selection bias, the SSDM we propose represents
Belmiloudi , Aziz; Rasheed , Amer
2015-01-01
In this paper we propose a numerical scheme and perform its numerical analysis devoted to an anisotropic phase-field model with convection under the influence of magnetic field for the isother-mal solidification of binary mixtures in two-dimensional geometry. Precisely, the numerical stability and error analysis of this approximation scheme which is based on mixed finite-element method are performed. The particular application of a nickelcopper (NiCu) binary alloy, with real physical paramete...
Yield curve event tree construction for multi stage stochastic programming models
DEFF Research Database (Denmark)
Rasmussen, Kourosh Marjani; Poulsen, Rolf
Dynamic stochastic programming (DSP) provides an intuitive framework for modelling of financial portfolio choice problems where market frictions are present and dynamic re--balancing has a significant effect on initial decisions. The application of these models in practice, however, is limited by...... of yield curves. Such trees may then be used to represent the underlying uncertainty in DSP models of fixed income risk and portfolio management....
Remote Sensing Protocols for Parameterizing an Individual, Tree-Based, Forest Growth and Yield Model
2014-09-01
Penelope Morgan. 2006. “Regression Modeling and Mapping of Coniferous Forest Basal Area and Tree Density from Discrete- Return LIDAR and... Basal Area Relationships of Open-Grown Southern Pines for Modeling Competition and Growth.” Canadian Journal of of Forest Research 22: 341–347... Forest Growth and Yield Model Co ns tr uc tio n En gi ne er in g R es ea rc h La bo ra to ry Scott A. Tweddale, Patrick J. Guertin, and
Assessing the Cooling Benefits of Tree Shade by an Outdoor Urban Physical Scale Model at Tempe, AZ
Directory of Open Access Journals (Sweden)
Qunshan Zhao
2018-01-01
Full Text Available Urban green infrastructure, especially shade trees, offers benefits to the urban residential environment by mitigating direct incoming solar radiation on building facades, particularly in hot settings. Understanding the impact of different tree locations and arrangements around residential properties has the potential to maximize cooling and can ultimately guide urban planners, designers, and homeowners on how to create the most sustainable urban environment. This research measures the cooling effect of tree shade on building facades through an outdoor urban physical scale model. The physical scale model is a simulated neighborhood consisting of an array of concrete cubes to represent houses with identical artificial trees. We tested and compared 10 different tree densities, locations, and arrangement scenarios in the physical scale model. The experimental results show that a single tree located at the southeast of the building can provide up to 2.3 °C hourly cooling benefits to east facade of the building. A two-tree cluster arrangement provides more cooling benefits (up to 6.6 °C hourly cooling benefits to the central facade when trees are located near the south and southeast sides of the building. The research results confirm the cooling benefits of tree shade and the importance of wisely designing tree locations and arrangements in the built environment.
Jovanovic, Milos; Radovanovic, Sandro; Vukicevic, Milan; Van Poucke, Sven; Delibasic, Boris
2016-09-01
Quantification and early identification of unplanned readmission risk have the potential to improve the quality of care during hospitalization and after discharge. However, high dimensionality, sparsity, and class imbalance of electronic health data and the complexity of risk quantification, challenge the development of accurate predictive models. Predictive models require a certain level of interpretability in order to be applicable in real settings and create actionable insights. This paper aims to develop accurate and interpretable predictive models for readmission in a general pediatric patient population, by integrating a data-driven model (sparse logistic regression) and domain knowledge based on the international classification of diseases 9th-revision clinical modification (ICD-9-CM) hierarchy of diseases. Additionally, we propose a way to quantify the interpretability of a model and inspect the stability of alternative solutions. The analysis was conducted on >66,000 pediatric hospital discharge records from California, State Inpatient Databases, Healthcare Cost and Utilization Project between 2009 and 2011. We incorporated domain knowledge based on the ICD-9-CM hierarchy in a data driven, Tree-Lasso regularized logistic regression model, providing the framework for model interpretation. This approach was compared with traditional Lasso logistic regression resulting in models that are easier to interpret by fewer high-level diagnoses, with comparable prediction accuracy. The results revealed that the use of a Tree-Lasso model was as competitive in terms of accuracy (measured by area under the receiver operating characteristic curve-AUC) as the traditional Lasso logistic regression, but integration with the ICD-9-CM hierarchy of diseases provided more interpretable models in terms of high-level diagnoses. Additionally, interpretations of models are in accordance with existing medical understanding of pediatric readmission. Best performing models have
Modeling transcriptional networks regulating secondary growth and wood formation in forest trees
Lijun Liu; Vladimir Filkov; Andrew Groover
2013-01-01
The complex interactions among the genes that underlie a biological process can be modeled and presented as a transcriptional network, in which genes (nodes) and their interactions (edges) are shown in a graphical form similar to a wiring diagram. A large number of genes have been identified that are expressed during the radial woody growth of tree stems (secondary...
The Statistical Analysis of General Processing Tree Models with the EM Algorithm.
Hu, Xiangen; Batchelder, William H.
1994-01-01
The statistical analysis of processing tree models is advanced by showing how the parameters of estimation and hypothesis testing, based on the likelihood functions, can be accomplished by adapting the expectation-maximization (EM) algorithm. The adaptation makes it easy to program a personal computer to accomplish the stages of statistical…
International Nuclear Information System (INIS)
Koh, Kwang Yong; Seong, Poong Hyun
2010-01-01
Fault tree analysis (FTA) has suffered from several drawbacks such that it uses only static gates and hence can not capture dynamic behaviors of the complex system precisely, and it is in lack of rigorous semantics, and reasoning process which is to check whether basic events really cause top events is done manually and hence very labor-intensive and time-consuming for the complex systems while it has been one of the most widely used safety analysis technique in nuclear industry. Although several attempts have been made to overcome this problem, they can not still do absolute or actual time modeling because they adapt relative time concept and can capture only sequential behaviors of the system. In this work, to resolve the problems, FTA and model checking are integrated to provide formal, automated and qualitative assistance to informal and/or quantitative safety analysis. Our approach proposes to build a formal model of the system together with fault trees. We introduce several temporal gates based on timed computational tree logic (TCTL) to capture absolute time behaviors of the system and to give concrete semantics to fault tree gates to reduce errors during the analysis, and use model checking technique to automate the reasoning process of FTA
Theory and Programs for Dynamic Modeling of Tree Rings from Climate
Paul C. van Deusen; Jennifer Koretz
1988-01-01
Computer programs written in GAUSS(TM) for IBM compatible personal computers are described that perform dynamic tree ring modeling with climate data; the underlying theory is also described. The programs and a separate users manual are available from the authors, although users must have the GAUSS software package on their personal computer. An example application of...
Modeling potential climate change impacts on the trees of the northeastern United States
Louis Iverson; Anantha Prasad; Stephen Matthews
2008-01-01
We evaluated 134 tree species from the eastern United States for potential response to several scenarios of climate change, and summarized those responses for nine northeastern United States. We modeled and mapped each species individually and show current and potential future distributions for two emission scenarios (A1fi [higher emission] and B1 [lower emission]) and...
A tree-based method to price American options in the Heston model
Vellekoop, M.; Nieuwenhuis, H.
2009-01-01
We develop an algorithm to price American options on assets that follow the stochastic volatility model defined by Heston. We use an approach which is based on a modification of a combined tree for stock prices and volatilities, where the number of nodes grows quadratically in the number of time
A quasi-steady state shrinking core model of "whole tree" combustion
African Journals Online (AJOL)
Remember me, or Register. DOWNLOAD FULL TEXT Open Access DOWNLOAD FULL TEXT Subscription or Fee Access. A quasi-steady state shrinking core model of "whole tree" combustion. A. Ouédraogo, JC Mulligan, JG Cleland. Abstract. (J. de la Recherche Scientifique de l'Université de Lomé, 2000, 4(2): 199-208) ...
Generic linear mixed-effects individual-tree biomass models for ...
African Journals Online (AJOL)
Quantification of forest biomass is important for practical forestry and for scientific purposes. It is fundamental to develop generic individual-tree biomass models suitable for large-scale forest biomass estimation. However, compatibility of forest biomass estimates at different scales may become a problem. We developed ...
Fader, Marianela; von Bloh, Werner; Shi, Sinan; Bondeau, Alberte; Cramer, Wolfgang
2016-04-01
In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall and direct degradation of ecosystems. Human population growth and socioeconomic changes, notably on the Eastern and Southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive ecohydrological model. Here we present here the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL, "Lund-Potsdam-Jena managed Land"): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was then successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. A first application of the model indicates that, currently, agricultural trees consume in average more irrigation water per hectare than annual crops. Also, different crops show different magnitude of changes in net irrigation requirements due to climate change, being the increases most pronounced in agricultural trees. This is very relevant since the Mediterranean area as a whole might face an increase in gross irrigation requirements between 4% and 74% from climate change and population growth if irrigation systems and conveyance are not improved. Additionally, future water scarcity might pose further challenges to the agricultural sector: Algeria, Libya, Israel, Jordan, Lebanon, Syria, Serbia, Morocco, Tunisia and Spain have a high risk of not being able to sustainably meet future irrigation water requirements in some scenarios by the end of the century (1). The importance of including agricultural trees in the ecohydrological models is also shown in the results concerning soil organic carbon (SOC). Since in former model
Decision tree based knowledge acquisition and failure diagnosis using a PWR loop vibration model
International Nuclear Information System (INIS)
Bauernfeind, V.; Ding, Y.
1993-01-01
An analytical vibration model of the primary system of a 1300 MW PWR was used for simulating mechanical faults. Deviations in the calculated power density spectra and coherence functions are determined and classified. The decision tree technique is then used for a personal computer supported knowledge presentation and for optimizing the logical relationships between the simulated faults and the observed symptoms. The optimized decision tree forms the knowledge base and can be used to diagnose known cases as well as to include new data into the knowledge base if new faults occur. (author)
A model for the inverse 1-median problem on trees under uncertain costs
Directory of Open Access Journals (Sweden)
Kien Trung Nguyen
2016-01-01
Full Text Available We consider the problem of justifying vertex weights of a tree under uncertain costs so that a prespecified vertex become optimal and the total cost should be optimal in the uncertainty scenario. We propose a model which delivers the information about the optimal cost which respect to each confidence level \\(\\alpha \\in [0,1]\\. To obtain this goal, we first define an uncertain variable with respect to the minimum cost in each confidence level. If all costs are independently linear distributed, we present the inverse distribution function of this uncertain variable in \\(O(n^{2}\\log n\\ time, where \\(n\\ is the number of vertices in the tree.
Modeling time-to-event (survival) data using classification tree analysis.
Linden, Ariel; Yarnold, Paul R
2017-12-01
Time to the occurrence of an event is often studied in health research. Survival analysis differs from other designs in that follow-up times for individuals who do not experience the event by the end of the study (called censored) are accounted for in the analysis. Cox regression is the standard method for analysing censored data, but the assumptions required of these models are easily violated. In this paper, we introduce classification tree analysis (CTA) as a flexible alternative for modelling censored data. Classification tree analysis is a "decision-tree"-like classification model that provides parsimonious, transparent (ie, easy to visually display and interpret) decision rules that maximize predictive accuracy, derives exact P values via permutation tests, and evaluates model cross-generalizability. Using empirical data, we identify all statistically valid, reproducible, longitudinally consistent, and cross-generalizable CTA survival models and then compare their predictive accuracy to estimates derived via Cox regression and an unadjusted naïve model. Model performance is assessed using integrated Brier scores and a comparison between estimated survival curves. The Cox regression model best predicts average incidence of the outcome over time, whereas CTA survival models best predict either relatively high, or low, incidence of the outcome over time. Classification tree analysis survival models offer many advantages over Cox regression, such as explicit maximization of predictive accuracy, parsimony, statistical robustness, and transparency. Therefore, researchers interested in accurate prognoses and clear decision rules should consider developing models using the CTA-survival framework. © 2017 John Wiley & Sons, Ltd.
Singh, Gyanendra; Sachdeva, S N; Pal, Mahesh
2016-11-01
This work examines the application of M5 model tree and conventionally used fixed/random effect negative binomial (FENB/RENB) regression models for accident prediction on non-urban sections of highway in Haryana (India). Road accident data for a period of 2-6 years on different sections of 8 National and State Highways in Haryana was collected from police records. Data related to road geometry, traffic and road environment related variables was collected through field studies. Total two hundred and twenty two data points were gathered by dividing highways into sections with certain uniform geometric characteristics. For prediction of accident frequencies using fifteen input parameters, two modeling approaches: FENB/RENB regression and M5 model tree were used. Results suggest that both models perform comparably well in terms of correlation coefficient and root mean square error values. M5 model tree provides simple linear equations that are easy to interpret and provide better insight, indicating that this approach can effectively be used as an alternative to RENB approach if the sole purpose is to predict motor vehicle crashes. Sensitivity analysis using M5 model tree also suggests that its results reflect the physical conditions. Both models clearly indicate that to improve safety on Indian highways minor accesses to the highways need to be properly designed and controlled, the service roads to be made functional and dispersion of speeds is to be brought down. Copyright © 2016 Elsevier Ltd. All rights reserved.
A Knowledge Tree Model and Its Application for Continuous Management Improvement
Lu, Yun; Bao, Zhen-Qiang; Zhao, Yu-Qin; Wang, Yan; Wang, Gui-Jun
This chapter analyzes the relationship of organizational knowledge and brings forward that organizational knowledge consists of three layers: core knowledge, structural knowledge, and implicit knowledge. According to the principle of knowledge maps, a dynamic management model of organizational knowledge based on knowledge tree is introduced and the definition of the value of knowledge node is given so that the quantitative management on knowledge is realized, which lays a foundation for performance evaluation of knowledge management. We also carefully study the application of knowledge tree in service quality management of hospital organizations and management innovation process and give the example of cooperation in endoscopic surgery to establish a knowledge tree about operational cooperation degree, which states the principle of organizational knowledge management and the knowledge innovation process of continuous management improvement.
Chakra B. Budhathoki; Thomas B. Lynch; James M. Guldin
2010-01-01
Nonlinear mixed-modeling methods were used to estimate parameters in an individual-tree basal area growth model for shortleaf pine (Pinus echinata Mill.). Shortleaf pine individual-tree growth data were available from over 200 permanently established 0.2-acre fixed-radius plots located in naturally-occurring even-aged shortleaf pine forests on the...
David W. MacFarlane
2015-01-01
Accurately assessing forest biomass potential is contingent upon having accurate tree biomass models to translate data from forest inventories. Building generality into these models is especially important when they are to be applied over large spatial domains, such as regional, national and international scales. Here, new, generalized whole-tree mass / volume...
Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen. Fitzgerald
2012-01-01
Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...
Jeurissen, S.M.F.; Seyhan, F.; Kandhai, M.C.; Dekkers, S.; Booij, C.J.H.; Bos, P.M.J.; Fels, van der H.J.
2011-01-01
This paper proposes an indicator based 'traffic light' model as a tool to pro-actively assess the occurrence of mycotoxins in tree nuts. The model is built using a holistic approach and, consequently, uses indicators from inside and outside the tree nut production chain as the basic elements.
Liu, Xuefeng; Daniels, Michael J; Marcus, Bess
2009-06-01
Joint models for the association of a longitudinal binary and a longitudinal continuous process are proposed for situations in which their association is of direct interest. The models are parameterized such that the dependence between the two processes is characterized by unconstrained regression coefficients. Bayesian variable selection techniques are used to parsimoniously model these coefficients. A Markov chain Monte Carlo (MCMC) sampling algorithm is developed for sampling from the posterior distribution, using data augmentation steps to handle missing data. Several technical issues are addressed to implement the MCMC algorithm efficiently. The models are motivated by, and are used for, the analysis of a smoking cessation clinical trial in which an important question of interest was the effect of the (exercise) treatment on the relationship between smoking cessation and weight gain.
Comparison of tree types of models for the prediction of final academic achievement
Directory of Open Access Journals (Sweden)
Silvana Gasar
2002-12-01
Full Text Available For efficient prevention of inappropriate secondary school choices and by that academic failure, school counselors need a tool for the prediction of individual pupil's final academic achievements. Using data mining techniques on pupils' data base and expert modeling, we developed several models for the prediction of final academic achievement in an individual high school educational program. For data mining, we used statistical analyses, clustering and two machine learning methods: developing classification decision trees and hierarchical decision models. Using an expert system shell DEX, an expert system, based on a hierarchical multi-attribute decision model, was developed manually. All the models were validated and evaluated from the viewpoint of their applicability. The predictive accuracy of DEX models and decision trees was equal and very satisfying, as it reached the predictive accuracy of an experienced counselor. With respect on the efficiency and difficulties in developing models, and relatively rapid changing of our education system, we propose that decision trees are used in further development of predictive models.
Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates
Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje
2017-04-01
Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak
Flow regulation in coronary vascular tree: a model study.
Directory of Open Access Journals (Sweden)
Xinzhou Xie
Full Text Available Coronary blood flow can always be matched to the metabolic demand of the myocardium due to the regulation of vasoactive segments. Myocardial compressive forces play an important role in determining coronary blood flow but its impact on flow regulation is still unknown. The purpose of this study was to develop a coronary specified flow regulation model, which can integrate myocardial compressive forces and other identified regulation factors, to further investigate the coronary blood flow regulation behavior.A theoretical coronary flow regulation model including the myogenic, shear-dependent and metabolic responses was developed. Myocardial compressive forces were included in the modified wall tension model. Shear-dependent response was estimated by using the experimental data from coronary circulation. Capillary density and basal oxygen consumption were specified to corresponding to those in coronary circulation. Zero flow pressure was also modeled by using a simplified capillary model.Pressure-flow relations predicted by the proposed model are consistent with previous experimental data. The predicted diameter changes in small arteries are in good agreement with experiment observations in adenosine infusion and inhibition of NO synthesis conditions. Results demonstrate that the myocardial compressive forces acting on the vessel wall would extend the auto-regulatory range by decreasing the myogenic tone at the given perfusion pressure.Myocardial compressive forces had great impact on coronary auto-regulation effect. The proposed model was proved to be consistent with experiment observations and can be employed to investigate the coronary blood flow regulation effect in physiological and pathophysiological conditions.
A Test of Carbon and Oxygen Stable Isotope Ratio Process Models in Tree Rings.
Roden, J. S.; Farquhar, G. D.
2008-12-01
Stable isotopes ratios of carbon and oxygen in tree ring cellulose have been used to infer environmental change. Process-based models have been developed to clarify the potential of historic tree ring records for meaningful paleoclimatic reconstructions. However, isotopic variation can be influenced by multiple environmental factors making simplistic interpretations problematic. Recently, the dual isotope approach, where the variation in one stable isotope ratio (e.g. oxygen) is used to constrain the interpretation of variation in another (e.g. carbon), has been shown to have the potential to de-convolute isotopic analysis. However, this approach requires further testing to determine its applicability for paleo-reconstructions using tree-ring time series. We present a study where the information needed to parameterize mechanistic models for both carbon and oxygen stable isotope ratios were collected in controlled environment chambers for two species (Pinus radiata and Eucalyptus globulus). The seedlings were exposed to treatments designed to modify leaf temperature, transpiration rates, stomatal conductance and photosynthetic capacity. Both species were grown for over 100 days under two humidity regimes that differed by 20%. Stomatal conductance was significantly different between species and for seedlings under drought conditions but not between other treatments or humidity regimes. The treatments produced large differences in transpiration rate and photosynthesis. Treatments that effected photosynthetic rates but not stomatal conductance influenced carbon isotope discrimination more than those that influenced primarily conductance. The various treatments produced a range in oxygen isotope ratios of 7 ‰. Process models predicted greater oxygen isotope enrichment in tree ring cellulose than observed. The oxygen isotope ratios of bulk leaf water were reasonably well predicted by current steady-state models. However, the fractional difference between models that
Widlowski, J.; Cote, J.; Beland, M.
2013-12-01
Current operational retrieval algorithms of terrestrial essential climate variables, like LAI and FAPAR, rely on simulations from physically based radiative transfer models that possess inherent assumptions regarding the structure of the vegetation. This work investigates the biases that can be expected when validated Monte Carlo ray-tracing models are used to simulated bi-directional reflectance properties of Savanna environments using different levels of architectural realism. More specifically, tree crowns will be gradually abstracted with voxels that increase in size from 0.1m to 0.9m sidelength. This will reduce the spatial variability of the foliage density in the tree crown, alter the outer silhouette of the tree, and change its directional cross-sectional area. To assess the impact of such structural changes on the radiative properties of Savanna environments, very detailed 3-D tree reconstructions are made use of that were originally derived from terrestrial LIDAR scans acquired in Mali. Canopy reflectance simulations of these reference targets are then compared with the same data from the voxelised canopy representations (with and without woody structures) at multiple spatial resolutions, spectral domains, as well as illumination and viewing configurations. The goal of this study is to find the least detailed tree architecture representations that are still suitable for the interpretation of space borne data. Graphical depiction of the Savanna trees (top left) that served as architectural reference for canopy reflectance simulations that were then compared to the same quantities for crown abstractions based on different voxel sizes (middle and right panels) as well as ellipsoids (bottom left).
Hill, Ryan M; Oosterhoff, Benjamin; Kaplow, Julie B
2017-07-01
Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. Participants were N = 4,799 youth (Mage = 16.15 years, SD = 1.63) who completed both Waves 1 and 2 of the National Longitudinal Study of Adolescent to Adult Health. CTA was used to generate a series of decision rules for identifying adolescents at risk for reporting suicide ideation at Wave 2. Findings revealed 3 distinct solutions with varying sensitivity and specificity for identifying adolescents who reported suicide ideation. Sensitivity of the classification trees ranged from 44.6% to 77.6%. The tree with greatest specificity and lowest sensitivity was based on a history of suicide ideation. The tree with moderate sensitivity and high specificity was based on depressive symptoms, suicide attempts or suicide among family and friends, and social support. The most sensitive but least specific tree utilized these factors and gender, ethnicity, hours of sleep, school-related factors, and future orientation. These classification trees offer community organizations options for instituting large-scale screenings for suicide ideation risk depending on the available resources and modality of services to be provided. This study provides a theoretically and empirically driven model for prospectively identifying adolescents at risk for suicide ideation and has implications for preventive interventions among at-risk youth. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
A Root water uptake model to compensate disease stress in citrus trees
Peddinti, S. R.; Kambhammettu, B. P.; Lad, R. S.; Suradhaniwar, S.
2017-12-01
Plant root water uptake (RWU) controls a number of hydrologic fluxes in simulating unsaturated flow and transport processes. Variable saturated models that simulate soil-water-plant interactions within the rizhosphere do not account for the health of the tree. This makes them difficult to analyse RWU patterns for diseased trees. Improper irrigation management activities on diseased (Phytopthora spp. affected) citrus trees of central India has resulted in a significant reduction in crop yield accompanied by disease escalation. This research aims at developing a quantitative RWU model that accounts for the reduction in water stress as a function of plant disease level (hereafter called as disease stress). A total of four research plots with varying disease severity were considered for our field experimentation. A three-dimensional electrical resistivity tomography (ERT) was performed to understand spatio-temporal distribution in soil moisture following irrigation. Evaporation and transpiration were monitored daily using micro lysimeter and sap flow meters respectively. Disease intensity was quantified (on 0 to 9 scale) using pathological analysis on soil samples. Pedo-physocal and pedo-electric relations were established under controlled laboratory conditions. A non-linear disease stress response function for citrus trees was derived considering phonological, hydrological, and pathological parameters. Results of numerical simulations conclude that the propagation of error in RWU estimates by ignoring the health condition of the tree is significant. The developed disease stress function was then validated in the presence of deficit water and nutrient stress conditions. Results of numerical analysis showed a good agreement with experimental data, corroborating the need for alternate management practices for disease citrus trees.
Infante, J M; Mauchamp, A; Fernández-Alé, R; Joffre, R; Rambal, S
2001-04-01
Within-tree variation in sap flow density (SFD) was measured in two isolated evergreen oak (Quercus ilex L.) trees growing in an oak savannah (dehesa) in southwest Spain. Sap flow was estimated by the constant heating method. Three sensors were installed in the trunk of each tree in three orientations: northeast (NE), northwest (NW) and south (S). Sap flow density was monitored continuously from May 18 to September 27, 1993. Daily values of SFD ranged between 500 and 4500 mm3 mm-2 day-1. There were significant differences in SFD between orientations; SFD was higher in the NE and NW orientations than in the S orientation. These differences were noted on both a daily and seasonal time scale, and were less pronounced on cloudy days and at the end of the drought period, when SFD was relatively low. Our results support the idea that branches of trees can be viewed as a collection of small independent plants.
Simulating local adaptation to climate of forest trees with a Physio-Demo-Genetics model.
Oddou-Muratorio, Sylvie; Davi, Hendrik
2014-04-01
One challenge of evolutionary ecology is to predict the rate and mechanisms of population adaptation to environmental variations. The variations in most life history traits are shaped both by individual genotypic and by environmental variation. Forest trees exhibit high levels of genetic diversity, large population sizes, and gene flow, and they also show a high level of plasticity for life history traits. We developed a new Physio-Demo-Genetics model (denoted PDG) coupling (i) a physiological module simulating individual tree responses to the environment; (ii) a demographic module simulating tree survival, reproduction, and pollen and seed dispersal; and (iii) a quantitative genetics module controlling the heritability of key life history traits. We used this model to investigate the plastic and genetic components of the variations in the timing of budburst (TBB) along an elevational gradient of Fagus sylvatica (the European beech). We used a repeated 5 years climatic sequence to show that five generations of natural selection were sufficient to develop nonmonotonic genetic differentiation in the TBB along the local climatic gradient but also that plastic variation among different elevations and years was higher than genetic variation. PDG complements theoretical models and provides testable predictions to understand the adaptive potential of tree populations.
Model checking software for phylogenetic trees using distribution and database methods.
Requeno, José Ignacio; Colom, José Manuel
2013-12-01
Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence) and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.
Model checking software for phylogenetic trees using distribution and database methods
Directory of Open Access Journals (Sweden)
Requeno José Ignacio
2013-12-01
Full Text Available Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.
Engineering of Algorithms for Hidden Markov models and Tree Distances
DEFF Research Database (Denmark)
Sand, Andreas
speed up all the classical algorithms for analyses and training of hidden Markov models. And I show how two particularly important algorithms, the forward algorithm and the Viterbi algorithm, can be accelerated through a reformulation of the algorithms and a somewhat more complicated parallelization....... Lastly, I show how hidden Markov models can be trained orders of magnitude faster on a given input by rethinking the forward algorithm such that it can automatically adapt itself to the input. Together, these optimization have enabled us to perform analysis of full genomes in a few minutes and thereby...
Directory of Open Access Journals (Sweden)
Hyun-Joo Oh
2017-09-01
Full Text Available The main purpose of this paper is to present some potential applications of sophisticated data mining techniques, such as artificial neural network (ANN and boosted tree (BT, for landslide susceptibility modeling in the Yongin area, Korea. Initially, landslide inventory was detected from visual interpretation using digital aerial photographic maps with a high resolution of 50 cm taken before and after the occurrence of landslides. The debris flows were randomly divided into two groups: training and validation sets with a 50:50 proportion. Additionally, 18 environmental factors related to landslide occurrence were derived from the topography, soil, and forest maps. Subsequently, the data mining techniques were applied to identify the influence of environmental factors on landslide occurrence of the training set and assess landslide susceptibility. Finally, the landslide susceptibility indexes from ANN and BT were compared with a validation set using a receiver operating characteristics curve. The slope gradient, topographic wetness index, and timber age appear to be important factors in landslide occurrence from both models. The validation result of ANN and BT showed 82.25% and 90.79%, which had reasonably good performance. The study shows the benefit of selecting optimal data mining techniques in landslide susceptibility modeling. This approach could be used as a guideline for choosing environmental factors on landslide occurrence and add influencing factors into landslide monitoring systems. Furthermore, this method can rank landslide susceptibility in urban areas, thus providing helpful information when selecting a landslide monitoring site and planning land-use.
New advances in tree shrew model in experimental studies of hepatitis B virus
Directory of Open Access Journals (Sweden)
JIN Xiong
2015-09-01
Full Text Available Hepatitis B virus (HBV infection is the main cause of liver fibrosis, cirrhosis, and hepatocellular carcinoma, and it is also a major health problem around the world. How to establish an efficient, reliable, and standardized animal model of chronic HBV infection is essential to the study of the pathogenesis and prevention strategies for HBV infection. This review summarizes the general research and new advances in using tree shrews as the model of HBV infection. We believe that tree shrews, as lower primates, will provide a vital platform and have a huge potential for building a proper animal model in the future, and could become the essential animal model for simulating the process of HBV infection in humans.
Massive Black Hole Binary Evolution
Directory of Open Access Journals (Sweden)
Merritt David
2005-11-01
Full Text Available Coalescence of binary supermassive black holes (SBHs would constitute the strongest sources of gravitational waves to be observed by LISA. While the formation of binary SBHs during galaxy mergers is almost inevitable, coalescence requires that the separation between binary components first drop by a few orders of magnitude, due presumably to interaction of the binary with stars and gas in a galactic nucleus. This article reviews the observational evidence for binary SBHs and discusses how they would evolve. No completely convincing case of a bound, binary SBH has yet been found, although a handful of systems (e.g. interacting galaxies; remnants of galaxy mergers are now believed to contain two SBHs at projected separations of <~ 1kpc. N-body studies of binary evolution in gas-free galaxies have reached large enough particle numbers to reproduce the slow, “diffusive” refilling of the binary’s loss cone that is believed to characterize binary evolution in real galactic nuclei. While some of the results of these simulations - e.g. the binary hardening rate and eccentricity evolution - are strongly N-dependent, others - e.g. the “damage” inflicted by the binary on the nucleus - are not. Luminous early-type galaxies often exhibit depleted cores with masses of ~ 1-2 times the mass of their nuclear SBHs, consistent with the predictions of the binary model. Studies of the interaction of massive binaries with gas are still in their infancy, although much progress is expected in the near future. Binary coalescence has a large influence on the spins of SBHs, even for mass ratios as extreme as 10:1, and evidence of spin-flips may have been observed.
Comparison of data mining and allometric model in estimation of tree biomass.
Sanquetta, Carlos R; Wojciechowski, Jaime; Dalla Corte, Ana P; Behling, Alexandre; Péllico Netto, Sylvio; Rodrigues, Aurélio L; Sanquetta, Mateus N I
2015-08-07
The traditional method used to estimate tree biomass is allometry. In this method, models are tested and equations fitted by regression usually applying ordinary least squares, though other analogous methods are also used for this purpose. Due to the nature of tree biomass data, the assumptions of regression are not always accomplished, bringing uncertainties to the inferences. This article demonstrates that the Data Mining (DM) technique can be used as an alternative to traditional regression approach to estimate tree biomass in the Atlantic Forest, providing better results than allometry, and demonstrating simplicity, versatility and flexibility to apply to a wide range of conditions. Various DM approaches were examined regarding distance, number of neighbors and weighting, by using 180 trees coming from environmental restoration plantations in the Atlantic Forest biome. The best results were attained using the Chebishev distance, 1/d weighting and 5 neighbors. Increasing number of neighbors did not improve estimates. We also analyze the effect of the size of data set and number of variables in the results. The complete data set and the maximum number of predicting variables provided the best fitting. We compare DM to Schumacher-Hall model and the results showed a gain of up to 16.5% in reduction of the standard error of estimate. It was concluded that Data Mining can provide accurate estimates of tree biomass and can be successfully used for this purpose in environmental restoration plantations in the Atlantic Forest. This technique provides lower standard error of estimate than the Schumacher-Hall model and has the advantage of not requiring some statistical assumptions as do the regression models. Flexibility, versatility and simplicity are attributes of DM that corroborates its great potential for similar applications.
Application of Decision-Tree Model to Groundwater Productivity-Potential Mapping
Directory of Open Access Journals (Sweden)
Saro Lee
2015-09-01
Full Text Available For the sustainable use of groundwater, this study analyzed groundwater productivity-potential using a decision-tree approach in a geographic information system (GIS in Boryeong and Pohang cities, Korea. The model was based on the relationship between groundwater-productivity data, including specific capacity (SPC, and its related hydrogeological factors. SPC data which is measured and calculated for groundwater productivity and data about related factors, including topography, lineament, geology, forest and soil data, were collected and input into a spatial database. A decision-tree model was applied and decision trees were constructed using the chi-squared automatic interaction detector (CHAID and the quick, unbiased, and efficient statistical tree (QUEST algorithms. The resulting groundwater-productivity-potential (GPP maps were validated using area-under-the-curve (AUC analysis with the well data that had not been used for training the model. In the Boryeong city, the CHAID and QUEST algorithms had accuracies of 83.31% and 79.47%, and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 86.18% and 80.00%. As another validation, the GPP maps were validated by comparing the actual SPC data. As the result, in the Boryeong city, the CHAID and QUEST algorithms had accuracies of 96.55% and 94.92% and in the Pohang city, the CHAID and QUEST algorithms had accuracies of 87.88% and 87.50%. These results indicate that decision-tree models can be useful for development of groundwater resources.
Enrique Orellana; Afonso Figueiredo Filho; Sylvio Péllico Netto; Jerome Klaas Vanclay
2016-01-01
Background: In recent decades, native Araucaria forests in Brazil have become fragmented due to the conversion of forest to agricultural lands and commercial tree plantations. Consequently, the forest dynamics in this forest type have been poorly investigated, as most fragments are poorly structured in terms of tree size and diversity. Methods: We developed a distance-independent individual tree-growth model to simulate the forest dynamics in a native Araucaria forest located pred...
Quantum cluster equilibrium model of N-methylformamide–water binary mixtures
Energy Technology Data Exchange (ETDEWEB)
Domaros, Michael von; Kirchner, Barbara, E-mail: kirchner@thch.uni-bonn.de [Mulliken Center for Theoretical Chemistry, Universität Bonn, Beringstr. 4, D-53115 Bonn (Germany); Jähnigen, Sascha [Martin-Luther-Universität Halle-Wittenberg, von-Danckelmann-Platz 4, D-06120 Halle (Germany); Friedrich, Joachim [Technische Universität Chemnitz, Straße der Nationen 62, D-09111 Chemnitz (Germany)
2016-02-14
The established quantum cluster equilibrium (QCE) approach is refined and applied to N-methylformamide (NMF) and its aqueous solution. The QCE method is split into two iterative cycles: one which converges to the liquid phase solution of the QCE equations and another which yields the gas phase. By comparing Gibbs energies, the thermodynamically stable phase at a given temperature and pressure is then chosen. The new methodology avoids metastable solutions and allows a different treatment of the mean-field interactions within the gas and liquid phases. These changes are of crucial importance for the treatment of binary mixtures. For the first time in a QCE study, the cis-trans-isomerism of a species (NMF) is explicitly considered. Cluster geometries and frequencies are calculated using density functional theory (DFT) and complementary coupled cluster single point energies are used to benchmark the DFT results. Independent of the selected quantum-chemical method, a large set of clusters is required for an accurate thermodynamic description of the binary mixture. The liquid phase of neat NMF is found to be dominated by the cyclic trans-NMF pentamer, which can be interpreted as a linear trimer that is stabilized by explicit solvation of two further NMF molecules. This cluster reflects the known hydrogen bond network preferences of neat NMF.
International Nuclear Information System (INIS)
Bejarano, Arturo; Gutierrez, Jorge E.; Araus, Karina A.; Fuente, Juan C. de la
2011-01-01
Research highlights: → (Vapor + liquid) equilibria of three (CO 2 + C 5 alcohol) binary systems were measured. → Complementary data are reported at (313, 323 and 333) K and from (2 to 11) MPa. → No liquid immiscibility was observed at the temperatures and pressures studied. → Experimental data were correlated with the PR-EoS and the van de Waals mixing rules. → Correlation results showed relative deviations ≤8 % (liquid) and ≤2 % (vapor). - Abstract: Complementary isothermal (vapor + liquid) equilibria data are reported for the (CO 2 + 3-methyl-2-butanol), (CO 2 + 2-pentanol), and (CO 2 + 3-pentanol) binary systems at temperatures of (313, 323, and 333) K, and at pressure range of (2 to 11) MPa. For all (CO 2 + alcohol) systems, it was visually monitored that there was no liquid immiscibility at the temperatures and pressures studied. The experimental data were correlated with the Peng-Robinson equation of state using the quadratic mixing rules of van der Waals with two adjustable parameters. The calculated (vapor + liquid) equilibria compositions were found to be in good agreement with the experimental data with deviations for the mole fractions <8% and <2% for the liquid and vapor phase, respectively.
International Nuclear Information System (INIS)
Del Pozzo, Walter; Veitch, John; Vecchio, Alberto
2011-01-01
Second-generation interferometric gravitational-wave detectors, such as Advanced LIGO and Advanced Virgo, are expected to begin operation by 2015. Such instruments plan to reach sensitivities that will offer the unique possibility to test general relativity in the dynamical, strong-field regime and investigate departures from its predictions, in particular, using the signal from coalescing binary systems. We introduce a statistical framework based on Bayesian model selection in which the Bayes factor between two competing hypotheses measures which theory is favored by the data. Probability density functions of the model parameters are then used to quantify the inference on individual parameters. We also develop a method to combine the information coming from multiple independent observations of gravitational waves, and show how much stronger inference could be. As an introduction and illustration of this framework-and a practical numerical implementation through the Monte Carlo integration technique of nested sampling-we apply it to gravitational waves from the inspiral phase of coalescing binary systems as predicted by general relativity and a very simple alternative theory in which the graviton has a nonzero mass. This method can (and should) be extended to more realistic and physically motivated theories.
Diameter-growth model across shortleaf pine range using regression tree analysis
Daniel Yaussy; Louis Iverson; Anantha Prasad
1999-01-01
Diameter growth of a tree in most gap-phase models is limited by light, nutrients, moisture, and temperature. Growing-season temperature is represented by growing degree days (gdd), which is the sum of the average daily temperatures above a baseline temperature. Gap-phase models determine the north-south range of a species by the gdd limits at the north and south...
DEFF Research Database (Denmark)
Arrad, Mouad; Kaddami, Mohammed; Maous, Jaafar
2015-01-01
In this study, new experimental data for the binary system of Mn(NO3)2-H2O are presented in the temperature range from -29°C to 35°C at atmospheric pressure using the conductometric method, this synthetic method is an accurate experimental procedure in the determination of the solubility of salts...... in the entire range of temperature and composition of the salt....... in aqueous solutions.Thermodynamic modeling for the binary system of Mn(NO3)2-H2O is also presented based on this new experimental solubility data and some modification on the available data bank.Model parameters for this system were determined and revisited; these parameters are generally valid...
Mao, Zhun; Saint-André, Laurent; Bourrier, Franck; Stokes, Alexia; Cordonnier, Thomas
2015-08-01
In mountain ecosystems, predicting root density in three dimensions (3-D) is highly challenging due to the spatial heterogeneity of forest communities. This study presents a simple and semi-mechanistic model, named ChaMRoots, that predicts root interception density (RID, number of roots m(-2)). ChaMRoots hypothesizes that RID at a given point is affected by the presence of roots from surrounding trees forming a polygon shape. The model comprises three sub-models for predicting: (1) the spatial heterogeneity - RID of the finest roots in the top soil layer as a function of tree basal area at breast height, and the distance between the tree and a given point; (2) the diameter spectrum - the distribution of RID as a function of root diameter up to 50 mm thick; and (3) the vertical profile - the distribution of RID as a function of soil depth. The RID data used for fitting in the model were measured in two uneven-aged mountain forest ecosystems in the French Alps. These sites differ in tree density and species composition. In general, the validation of each sub-model indicated that all sub-models of ChaMRoots had good fits. The model achieved a highly satisfactory compromise between the number of aerial input parameters and the fit to the observed data. The semi-mechanistic ChaMRoots model focuses on the spatial distribution of root density at the tree cluster scale, in contrast to the majority of published root models, which function at the level of the individual. Based on easy-to-measure characteristics, simple forest inventory protocols and three sub-models, it achieves a good compromise between the complexity of the case study area and that of the global model structure. ChaMRoots can be easily coupled with spatially explicit individual-based forest dynamics models and thus provides a highly transferable approach for modelling 3-D root spatial distribution in complex forest ecosystems. © The Author 2015. Published by Oxford University Press on behalf of the
Ultrasonographic diagnosis of biliary atresia based on a decision-making tree model
Energy Technology Data Exchange (ETDEWEB)
Lee, So Mi; Cheon, Jung Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun Hye; Kim, In One; You, Sun Kyoung [Dept. of Radiology, Seoul National University College of Medicine, Seoul (Korea, Republic of)
2015-12-15
To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.
Ultrasonographic Diagnosis of Biliary Atresia Based on a Decision-Making Tree Model.
Lee, So Mi; Cheon, Jung-Eun; Choi, Young Hun; Kim, Woo Sun; Cho, Hyun-Hae; Cho, Hyun-Hye; Kim, In-One; You, Sun Kyoung
2015-01-01
To assess the diagnostic value of various ultrasound (US) findings and to make a decision-tree model for US diagnosis of biliary atresia (BA). From March 2008 to January 2014, the following US findings were retrospectively evaluated in 100 infants with cholestatic jaundice (BA, n = 46; non-BA, n = 54): length and morphology of the gallbladder, triangular cord thickness, hepatic artery and portal vein diameters, and visualization of the common bile duct. Logistic regression analyses were performed to determine the features that would be useful in predicting BA. Conditional inference tree analysis was used to generate a decision-making tree for classifying patients into the BA or non-BA groups. Multivariate logistic regression analysis showed that abnormal gallbladder morphology and greater triangular cord thickness were significant predictors of BA (p = 0.003 and 0.001; adjusted odds ratio: 345.6 and 65.6, respectively). In the decision-making tree using conditional inference tree analysis, gallbladder morphology and triangular cord thickness (optimal cutoff value of triangular cord thickness, 3.4 mm) were also selected as significant discriminators for differential diagnosis of BA, and gallbladder morphology was the first discriminator. The diagnostic performance of the decision-making tree was excellent, with sensitivity of 100% (46/46), specificity of 94.4% (51/54), and overall accuracy of 97% (97/100). Abnormal gallbladder morphology and greater triangular cord thickness (> 3.4 mm) were the most useful predictors of BA on US. We suggest that the gallbladder morphology should be evaluated first and that triangular cord thickness should be evaluated subsequently in cases with normal gallbladder morphology.
Yule-generated trees constrained by node imbalance.
Disanto, Filippo; Schlizio, Anna; Wiehe, Thomas
2013-11-01
The Yule process generates a class of binary trees which is fundamental to population genetic models and other applications in evolutionary biology. In this paper, we introduce a family of sub-classes of ranked trees, called Ω-trees, which are characterized by imbalance of internal nodes. The degree of imbalance is defined by an integer 0 ≤ ω. For caterpillars, the extreme case of unbalanced trees, ω = 0. Under models of neutral evolution, for instance the Yule model, trees with small ω are unlikely to occur by chance. Indeed, imbalance can be a signature of permanent selection pressure, such as observable in the genealogies of certain pathogens. From a mathematical point of view it is interesting to observe that the space of Ω-trees maintains several statistical invariants although it is drastically reduced in size compared to the space of unconstrained Yule trees. Using generating functions, we study here some basic combinatorial properties of Ω-trees. We focus on the distribution of the number of subtrees with two leaves. We show that expectation and variance of this distribution match those for unconstrained trees already for very small values of ω. Copyright © 2013 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Zheng Zhao
2018-01-01
Full Text Available Urban trees are more about people than trees. Urban trees programs need public support and engagement, from the intentions to support to implement actions in supporting the programs. Built upon the theory of planned behavior and Structural Equation Modeling (SEM, this study uses Beijing as a case study to investigate how subjective norm (cognition of urban trees, attitude (benefits residents’ believe urban trees can provide, and perceived behavioral control (the believed ability of what residents can do affect intention and its transformation into implemented of supporting action. A total of 800 residents were interviewed in 2016 and asked about their opinion of neighborhood trees, park trees, and historical trees, and analyzed, respectively. The results show that subjective norm has a significant positive effect on intentions pertaining to historical and neighborhood trees. Attitudes influence intentions, but its overall influence is much lower than that of the subjective norm, indicating that residents are more likely to be influenced by external factors. The perceived behavioral control has the strongest effect among the three, suggesting the importance of public participation in strengthening intention. The transformation from intention to behavior seems relatively small, especially regarding neighborhood trees, suggesting that perceptions and participation need to be strengthened.
International Nuclear Information System (INIS)
Meloni, S.
1998-01-01
To simulate transmitted radiation in agroforestry systems, radiative transfer models usually require a detailed three-dimensional description of the tree canopy. We propose here a simplification of the description of the three-dimensional structure of wild cherry trees (Prunus avium). The simplified tree description was tested against the detailed one for five-year-old wild cherry. It allowed accurate simulation of transmitted radiation and avoided tedious measurements of tree structure. The simplified description was then applied to older trees. Allometric relationships were used to compute the parameters not available on free-grown trees. The transmitted radiation in an agroforestry system was simulated at four different ages: 5, 10, 15 and 20 years. The trees were planted on a 5 m square grid. Two row orientations, chosen to provide different transmitted radiation patterns, were tested: north/south and north- east/south-west. The simulations showed that the daily mean transmitted radiation was reduced from 92% of incident radiation under five-year-old trees to 37% under 20-year-old trees. The variability of transmitted radiation increased with tree growth. The row orientation had only small effects on the shaded area at the beginning and end of the day when solar elevation was low. (author)
Surface-based geometric modelling using teaching trees for advanced robots
International Nuclear Information System (INIS)
Nakamura, Akira; Ogasawara, Tsukasa; Tsukune, Hideo; Oshima, Masaki
2000-01-01
Geometric modelling of the environment is important in robot motion planning. Generally, shapes can be stored in a data base, so the elements that need to be decided are positions and orientations. In this paper, surface-based geometric modelling using a teaching tree is proposed. In this modelling, combinations of surfaces are considered in order to decide positions and orientations of objects. The combinations are represented by a depth-first tree, which makes it easy for the operator to select one combination out of several. This method is effective not only in the case when perfect data can be obtained, but also when conditions for measurement of three-dimensional data are unfavorable, which often occur in the environment of a working robot. (author)
Sakschewski, B.; Kirsten, T.; von Bloh, W.; Poorter, L.; Pena-Claros, M.; Boit, A.
2016-12-01
Functional diversity of ecosystems has been found to increase ecosystem functions and therefore enhance ecosystem resilience against environmental stressors. However, global carbon-cycle and biosphere models still classify the global vegetation into a relatively small number of distinct plant functional types (PFT) with constant features over space and time. Therefore, those models might underestimate the resilience and adaptive capacity of natural vegetation under climate change by ignoring positive effects that functional diversity might bring about. We diversified a set a of selected tree traits in a dynamic global vegetation model (LPJmL). In the new subversion, called LPJmL-FIT, Amazon region biomass stocks and forest structure appear significantly more resilient against climate change. Enhanced tree trait diversity enables the simulated rainforests to adjust to new environmental conditions via ecological sorting. These results may stimulate a new debate on the value of biodiversity for climate change mitigation.
Chen, Wansu; Shi, Jiaxiao; Qian, Lei; Azen, Stanley P
2014-06-26
To estimate relative risks or risk ratios for common binary outcomes, the most popular model-based methods are the robust (also known as modified) Poisson and the log-binomial regression. Of the two methods, it is believed that the log-binomial regression yields more efficient estimators because it is maximum likelihood based, while the robust Poisson model may be less affected by outliers. Evidence to support the robustness of robust Poisson models in comparison with log-binomial models is very limited. In this study a simulation was conducted to evaluate the performance of the two methods in several scenarios where outliers existed. The findings indicate that for data coming from a population where the relationship between the outcome and the covariate was in a simple form (e.g. log-linear), the two models yielded comparable biases and mean square errors. However, if the true relationship contained a higher order term, the robust Poisson models consistently outperformed the log-binomial models even when the level of contamination is low. The robust Poisson models are more robust (or less sensitive) to outliers compared to the log-binomial models when estimating relative risks or risk ratios for common binary outcomes. Users should be aware of the limitations when choosing appropriate models to estimate relative risks or risk ratios.
International Nuclear Information System (INIS)
Gutierrez, Jorge E.; Bejarano, Arturo; Fuente, Juan C. de la
2010-01-01
An apparatus based on a static-analytic method assembled in this work was utilized to perform high pressure (vapour + liquid) equilibria measurements with uncertainties estimated at 2 + 1-propanol), (CO 2 + 2-methyl-1-propanol), (CO 2 + 3-methyl-1-butanol), and (CO 2 + 1-pentanol) binary systems at temperatures of (313, 323, and 333) K, and at pressure range of (2 to 12) MPa. For all the (CO 2 + alcohol) systems, it was visually monitored to insure that there was no liquid immiscibility at the temperatures and pressures studied. The experimental results were correlated with the Peng-Robinson equation of state using the quadratic mixing rules of van der Waals with two adjustable parameters. The calculated (vapour + liquid) equilibria compositions were found to be in good agreement with the experimental values with deviations for the mol fractions <0.12 and <0.05 for the liquid and vapour phase, respectively.
Bright, Jane; Torres, Guillermo
2018-01-01
We report new spectroscopic observations of the F-type triple system V2154 Cyg, in which two of the stars form an eclipsing binary with a period of 2.6306303 ± 0.0000038 days. We combine the results from our spectroscopic analysis with published light curves in the uvby Strömgren passbands to derive the first reported absolute dimensions of the stars in the eclipsing binary. The masses and radii are measured with high accuracy to better than 1.5% precision. For the primary and secondary respectively, we find that the masses are 1.269 ± 0.017 M⊙ and 0.7542 ± 0.0059 M⊙, the radii are 1.477 ± 0.012 R⊙ and 0.7232 ± 0.0091R⊙, and the temperatures are 6770 ± 150 K and 5020 ± 150 K. Current models of stellar evolution agree with the measured properties of the primary, but the secondary is larger than predicted. This may be due to activity in the secondary, as has been shown for other systems with a star of similar mass with this same discrepancy.The SAO REU program is funded by the National Science Foundation REU and Department of Defense ASSURE programs under NSF Grant AST-1659473, and by the Smithsonian Institution. GT acknowledges partial support for this work from NSF grant AST-1509375.
On phase transitions of the Potts model with three competing interactions on Cayley tree
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S. Temir
2011-06-01
Full Text Available In the present paper we study a phase transition problem for the Potts model with three competing interactions, the nearest neighbors, the second neighbors and triples of neighbors and non-zero external field on Cayley tree of order two. We prove that for some parameter values of the model there is phase transition. We reduce the problem of describing by limiting Gibbs measures to the problem of solving a system of nonlinear functional equations. We extend the results obtained by Ganikhodjaev and Rozikov [Math. Phys. Anal. Geom., 2009, vol. 12, No. 2, 141-156] on phase transition for the Ising model to the Potts model setting.
International Nuclear Information System (INIS)
Wang Jinshan; Zhu Yuqun; Jiang Chao
2006-01-01
A mathematic model is established that formulated the relationship between the working temperature and thermal gradient in producing a uniform liquid layer of binary fuel mixture inside a cryogenic spherical shell inertial confinement fusion target. When the external linear thermal gradient was imposed on the target, the model showed the gradient of face tension induced by thermal gradient acted on the far field pull the liquid inside the ICF forward. This motion overcame the effect of gravitation to produce a uniform liquid layer inside ICF. And a finite element analysis of the heat transfer in hollow micro-sphere filled with the ICF fuel was made, the results compared with the experimental finding by K. Kim and the tendency of the thermal gradient was shown to be similar. (authors)
International Nuclear Information System (INIS)
Pizzirusso, Antonio; De Nicola, Antonio; Milano, Giuseppe; Brasiello, Antonio; Marangoni, Alejandro G
2015-01-01
The first simulation study of the crystallisation of a binary mixture of triglycerides using molecular dynamics simulations is reported. Coarse-grained models of tristearin (SSS) and tripalmitin (PPP) molecules have been considered. The models have been preliminarily tested in the crystallisation of pure SSS and PPP systems. Two different quenching procedures have been tested and their performances have been analysed. The structures obtained from the crystallisation procedures show a high orientation order and a high content of molecules in the tuning fork conformation, comparable with the crystalline α phase. The behaviour of melting temperatures for the α phase of the mixture SSS/PPP obtained from the simulations is in qualitative agreement with the behaviour that was experimentally determined. (paper)
DEFF Research Database (Denmark)
Fraser, Diane P.; Zuckermann, Martin J.; Mouritsen, Ole G.
1991-01-01
by the method in the case of a binary mixture, and results are presented for varying disk-size ratios and degeneracies. The results are also compared with the predictions of the extended scaled-particle theory. Applications of the model are discussed in relation to lipid monolayers spread on air......A two-dimensional Monte Carlo simulation method based on the NpT ensemble and the Voronoi tesselation, which was previously developed for single-species hard-disk systems, is extended, along with a version of scaled-particle theory, to many-component mixtures. These systems are unusual in the sense...... that their composition is not fixed, but rather determined by a set of internal degeneracies assigned to the differently sized hard disks, where the larger disks have the higher degeneracies. Such systems are models of monolayers of molecules with internal degrees of freedom. The combined set of translational...
Complementary models of tree species-soil relationships in old-growth temperate forests
Cross, Alison; Perakis, Steven S.
2011-01-01
Ecosystem level studies identify plant soil feed backs as important controls on soil nutrient availability,particularly for nitrogen and phosphorus. Although site and species specific studies of tree species soil relationships are relatively common,comparatively fewer studies consider multiple coexisting speciesin old-growth forests across a range of sites that vary underlying soil fertility. We characterized patterns in forest floor and mineral soil nutrients associated with four common tree species across eight undisturbed old-growth forests in Oregon, USA, and used two complementary conceptual models to assess tree species soil relationships. Plant soil feedbacks that could reinforce sitelevel differences in nutrient availability were assessed using the context dependent relationships model, where by relative species based differences in each soil nutrient divergedorconvergedas nutrient status changed across sites. Tree species soil relationships that did not reflect strong feedbacks were evaluated using a site independent relationships model, where by forest floor and surface mineral soil nutrient tools differed consistently by tree species across sites,without variation in deeper mineral soils. We found that theorganically cycled elements carbon, nitrogen, and phosphorus exhibited context-dependent differences among species in both forest floor and mineral soil, and most of ten followed adivergence model,where by species differences were greatest at high-nutrient sites. These patterns are consistent with the oryemphasizing biotic control of these elements through plant soil feedback mechanisms. Site independent species differences were strongest for pool so if the weather able cations calcium, magnesium, potassium,as well as phosphorus, in mineral soils. Site independent species differences in forest floor nutrients we reattributable too nespecies that displayed significant greater forest floor mass accumulation. Our finding confirmed that site-independent and
A conceptual approach to approximate tree root architecture in infinite slope models
Schmaltz, Elmar; Glade, Thomas
2016-04-01
Vegetation-related properties - particularly tree root distribution and coherent hydrologic and mechanical effects on the underlying soil mantle - are commonly not considered in infinite slope models. Indeed, from a geotechnical point of view, these effects appear to be difficult to be reproduced reliably in a physically-based modelling approach. The growth of a tree and the expansion of its root architecture are directly connected with both intrinsic properties such as species and age, and extrinsic factors like topography, availability of nutrients, climate and soil type. These parameters control four main issues of the tree root architecture: 1) Type of rooting; 2) maximum growing distance to the tree stem (radius r); 3) maximum growing depth (height h); and 4) potential deformation of the root system. Geometric solids are able to approximate the distribution of a tree root system. The objective of this paper is to investigate whether it is possible to implement root systems and the connected hydrological and mechanical attributes sufficiently in a 3-dimensional slope stability model. Hereby, a spatio-dynamic vegetation module should cope with the demands of performance, computation time and significance. However, in this presentation, we focus only on the distribution of roots. The assumption is that the horizontal root distribution around a tree stem on a 2-dimensional plane can be described by a circle with the stem located at the centroid and a distinct radius r that is dependent on age and species. We classified three main types of tree root systems and reproduced the species-age-related root distribution with three respective mathematical solids in a synthetic 3-dimensional hillslope ambience. Thus, two solids in an Euclidian space were distinguished to represent the three root systems: i) cylinders with radius r and height h, whilst the dimension of latter defines the shape of a taproot-system or a shallow-root-system respectively; ii) elliptic
He, Minhui; Shishov, Vladimir; Kaparova, Nazgul; Yang, Bao; Bräuning, Achim; Grießinger, Jussi
2017-04-01
Response of climate warming on tree-ring formation has attracted much attention during recent years. However, most studies are based on statistical analysis, lacking understanding of tree-physiological processes, especially on the mountainous region of the Tibetan Plateau (TP). Herein, we firstly use an updated new version of the tree-ring process-based Vaganov-Shashkin model (VS-oscilloscope) to simulate tree-ring formation and its relationships with climate factors during the past six decades. Our analysis covered 341 sampled trees, with elevation ranges from 2750 to 4575 m a.s.l. at five sampling sites from southern to northern part of the TP. Simulated tree-ring width series are significantly (p interval periods. Starting dates of tree-ring width formation are all determined by temperature at the five sampling sites. After the initiation of tree stem cambial activity, soil moisture content has a significant effect on tree-ring growth. Ending dates are driven by temperature in the study region. Simulated results indicate the difference between wide and narrow tree-ring formation is mostly induced by soil moisture content, especially at the first half of the growing season, while effect from temperature is minor. Interestingly, we detected significantly (p the year 1985 at the five sampling sites. However, the variability of mean relative growth rate due to temperature (GrT) is negligible before and after that. Based on the successful application of VS-oscilloscope modeling on the high-elevation tree stands of the TP, our study provides a new perspective of tree radial growth process and their relationships with climate data during the past six decades.
Don C. Bragg; Jeffrey L. Kershner
2004-01-01
Riparian large woody debris (LWD) recruitment simulations have traditionally applied a random angle of tree fall from two well-forested stream banks. We used a riparian LWD recruitment model (CWD, version 1.4) to test the validity these assumptions. Both the number of contributing forest banks and predominant tree fall direction significantly influenced simulated...
Eric M. Pfeifer; Jeffrey A. Hicke; Arjan J.H. Meddens
2011-01-01
Bark beetle epidemics result in tree mortality across millions of hectares in North America. However, few studies have quantified impacts on carbon (C) cycling. In this study, we quantified the immediate response and subsequent trajectories of stand-level aboveground tree C stocks and fluxes using field measurements and modeling for a location in central Idaho, USA...
International Nuclear Information System (INIS)
Vichev, S.; Bogdanov, D.
2000-01-01
The purpose of this paper is to introduce the fault tree analysis method as a tool for unit protection reliability estimation. The constant failure rate model applies for making reliability assessment, and especially availability assessment. For that purpose an example for unit primary equipment structure and fault tree example for simplified unit protection system is presented (author)
Hülsmann, Lisa; Bugmann, Harald; Cailleret, Maxime; Brang, Peter
2018-03-01
Dynamic Vegetation Models (DVMs) are designed to be suitable for simulating forest succession and species range dynamics under current and future conditions based on mathematical representations of the three key processes regeneration, growth, and mortality. However, mortality formulations in DVMs are typically coarse and often lack an empirical basis, which increases the uncertainty of projections of future forest dynamics and hinders their use for developing adaptation strategies to climate change. Thus, sound tree mortality models are highly needed. We developed parsimonious, species-specific mortality models for 18 European tree species using >90,000 records from inventories in Swiss and German strict forest reserves along a considerable environmental gradient. We comprehensively evaluated model performance and incorporated the new mortality functions in the dynamic forest model ForClim. Tree mortality was successfully predicted by tree size and growth. Only a few species required additional covariates in their final model to consider aspects of stand structure or climate. The relationships between mortality and its predictors reflect the indirect influences of resource availability and tree vitality, which are further shaped by species-specific attributes such as maximum longevity and shade tolerance. Considering that the behavior of the models was biologically meaningful, and that their performance was reasonably high and not impacted by changes in the sampling design, we suggest that the mortality algorithms developed here are suitable for implementation and evaluation in DVMs. In the DVM ForClim, the new mortality functions resulted in simulations of stand basal area and species composition that were generally close to historical observations. However, ForClim performance was poorer than when using the original, coarse mortality formulation. The difficulties of simulating stand structure and species composition, which were most evident for Fagus sylvatica L
Domańska, Urszula; Zawadzki, Maciej; Paduszyński, Kamil; Królikowski, Marek
2012-07-19
This contribution reports a recapitulation of our experimental and modeling study on thermodynamic behavior of binary systems containing N-alkylisoquinolinium ionic liquids (ILs) based on bis(trifluoromethylsulfonyl)imide anion, [CniQuin][NTf2] (n = 4,6,8). In particular, we report isothermal vapor-liquid equilibrium (VLE) phase diagrams and molar excess enthalpies of mixing (H(E)) for binary mixtures of [C8iQuin][NTf2] IL with various organic solutes including benzene, toluene, thiophene, pyridine, and butan-1-ol. The measured VLE data represented simple homozeotropic behavior with either negative or positive deviations from ideality, depending on polarity of the solute, temperature, and mole fraction of IL. In turn, the obtained data on H(E) were negative and positive for the mixtures containing aromatic hydrocarbons or thiophene and butan-1-ol, respectively, in the whole range of IL's concentration. All of the measured and some previously published data regarding phase behavior of [C8iQuin][NTf2] IL were analyzed and successfully described in terms of perturbed-chain statistical associating fluid theory (PC-SAFT). The methodology used in this work was described by us previously. In general, the proposed modeling results in VLE diagrams, which are in excellent agreement with experimental data. In the case of H(E), the results obtained are good as well but not so satisfactory such as those for VLE. Nevertheless, they seem to be very promising if one take into account the simplicity of the utilized molecular model against significant complexity of IL-based systems. Thus, we concluded that PC-SAFT equation of state can be viewed as a powerful and robust tool for modeling of systems involving ILs.
Directory of Open Access Journals (Sweden)
Albaiti Albaiti
2016-04-01
Full Text Available N-hexane and methanol systen is one example of a binary system that shows the solubility properties of reciprocity. This study aimed to assess the mental model of a n-hexane-methanolbinary system. Interaction at the submicroscopic level between n-hexane and methanol molecules is described in the form of mental model. Penelitian ini menggunakan cloud point method untuk memperoleh data kesetimbangan cair-cair sistem n-heksana-metanol. This study used a cloud point method to obtain data on liquid-liquid equilibrium on the system of n-hexane-methanol. Research data showed the maximum critical temperature (above the consolute temperature of this system was at 42.95 °C with Xmethanol = 0.475 (P= 715 mmHg. Data from the laboratory observations was representedas a symbolic level in the form of the curve of correlation between mole fraction of methanol with temperature in a phase diagram system of n-hexane-methanol. The curve that was formed was asymmetric. It indicated that the solubility of n-hexane in methanol was relatively small compared to the solubility of methanol in n-hexane. Mental model of the binary system of n-hexane-methanol in four curve areasin the form of visualization of the interaction between n-hexane and methanol molecules through London force. In thermodynamics, each component had the same chemical potential inboth phases at equilibrium state. This study results could have a contribution to form a mental model on the student as the prospective chemistry subject teachers.
Regional deposition of thoron progeny in models of the human tracheobronchial tree
Energy Technology Data Exchange (ETDEWEB)
Smith, S.M.; Cheng, Yung-Sung; Yeh, Hsu-Chi
1995-12-01
Models of the human tracheobronchial tree have been used to determine total and regional aerosol deposition of inhaled particles. Particle sizes measured in these studies have all been > 40 nm in diameter. The deposition of aerosols < 40 nm in diameter has not been measured. Particles in the ultrafine aerosol size range include some combustion aerosols and indoor radon progeny. Also, the influence of reduced lung size and airflow rates on particle deposition in young children has not been determined. With their smaller lung size and smaller minute volumes, children may be at increased risk from ultrafine pollutants. In order to accurately determine dose of inhaled aerosols, the effects of particle size, minute volume, and age at exposure must be quantified. The purpose of this study was to determine the deposition efficiency of ultrafine aerosols smaller than 40 nm in diameter in models of the human tracheobronchia tree. This study demonstrates that the deposition efficiency of aerosols in the model of the child`s tracheobronchial tree may be slightly higher than in the adult models.
Directory of Open Access Journals (Sweden)
Elias .
2011-03-01
Full Text Available The case study was conducted in the area of Acacia mangium plantation at BKPH Parung Panjang, KPH Bogor. The objective of the study was to formulate equation models of tree root carbon mass and root to shoot carbon mass ratio of the plantation. It was found that carbon content in the parts of tree biomass (stems, branches, twigs, leaves, and roots was different, in which the highest and the lowest carbon content was in the main stem of the tree and in the leaves, respectively. The main stem and leaves of tree accounted for 70% of tree biomass. The root-shoot ratio of root biomass to tree biomass above the ground and the root-shoot ratio of root biomass to main stem biomass was 0.1443 and 0.25771, respectively, in which 75% of tree carbon mass was in the main stem and roots of tree. It was also found that the root-shoot ratio of root carbon mass to tree carbon mass above the ground and the root-shoot ratio of root carbon mass to tree main stem carbon mass was 0.1442 and 0.2034, respectively. All allometric equation models of tree root carbon mass of A. mangium have a high goodness-of-fit as indicated by its high adjusted R2.Keywords: Acacia mangium, allometric, root-shoot ratio, biomass, carbon mass
Non-robust Phase Transitions in the Generalized Clock Model on Trees
Külske, C.; Schriever, P.
2018-01-01
Pemantle and Steif provided a sharp threshold for the existence of a robust phase transition (RPT) for the continuous rotator model and the Potts model in terms of the branching number and the second eigenvalue of the transfer matrix whose kernel describes the nearest neighbor interaction along the edges of the tree. Here a RPT is said to occur if an arbitrarily weak coupling with symmetry-breaking boundary conditions suffices to induce symmetry breaking in the bulk. They further showed that for the Potts model RPT occurs at a different threshold than PT (phase transition in the sense of multiple Gibbs measures), and conjectured that RPT and PT should occur at the same threshold in the continuous rotator model. We consider the class of four- and five-state rotation-invariant spin models with reflection symmetry on general trees which contains the Potts model and the clock model with scalarproduct-interaction as limiting cases. The clock model can be viewed as a particular discretization which is obtained from the classical rotator model with state space S^1. We analyze the transition between PT=RPT and PT≠ RPT, in terms of the eigenvalues of the transfer matrix of the model at the critical threshold value for the existence of RPT. The transition between the two regimes depends sensitively on the third largest eigenvalue.
DEFF Research Database (Denmark)
Herslund, Peter Jørgensen; Thomsen, Kaj; Abildskov, Jens
2013-01-01
The complex fluid phase behaviour, of the binary system comprised of water and tetrahydrofuran (THF) is modelled by use of the cubic-plus-association (CPA) equation of state. A total of seven modelling approaches are analysed, differing only in their way of describing THF and its interactions...
Microwave sensing of tree trunks
Jezova, Jana; Mertens, Laurence; Lambot, Sebastien
2015-04-01
was divided into three sections to separate parts with different moisture (heartwood and sapwood) or empty space (decays). For easier manipulation with the antenna we developed a special ruler for measuring the distance along the scans. Instead of the surveying wheel we read the distance with a camera, which was fixed on the antenna and focused on the ruler with a binary pattern. Hence, during whole measurement and the data processing we were able to identify an accurate position on the tree in view of the scan. Some preliminary measurements on the trees were also conducted. They were performed using a GSSI 900 MHz antenna. Several tree species (beech, horse-chestnut, birch, ...) in Louvain-la-Neuve and Brussels, Belgium, have been investigated to see the internal structure of the tree decays. The measurements were carried out mainly by circumferential measurement around the trunk and also by vertical measurement along the trunk for approximate detection of the cavity. The comparison between the numerical simulations, simplified tree trunk model and real data from trees is presented. This research is funded by the Fonds de la Recherche Scientifique (FNRS, Belgium) and benefits from networking activities carried out within the EU COST Action TU1208 "Civil Engineering Applications of Ground Penetrating Radar".
Babanatsas, T.; Glăvan, D. O.; Babanatis Merce, R. M.; Maris, S. A.
2018-01-01
The purpose of this study is to bring as much as possible, close to real situation the 3D modelling for the olive trees in order to establish the necessary forces for automatic harvesting (harvesting robots). To fulfil our goal we have at our disposal different ways to do modelling very close to the real situation. One way is to use reality capture software (its results being photos) that are converted into a real 3D model, the disadvantage of the method being a mesh model that is not accurate enough. The reasonable alternative is to develop an experiment by measuring a sample orchard of olive trees (experiment who took place in Halkidiki, Greece, measuring over 120 trees). After establishing the real dimensions, we adopted as model the media that we have measured (the height of the tree, the thickness of branches, number of branches, etc.), model which we consider closer to the reality and therefor more suitable for our simulation.
Analysis of a Model for the Morphological Structure of Renal Arterial Tree: Fractal Structure
Directory of Open Access Journals (Sweden)
Aurora Espinoza-Valdez
2013-01-01
experimental data measurements of the rat kidneys. The fractal dimension depends on the probability of sprouting angiogenesis in the development of the arterial vascular tree of the kidney, that is, of the distribution of blood vessels in the morphology generated by the analytical model. The fractal dimension might determine whether a suitable renal vascular structure is capable of performing physiological functions under appropriate conditions. The analysis can describe the complex structures of the development vasculature in kidney.
Directory of Open Access Journals (Sweden)
T. Sghaier
2013-12-01
Full Text Available Aim of study: The aim of the work was to develop an individual tree diameter-increment model for Thuya (Tetraclinis articulata in Tunisia.Area of study: The natural Tetraclinis articulata stands at Jbel Lattrech in north-eastern of Tunisia.Material and methods: Data came from 200 trees located in 50 sample plots. The diameter at age t and the diameter increment for the last five years obtained from cores taken at breast height were measured for each tree. Four difference equations derived from the base functions of Richards, Lundqvist, Hossfeld IV and Weibull were tested using the age-independent formulations of the growth functions. Both numerical and graphical analyses were used to evaluate the performance of the candidate models.Main results: Based on the analysis, the age-independent difference equation derived from the base function Richards model was selected. Two of the three parameters (growth rate and shape parameter of the retained model were related to site quality, represented by a Growth Index, stand density and the basal area in larger trees divided by diameter of the subject tree expressing the inter-tree competition.Research highlights: The proposed model can be useful for predicting the diameter growth of Tetraclinis articulata in Tunisia when age is not available or for trees growing in uneven-aged stands.Keywords: Age-independent growth model; difference equations; Tetraclinis articulata; Tunisia.
Yang, Ziheng; Zhu, Tianqi
2018-02-20
The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.
Directory of Open Access Journals (Sweden)
R. K. Tiwari
2011-08-01
Full Text Available A novel technique based on the Bayesian neural network (BNN theory is developed and employed to model the temperature variation record from the Western Himalayas. In order to estimate an a posteriori probability function, the BNN is trained with the Hybrid Monte Carlo (HMC/Markov Chain Monte Carlo (MCMC simulations algorithm. The efficacy of the new algorithm is tested on the well known chaotic, first order autoregressive (AR and random models and then applied to model the temperature variation record decoded from the tree-ring widths of the Western Himalayas for the period spanning over 1226–2000 AD. For modeling the actual tree-ring temperature data, optimum network parameters are chosen appropriately and then cross-validation test is performed to ensure the generalization skill of the network on the new data set. Finally, prediction result based on the BNN model is compared with the conventional artificial neural network (ANN and the AR linear models results. The comparative results show that the BNN based analysis makes better prediction than the ANN and the AR models. The new BNN modeling approach provides a viable tool for climate studies and could also be exploited for modeling other kinds of environmental data.
Steensels, M; Antler, A; Bahr, C; Berckmans, D; Maltz, E; Halachmi, I
2016-09-01
Early detection of post-calving health problems is critical for dairy operations. Separating sick cows from the herd is important, especially in robotic-milking dairy farms, where searching for a sick cow can disturb the other cows' routine. The objectives of this study were to develop and apply a behaviour- and performance-based health-detection model to post-calving cows in a robotic-milking dairy farm, with the aim of detecting sick cows based on available commercial sensors. The study was conducted in an Israeli robotic-milking dairy farm with 250 Israeli-Holstein cows. All cows were equipped with rumination- and neck-activity sensors. Milk yield, visits to the milking robot and BW were recorded in the milking robot. A decision-tree model was developed on a calibration data set (historical data of the 10 months before the study) and was validated on the new data set. The decision model generated a probability of being sick for each cow. The model was applied once a week just before the veterinarian performed the weekly routine post-calving health check. The veterinarian's diagnosis served as a binary reference for the model (healthy-sick). The overall accuracy of the model was 78%, with a specificity of 87% and a sensitivity of 69%, suggesting its practical value.
Perceived Organizational Support for Enhancing Welfare at Work: A Regression Tree Model
Giorgi, Gabriele; Dubin, David; Perez, Javier Fiz
2016-01-01
When trying to examine outcomes such as welfare and well-being, research tends to focus on main effects and take into account limited numbers of variables at a time. There are a number of techniques that may help address this problem. For example, many statistical packages available in R provide easy-to-use methods of modeling complicated analysis such as classification and tree regression (i.e., recursive partitioning). The present research illustrates the value of recursive partitioning in the prediction of perceived organizational support in a sample of more than 6000 Italian bankers. Utilizing the tree function party package in R, we estimated a regression tree model predicting perceived organizational support from a multitude of job characteristics including job demand, lack of job control, lack of supervisor support, training, etc. The resulting model appears particularly helpful in pointing out several interactions in the prediction of perceived organizational support. In particular, training is the dominant factor. Another dimension that seems to influence organizational support is reporting (perceived communication about safety and stress concerns). Results are discussed from a theoretical and methodological point of view. PMID:28082924
An Assessment for A Filtered Containment Venting Strategy Using Decision Tree Models
International Nuclear Information System (INIS)
Shin, Hoyoung; Jae, Moosung
2016-01-01
In this study, a probabilistic assessment of the severe accident management strategy through a filtered containment venting system was performed by using decision tree models. In Korea, the filtered containment venting system has been installed for the first time in Wolsong unit 1 as a part of Fukushima follow-up steps, and it is planned to be applied gradually for all the remaining reactors. Filtered containment venting system, one of severe accident countermeasures, prevents a gradual pressurization of the containment building exhausting noncondensable gas and vapor to the outside of the containment building. In this study, a probabilistic assessment of the filtered containment venting strategy, one of the severe accident management strategies, was performed by using decision tree models. Containment failure frequencies of each decision were evaluated by the developed decision tree model. The optimum accident management strategies were evaluated by comparing the results. Various strategies in severe accident management guidelines (SAMG) could be improved by utilizing the methodology in this study and the offsite risk analysis methodology
Directory of Open Access Journals (Sweden)
Dan A. MacIsaac
2011-09-01
Full Text Available We investigated the relationship of stem diameter to tree, site and stand characteristics for six major tree species (trembling aspen, white birch, balsam fir, lodgepole pine, black spruce, and white spruce in Alberta (Canada with data from Alberta Sustainable Resource Development Permanent Sample Plots. Using non-linear mixed effects modeling techniques, we developed models to estimate diameter at breast height using height, crown and stand attributes. Mixed effects models (with plot as subject using height, crown area, and basal area of the larger trees explained on average 95% of the variation in diameter at breast height across the six species with a root mean square error of 2.0 cm (13.4% of mean diameter. Fixed effects models (without plot as subject including the Natural Sub-Region (NSR information explained on average 90% of the variation in diameter at breast height across the six species with a root mean square error equal to 2.8 cm (17.9% of mean diameter. Selected climate variables provided similar results to models with NSR information. The inclusion of nutrient regime and moisture regime did not significantly improve the predictive ability of these models.
International Nuclear Information System (INIS)
Wu, Qiong-Li; Cournède, Paul-Henry; Mathieu, Amélie
2012-01-01
Global sensitivity analysis has a key role to play in the design and parameterisation of functional–structural plant growth models which combine the description of plant structural development (organogenesis and geometry) and functional growth (biomass accumulation and allocation). We are particularly interested in this study in Sobol's method which decomposes the variance of the output of interest into terms due to individual parameters but also to interactions between parameters. Such information is crucial for systems with potentially high levels of non-linearity and interactions between processes, like plant growth. However, the computation of Sobol's indices relies on Monte Carlo sampling and re-sampling, whose costs can be very high, especially when model evaluation is also expensive, as for tree models. In this paper, we thus propose a new method to compute Sobol's indices inspired by Homma–Saltelli, which improves slightly their use of model evaluations, and then derive for this generic type of computational methods an estimator of the error estimation of sensitivity indices with respect to the sampling size. It allows the detailed control of the balance between accuracy and computing time. Numerical tests on a simple non-linear model are convincing and the method is finally applied to a functional–structural model of tree growth, GreenLab, whose particularity is the strong level of interaction between plant functioning and organogenesis. - Highlights: ► We study global sensitivity analysis in the context of functional–structural plant modelling. ► A new estimator based on Homma–Saltelli method is proposed to compute Sobol indices, based on a more balanced re-sampling strategy. ► The estimation accuracy of sensitivity indices for a class of Sobol's estimators can be controlled by error analysis. ► The proposed algorithm is implemented efficiently to compute Sobol indices for a complex tree growth model.
Detecting Difference between Process Models Based on the Refined Process Structure Tree
Directory of Open Access Journals (Sweden)
Jing Fan
2017-01-01
Full Text Available The development of mobile workflow management systems (mWfMS leads to large number of business process models. In the meantime, the location restriction embedded in mWfMS may result in different process models for a single business process. In order to help users quickly locate the difference and rebuild the process model, detecting the difference between different process models is needed. Existing detection methods either provide a dissimilarity value to represent the difference or use predefined difference template to generate the result, which cannot reflect the entire composition of the difference. Hence, in this paper, we present a new approach to solve this problem. Firstly, we parse the process models to their corresponding refined process structure trees (PSTs, that is, decomposing a process model into a hierarchy of subprocess models. Then we design a method to convert the PST to its corresponding task based process structure tree (TPST. As a consequence, the problem of detecting difference between two process models is transformed to detect difference between their corresponding TPSTs. Finally, we obtain the difference between two TPSTs based on the divide and conquer strategy, where the difference is described by an edit script and we make the cost of the edit script close to minimum. The extensive experimental evaluation shows that our method can meet the real requirements in terms of precision and efficiency.
Oh, Hyo-Sook; Park, Hyeoun-Ae
2006-06-01
This study was performed to develop and test a decision-tree model of treatment-seeking behaviors about when Korean patients visit a doctor after experiencing stroke symptoms. The study used methodological triangulation. The model was developed based on qualitative data collected from in-depth interviews with 18 stroke patients. The model was tested using quantitative data collected from interviews and a structured questionnaire involving 150 stroke patients. The predictability of the decision-tree model was quantified as the proportion of participants who followed the pathway predicted by the model. Decision outcomes of the model were categorized into immediate and delayed treatment-seeking behavior. The model was influenced by lowered consciousness, social-group influences, perceived seriousness of symptoms, past history of hypertension or stroke, and barriers to hospital visits. The predictability of the model was found to be 90.7%. The results from this study can help healthcare personnel understand the education needs of stroke patients regarding treatment-seeking behaviors, and hence aid in the development of educational strategies for stroke patients.
International Nuclear Information System (INIS)
Dongiovanni, Danilo Nicola; Iesmantas, Tomas
2016-01-01
Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability
Energy Technology Data Exchange (ETDEWEB)
Dongiovanni, Danilo Nicola, E-mail: danilo.dongiovanni@enea.it [ENEA, Nuclear Fusion and Safety Technologies Department, via Enrico Fermi 45, Frascati 00040 (Italy); Iesmantas, Tomas [LEI, Breslaujos str. 3 Kaunas (Lithuania)
2016-11-01
Highlights: • RAMI (Reliability, Availability, Maintainability and Inspectability) assessment of secondary heat transfer loop for a DEMO nuclear fusion plant. • Definition of a fault tree for a nuclear steam turbine operated in pulsed mode. • Turbine failure rate models update by mean of a Bayesian network reflecting the fault tree analysis in the considered scenario. • Sensitivity analysis on system availability performance. - Abstract: Availability will play an important role in the Demonstration Power Plant (DEMO) success from an economic and safety perspective. Availability performance is commonly assessed by Reliability Availability Maintainability Inspectability (RAMI) analysis, strongly relying on the accurate definition of system components failure modes (FM) and failure rates (FR). Little component experience is available in fusion application, therefore requiring the adaptation of literature FR to fusion plant operating conditions, which may differ in several aspects. As a possible solution to this problem, a new methodology to extrapolate/estimate components failure rate under different operating conditions is presented. The DEMO Balance of Plant nuclear steam turbine component operated in pulse mode is considered as study case. The methodology moves from the definition of a fault tree taking into account failure modes possibly enhanced by pulsed operation. The fault tree is then translated into a Bayesian network. A statistical model for the turbine system failure rate in terms of subcomponents’ FR is hence obtained, allowing for sensitivity analyses on the structured mixture of literature and unknown FR data for which plausible value intervals are investigated to assess their impact on the whole turbine system FR. Finally, the impact of resulting turbine system FR on plant availability is assessed exploiting a Reliability Block Diagram (RBD) model for a typical secondary cooling system implementing a Rankine cycle. Mean inherent availability
Analytical model of the binary multileaf collimator of tomotherapy for Monte Carlo simulations
International Nuclear Information System (INIS)
Sterpin, E; Vynckier, S; Salvat, F; Olivera, G H
2008-01-01
Helical Tomotherapy (HT) delivers intensity-modulated radiotherapy by the means of many configurations of the binary multi-leaf collimator (MLC). The aim of the present study was to devise a method, which we call the 'transfer function' (TF) method, to perform the transport of particles through the MLC much faster than the time consuming Monte Carlo (MC) simulation and with no significant loss of accuracy. The TF method consists of calculating, for each photon in the phase-space file, the attenuation factor for each leaf (up to three) that the photon passes, assuming straight propagation through closed leaves, and storing these factors in a modified phase-space file. To account for the transport through the MLC in a given configuration, the weight of a photon is simply multiplied by the attenuation factors of the leaves that are intersected by the photon ray and are closed. The TF method was combined with the PENELOPE MC code, and validated with measurements for the three static field sizes available (40x5, 40x2.5 and 40x1 cm 2 ) and for some MLC patterns. The TF method allows a large reduction in computation time, without introducing appreciable deviations from the result of full MC simulations
Lizotte, Todd E.; Ohar, Orest P.; Tuttle, Tracie
2006-04-01
Performance of diffractive optics is determined by high-quality design and a suitable fabrication process that can actually realize the design. Engineers who are tasked with developing or implementing a diffractive optic solution into a product need to take into consideration the risks of using grayscale versus binary fabrication processes. In many cases, grayscale design doesn't always provide the best solution or cost benefit during product development. This fabrication dilemma arises when the engineer has to select a source for design and/or fabrication. Engineers come face to face with reality in view of the fact that diffractive optic suppliers tend to provide their services on a "best effort basis". This can be very disheartening to an engineer who is trying to implement diffractive optics. This paper will compare and contrast the design and performance of a 1 to 24 beam, two dimensional; beam splitter fabricated using a fifty (50) phase level grayscale and a five (5) phase level binary fabrication methods. Optical modeling data will be presented showing both designs and the performance expected prior to fabrication. An overview of the optical testing methods used will be discussed including the specific test equipment and metrology techniques used to verify actual optical performance and fabricated dimensional stability of each optical element. Presentation of the two versions of the splitter will include data on fabrication dimensional errors, split beam-to-beam uniformity, split beam-to-beam spatial size uniformity and splitter efficiency as compared to the original intended design performance and models. This is a continuation of work from 2005, Laser Beam Shaping VI.
Chuine, Isabelle; Bonhomme, Marc; Legave, Jean-Michel; García de Cortázar-Atauri, Iñaki; Charrier, Guillaume; Lacointe, André; Améglio, Thierry
2016-10-01
The onset of the growing season of trees has been earlier by 2.3 days per decade during the last 40 years in temperate Europe because of global warming. The effect of temperature on plant phenology is, however, not linear because temperature has a dual effect on bud development. On one hand, low temperatures are necessary to break bud endodormancy, and, on the other hand, higher temperatures are necessary to promote bud cell growth afterward. Different process-based models have been developed in the last decades to predict the date of budbreak of woody species. They predict that global warming should delay or compromise endodormancy break at the species equatorward range limits leading to a delay or even impossibility to flower or set new leaves. These models are classically parameterized with flowering or budbreak dates only, with no information on the endodormancy break date because this information is very scarce. Here, we evaluated the efficiency of a set of phenological models to accurately predict the endodormancy break dates of three fruit trees. Our results show that models calibrated solely with budbreak dates usually do not accurately predict the endodormancy break date. Providing endodormancy break date for the model parameterization results in much more accurate prediction of this latter, with, however, a higher error than that on budbreak dates. Most importantly, we show that models not calibrated with endodormancy break dates can generate large discrepancies in forecasted budbreak dates when using climate scenarios as compared to models calibrated with endodormancy break dates. This discrepancy increases with mean annual temperature and is therefore the strongest after 2050 in the southernmost regions. Our results claim for the urgent need of massive measurements of endodormancy break dates in forest and fruit trees to yield more robust projections of phenological changes in a near future. © 2016 John Wiley & Sons Ltd.
Modeled PM2.5 removal by trees in ten U.S. cities and associated health effects
International Nuclear Information System (INIS)
Nowak, David J.; Hirabayashi, Satoshi; Bodine, Allison; Hoehn, Robert
2013-01-01
Urban particulate air pollution is a serious health issue. Trees within cities can remove fine particles from the atmosphere and consequently improve air quality and human health. Tree effects on PM 2.5 concentrations and human health are modeled for 10 U.S. cities. The total amount of PM 2.5 removed annually by trees varied from 4.7 tonnes in Syracuse to 64.5 tonnes in Atlanta, with annual values varying from $1.1 million in Syracuse to $60.1 million in New York City. Most of these values were from the effects of reducing human mortality. Mortality reductions were typically around 1 person yr −1 per city, but were as high as 7.6 people yr −1 in New York City. Average annual percent air quality improvement ranged between 0.05% in San Francisco and 0.24% in Atlanta. Understanding the impact of urban trees on air quality can lead to improved urban forest management strategies to sustain human health in cities. -- Highlights: •Paper provides the first broad-scale estimates of city-wide tree impacts on PM 2.5 . •Trees improve overall air quality by intercepting particulate matter. •Particle resuspension can lead to short-term increases in pollutant concentrations. •Urban trees produce substantial health improvements and values. -- Air pollution modeling reveals broad-scale impacts of pollution removal by urban trees on PM 2.5 concentrations and human health
Vanbeveren, D., Van Rensbergen, W., De Loore, C.
Massive stars are distributed all over the upper part of the Hertzsprung-Russell diagram according to their subsequent phases of stellar evolution from main sequence to supernova. Massive stars may either be single or they may be a component of a close binary. The observed single star/binary frequency is known only in a small part of the Galaxy. Whether this holds for the whole galaxy or for the whole cosmos is questionable and needs many more high quality observations. Massive star evolution depends critically on mass loss by stellar wind and this stellar wind mass loss may change dramatically when stars evolve from one phase to another. We start the book with a critical discussion of observations of the different types of massive stars, observations that are of fundamental importance in relation to stellar evolution, with special emphasis on mass loss by stellar wind. We update our knowledge of the physics that models the structure and evolution of massive single stars and we present new calculations. The conclusions resulting from a comparison between these calculations and observations are then used to study the evolution of massive binaries. This book provides our current knowledge of a great variety of massive binaries, and hence of a great variety of evolutionary phases. A large number of case studies illustrates the existence of these phases. Finally, we present the results of massive star population number synthesis, including the effect of binaries. The results indicate that neglecting them leads to a conclusion which may be far from reality. This book is written for researchers in massive star evolution. We hope that, after reading this book, university-level astrophysics students will become fascinated by the exciting world of the `Brightest Binaries'.
Bayesian parameter estimation and interpretation for an intermediate model of tree-ring width
Directory of Open Access Journals (Sweden)
S. E. Tolwinski-Ward
2013-07-01
Full Text Available We present a Bayesian model for estimating the parameters of the VS-Lite forward model of tree-ring width for a particular chronology and its local climatology. The scheme also provides information about the uncertainty of the parameter estimates, as well as the model error in representing the observed proxy time series. By inferring VS-Lite's parameters independently for synthetically generated ring-width series at several hundred sites across the United States, we show that the algorithm is skillful. We also infer optimal parameter values for modeling observed ring-width data at the same network of sites. The estimated parameter values covary in physical space, and their locations in multidimensional parameter space provide insight into the dominant climatic controls on modeled tree-ring growth at each site as well as the stability of those controls. The estimation procedure is useful for forward and inverse modeling studies using VS-Lite to quantify the full range of model uncertainty stemming from its parameterization.
Directory of Open Access Journals (Sweden)
Gang WU
2016-01-01
Full Text Available Objective To analyze the risk factors for prognosis in intracerebral hemorrhage using decision tree (classification and regression tree, CART model and logistic regression model. Methods CART model and logistic regression model were established according to the risk factors for prognosis of patients with cerebral hemorrhage. The differences in the results were compared between the two methods. Results Logistic regression analyses showed that hematoma volume (OR-value 0.953, initial Glasgow Coma Scale (GCS score (OR-value 1.210, pulmonary infection (OR-value 0.295, and basal ganglia hemorrhage (OR-value 0.336 were the risk factors for the prognosis of cerebral hemorrhage. The results of CART analysis showed that volume of hematoma and initial GCS score were the main factors affecting the prognosis of cerebral hemorrhage. The effects of two models on the prognosis of cerebral hemorrhage were similar (Z-value 0.402, P=0.688. Conclusions CART model has a similar value to that of logistic model in judging the prognosis of cerebral hemorrhage, and it is characterized by using transactional analysis between the risk factors, and it is more intuitive. DOI: 10.11855/j.issn.0577-7402.2015.12.13
Reconstruction of 3D tree stem models from low-cost terrestrial laser scanner data
Kelbe, Dave; Romanczyk, Paul; van Aardt, Jan; Cawse-Nicholson, Kerry
2013-05-01
With the development of increasingly advanced airborne sensing systems, there is a growing need to support sensor system design, modeling, and product-algorithm development with explicit 3D structural ground truth commensurate to the scale of acquisition. Terrestrial laser scanning is one such technique which could provide this structural information. Commercial instrumentation to suit this purpose has existed for some time now, but cost can be a prohibitive barrier for some applications. As such we recently developed a unique laser scanning system from readily-available components, supporting low cost, highly portable, and rapid measurement of below-canopy 3D forest structure. Tools were developed to automatically reconstruct tree stem models as an initial step towards virtual forest scene generation. The objective of this paper is to assess the potential of this hardware/algorithm suite to reconstruct 3D stem information for a single scan of a New England hardwood forest site. Detailed tree stem structure (e.g., taper, sweep, and lean) is recovered for trees of varying diameter, species, and range from the sensor. Absolute stem diameter retrieval accuracy is 12.5%, with a 4.5% overestimation bias likely due to the LiDAR beam divergence.
Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones
Rosli, A. D.; Hashim, H.; Khairuzzaman, N. A.; Mohd Sampian, A. F.; Baharudin, R.; Abdullah, N. E.; Sulaiman, M. S.; Kamaru'zzaman, M.
2015-11-01
This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water.
Capacitance Regression Modelling Analysis on Latex from Selected Rubber Tree Clones
International Nuclear Information System (INIS)
Rosli, A D; Baharudin, R; Hashim, H; Khairuzzaman, N A; Mohd Sampian, A F; Abdullah, N E; Kamaru'zzaman, M; Sulaiman, M S
2015-01-01
This paper investigates the capacitance regression modelling performance of latex for various rubber tree clones, namely clone 2002, 2008, 2014 and 3001. Conventionally, the rubber tree clones identification are based on observation towards tree features such as shape of leaf, trunk, branching habit and pattern of seeds texture. The former method requires expert persons and very time-consuming. Currently, there is no sensing device based on electrical properties that can be employed to measure different clones from latex samples. Hence, with a hypothesis that the dielectric constant of each clone varies, this paper discusses the development of a capacitance sensor via Capacitance Comparison Bridge (known as capacitance sensor) to measure an output voltage of different latex samples. The proposed sensor is initially tested with 30ml of latex sample prior to gradually addition of dilution water. The output voltage and capacitance obtained from the test are recorded and analyzed using Simple Linear Regression (SLR) model. This work outcome infers that latex clone of 2002 has produced the highest and reliable linear regression line with determination coefficient of 91.24%. In addition, the study also found that the capacitive elements in latex samples deteriorate if it is diluted with higher volume of water. (paper)
Energy Technology Data Exchange (ETDEWEB)
Roux, P
2005-12-15
This work deals with the modelling of dendritic solidification in binary mixtures. Large scale phenomena are represented by volume averaging of the local conservation equations. This method allows to rigorously derive the partial differential equations of averaged fields and the closure problems associated to the deviations. Such problems can be resolved numerically on periodic cells, representative of dendritic structures, in order to give a precise evaluation of macroscopic transfer coefficients (Drag coefficients, exchange coefficients, diffusion-dispersion tensors...). The method had already been applied for a model of columnar dendritic mushy zone and it is extended to the case of equiaxed dendritic solidification, where solid grains can move. The two-phase flow is modelled with an Eulerian-Eulerian approach and the novelty is to account for the dispersion of solid velocity through the kinetic agitation of the particles. A coupling of the two models is proposed thanks to an original adaptation of the columnar model, allowing for undercooling calculation: a solid-liquid interfacial area density is introduced and calculated. At last, direct numerical simulations of crystal growth are proposed with a diffuse interface method for a representation of local phenomena. (author)