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- Methodology article
- Open Access
A cooperative strategy for parameter estimation in large scale systems biology models
- Alejandro F Villaverde1,
- Jose A Egea2 and
- Julio R Banga1Email author
© Villaverde et al.; licensee BioMed Central Ltd. 2012
- Received: 21 February 2012
- Accepted: 11 June 2012
- Published: 22 June 2012
Mathematical models play a key role in systems biology: they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Model calibration consists of finding the parameters that give the best fit to a set of experimental data, which entails minimizing a cost function that measures the goodness of this fit. Most mathematical models in systems biology present three characteristics which make this problem very difficult to solve: they are highly non-linear, they have a large number of parameters to be estimated, and the information content of the available experimental data is frequently scarce. Hence, there is a need for global optimization methods capable of solving this problem efficiently.
A new approach for parameter estimation of large scale models, called Cooperative Enhanced Scatter Search (CeSS), is presented. Its key feature is the cooperation between different programs ("threads") that run in parallel in different processors. Each thread implements a state of the art metaheuristic, the enhanced Scatter Search algorithm (eSS). Cooperation, meaning information sharing between threads, modifies the systemic properties of the algorithm and allows to speed up performance. Two parameter estimation problems involving models related with the central carbon metabolism of E. coli which include different regulatory levels (metabolic and transcriptional) are used as case studies. The performance and capabilities of the method are also evaluated using benchmark problems of large-scale global optimization, with excellent results.
The cooperative CeSS strategy is a general purpose technique that can be applied to any model calibration problem. Its capability has been demonstrated by calibrating two large-scale models of different characteristics, improving the performance of previously existing methods in both cases. The cooperative metaheuristic presented here can be easily extended to incorporate other global and local search solvers and specific structural information for particular classes of problems.
- Local Search
- Differential Evolution
- Cooperative Strategy
- Flux Balance Analysis
- Scatter Search
The aim of systems biology is to understand the organization of complex biological systems by combining experimental data with mathematical modeling and advanced computational techniques. Mathematical models play a key role, since–among other functions–they summarize the currently available knowledge in a way that allows to make experimentally verifiable predictions. Due to the increasing amount of "omic" data available from high throughput techniques, there is a need for large-scale model building methods.
Model building is a complex task that usually follows an iterative process[1–7]. It begins with the definition of the purpose of the model, this is, with the determination of the questions that the model should be able to answer. This conditions the modeling framework and the information that must be included in the model. The next step is to propose a mathematical structure with the necessary level of detail, which will in general include a number of unknown, non-measurable parameters. An estimation of these parameters is needed in order to obtain quantitative predictions; this is the next step, which is commonly known as parameter estimation or identification, data fitting, or model calibration[1, 4–6]. The final step is model validation, which entails testing the model with new data; if this reveals modeling errors, the process should be iteratively repeated.
In recent years a number of approaches to large-scale kinetic modelling have been presented. Jamshidi and Palsson[8] presented a procedure to construct dynamic network models in a scalable way using metabolomic data mapped onto existing stoichiometric models, thus incorporating kinetics and regulation into those stoichiometric models. Liebermeister and Klipp[9, 10] introduced a simplified, general rate law named convenience kinetics. It can be derived from a random-order enzyme mechanism, and it may be used to obtain a dynamical model from a biochemical network. The resulting model has plausible biological properties. More recently, the same authors proposed five modular rate laws[11], characterized by different formulae of their denominators, as a way of parameterizing metabolic network models. Tran et al[12] advocated the use of an ensemble of dynamic models. The models in the ensemble share the same mechanistic framework, span the space of all kinetics allowable by thermodynamics, and reach the same steady state. The size of the ensemble is reduced by acquiring data, converging to a smaller and more predictive set of models, which are able to describe relevant phenotypes upon enzyme perturbations. The well-known flux balance analysis method (FBA) has been widely used for large-scale analysis of metabolic networks. In[13] it was extended in order to incorporate transcriptional regulation (regulatory FBA, or rFBA); further developments included also signal transduction networks (integrated FBA or iFBA[14], and integrated dynamic FBA or idFBA[15]). Another integration of FBA with kinetic information was carried out by Smallbone et al. In[16] they presented a method for building a parameterized genome-scale kinetic model of a metabolic network, based solely on the knowledge of reaction stoichiometries. Fluxes were estimated by flux balance analysis and allowed to vary dynamically according to linlog kinetics. This method was applied[17] to a model of S. cerevisiae comprising 956 metabolic reactions and 820 metabolites. Kotte et al[18] modeled the coupling of enzymatic and transcriptional regulation of E. coli's central metabolism using differential equations. The resulting medium-scale model is able to explain, from the interplay of known interactions, the adjustments of metabolic operation between glycolytic and gluconeogenic carbon sources. Another interesting contribution to the problem of building large-scale mathematical models of biological systems can be found in[19]. It extends an ordinary differential equation (ODE) model of ErbB signaling pathways to include 28 proteins, 499 ODEs, 828 reactions, and 229 parameters. The parameter space size is reduced to 75, following an initial sensitivity analysis based on estimates of nominal parameter values. Parameter estimation is then carried out by means of extensive computations using an stochastic method (simulated annealing).
- 1.
They are highly non-linear, which creates multimodality, so standard local methods (e.g. Levenberg-Marquardt or Gauss-Newton) converge to local solutions. This must be overcome with the use of global methods capable of finding the optimum in a rugged landscape.
- 2.
There is large number of parameters to be estimated. This is an especially problematic issue, since the necessary computational effort increases very rapidly with the problem size. The increase may be exponential, thus preventing methods that work well for a limited number of parameters from being applied to realistically sized problems. This means that global deterministic methods, which guarantee finding the global optimum, fail to provide the solution in reasonable computing times. Hence, stochastic methods must be used instead.
- 3.
The information content of the available experimental data is frequently scarce, which might cause an identifiability problem (i.e., different combinations of parameter values may produce similar model outputs). An example illustrating this point can be found in the aforementioned work of Chen et al [19], where the estimation of parameters yielded the result that the model is non-identifiable.
Due to these difficulties, no full and proper model calibration has been performed so far in the large-scale kinetic models referenced above. In many cases, a large subset of parameters were taken, where available, from previous models or databases, but this procedure, although practical for some aplications, is not equivalent to a proper calibration of the large-scale model. Our main objective in this paper it to present a novel metaheuristic which exploits cooperative parallelism in order to surmount the difficulties mentioned above. Parallel implementations of global optimization methods have been used recently in systems biology (see[21] and references therein). Here we have improved this concept by incorporating cooperation of individual search threads.
The novelty of our approach has the following two main pillars:
The use of an efficient global optimization method for solving large-scale parameter estimation problems, based on extensions of the scatter search metaheuristic[22–25].
A parallel implementation of the algorithm incorporating a cooperative strategy, which means that there is an exchange of information between a set of individual optimization programs, or threads, running in parallel. As a result, this cooperation not only speeds up the algorithm, but also alters its systemic properties, thus yielding performance improvements more than proportional to the increase in computing power.
The capabilities of these novel methods are illustrated considering two case studies based on E. coli:
This paper is structured as follows: after the presentation of the problem statement, we discuss the need of global optimization methods, and then we present a cooperative parallel method which is able to handle the challenges arising from this class of problems. Results for two different case studies are then presented and discussed, finally arriving to a set of conclusions.
Problem statement
Given a model of a nonlinear dynamic system and a set of experimental data, the parameter estimation problem consists of finding the vector of decision variables p(unknown model parameters) that minimizes a cost function that measures the goodness of the fit of the model predictions with respect to the data, subject to a number of constraints. The output state variables that are measured experimentally are called observables.
where n ε is the number of experiments, is the number of observables per experiment, and is the number of samples per observable per experiment. The measured data will be denoted as and the corresponding model predictions will be denoted as (p). Finally, W is a scaling matrix used to balance the contributions of the observables (usually by scaling each temporal series with respect to its maximum value).
where g is the observation function, x is the vector of state variables with initial conditions x0, f is the set of differential and algebraic equality constraints describing the system dynamics (that is, the nonlinear process model), h eq and h in are equality and inequality constraints that express additional requirements for the system performance, and p L and p U are lower and upper bounds for the parameter vector p.
As was mentioned in the Background section, in systems biology models this problem is often multimodal (nonconvex), due to the nonlinear and constrained nature of the system dynamics. Hence, standard local methods usually fail to obtain the global optimum. As an alternative, one may choose a multistart strategy, where a local method is used repeatedly, starting from a number of different initial guesses for the parameters. However, this approach is usually not efficient for realistic applications, and global optimization (GO) techniques, such as the ones presented in the next section, need to be used instead.
To efficiently solve the calibration problem there is a need of global optimization methods whose performance does not deteriorate when the number of parameters to be estimated is very large (as it occurs with most methods). Global optimization methods can be divided into deterministic and stochastic. Deterministic global optimization methods guarantee that the solution is the global optimum, but the computational effort they require can make them unaffordable for large-scale problems. Stochastic global optimization methods, on the other hand, do not guarantee the global optimality of the solution, but they are frequently capable of finding excellent solutions in reasonable computation times. A particularly efficient class of stochastic global optimization methods are the so-called metaheuristic approaches, which combine mechanisms for exploring the search space and exploiting previously obtained knowledge. Here we propose a method, Cooperative enhanced Scatter Search (CeSS), based on extensions and cooperative parallelization of the scatter search metaheuristic[22–25].
Global optimization via enhanced scatter search
Scatter search can be classified as an evolutionary optimization method which, like many other metaheuristics, arose in the context of integer optimization[26]. Several adaptations to continuous problems have been developed in recent years. The application of the method to parameter estimation in systems biology problems has provided excellent results[22].
Scatter search is a population-based algorithm which, compared with other methods like genetic algorithms, makes use of a low number of population members, called "Reference Set" (RefSet) in this context. Besides, scatter search includes the so-called "improvement method" which usually consists in a local search to speed-up the convergence to optimal solutions.
The method starts by creating an initial population of diverse solutions within the search space (Figure1.a). From them, the best solutions in terms of quality are selected to create the initial RefSet (in red in Figure1.b). The rest of solutions in the RefSet are chosen randomly (in green in Figure1.b), although in some advanced implementations they may be chosen following a criterion of maximum diversity to cover a broader area of the search space. Once the RefSet solutions have been selected, the remaining diverse solutions generated in the first step are deleted and the so-called "subset generation method" starts. It consists in combining sets of RefSet solutions to create new ones. In our scheme, we combine every solution in the RefSet with the other RefSet by generating hyper-rectangles defined by their relative position and distance, and creating new solutions inside them. This step is illustrated in Figure1.c. Each RefSet member will create one hyper-rectangle with every other RefSet member, thus generating a number of b−1 new solutions (being b the RefSet size) per each RefSet member. After this procedure, all the RefSet members have a set of offspring solutions around them covering different distances and directions (Figure1.d). If the best offspring solution outperforms the parent solution (which is the case of Figure1.d with the best offspring solution represented as a star), the replacement (or update) is carried out. Otherwise, the same RefSet member will stay in the population in the next iteration. Although the procedure is illustrated for just one RefSet member, the same scheme applies for every solution in the RefSet. After the RefSet update, the algorithm applied the "solution combination method" again, repeating the process until a stop criterion is met.
In this work, a novel extended implementation of the enhanced scatter search metaheuristic (eSS)[24, 25], has been used. Its pseudocode is shown in Algorithm 1.
Algorithm 1
Basic pseudocode of eSS
Set parameters: dim_refset, local.n 2, balance, ndiverse
Initialize n stuck , neval
Create set of ndiverse solutions
Generate initial RefSet with dim_refset solutions with high quality and random elements
Sort RefSet by quality [x1,x2,…,x dim_refset ]so that f(x i ) ≤ f(x j ) where i,j∈[1,2,…,dim_refset] and i < j
if max with i < j then
Replace x j by a random solution
end if
for i = 1 to dim_refset do
Combine x i with the rest of population members to generate a set of dim_refset new solutions,
offspring i
best solution in offspring i
if outperforms x i then
Label x i
xtemp = x i
improvement = 1
∧ = 1
while do
Create a new solution, xnew, in the hyper-rectangle defined by
improvement = improvement + 1
if improvement = 2 then
∧ = ∧/2
improvement = 0
end if
end while
end if
end for
offspring= with n = dim_refset
if neval ≥ local.n 2 and at least one local solution has been found then
Sort offspring solutions by quality [x1,1,x2,1,…,xm,1] where m = n(n−1) and f(xi,1) ≤ f(xj,1) where i,j∈[1,2,…,m] and i < j
Compute the minimum distance between each element i ∈ [1,2,…,m] in offspring and all the local optima found so far, d(x i )
Sort offspring solutions by diversity [x1,2,x2,2,…,xm,2] with d(xi,2) ≥ d(xj,2) where i,j∈[1,2,…,m] and i < j
Choose z as the offspring member balancing quality and diversity according to balance
Perform a local search from z to obtain z∗
if z∗ is a new local optimum then
Update list of found local optima adding z∗
end if
if f(z∗) < fbest then
Update xbest, fbest
end if
neval = 0
end if
neval = neval + function evaluations of current iteration
Replace labeled population members by their corresponding and reset their corresponding n stuck (i)
Add one unit to the corresponding n stuck (j) of the not labeled population members
if any of the n stuck values > nchange then
Replace those population members by random solutions and reset their n stuck values
end if
until stopping criterion is met
Apply final local search over xbest and update it
The innovative mechanisms implemented in different parts of the method as well as the appropriate local search selection, make the algorithm specially suitable for solving large-scale optimization problems. These mechanisms, which address the most important question in global optimization (i.e., the balance between intensificacion, or local search, and diversification, or global search) are depicted in the following points:
Population-based algorithms with a large population size can become inefficient due to the large amount of function evaluations they perform in each iteration. On the other hand, if the population size is too small, the algorithm may converge prematurely to suboptimal solutions. The enhanced scatter search method uses a small population size, even for large-scale problems, but allowing more search directions than in classical scatter search designs thanks to the hyper-rectangle-based combination scheme. This does not increase the number of evaluations per iteration while preserving the diversity in the search.
Another key aspect in population-based algorithms is the population update scheme. (μ + λ) strategies[27] (i.e., members of the following population will be selected among the set of solutions including old population members and new offspring solutions) may tend to prematurely stagnate the population in suboptimal solutions. (μ λ) strategies (i.e., members of the following population will be selected among the set of solutions including only new offspring solutions) may need a high number of function evaluations to converge. On the other hand a (1 + 1) strategy applied to every population member as the one depicted in Figures1.(a-d) can take the advantages of both mechanisms. This is the strategy used in eSS and, again, provides a good balance between intensification (i.e., local search) and diversification (i.e., global search).
The specific intensification mechanisms are crucial in large scale optimization in order to reduce the computational times as much as possible. eSS implements an intensification mechanism already in the global phase, which exploits the promising directions defined by a pair of solutions in the RefSet. Besides, the use of a local search method to accelerate the convergence is mandatory in this type of applications. Gradient-based methods are the most widely used local methods. However, for dynamic problems they might be inefficient due to some characteristics of this type of problems (see[28] for more details). Furthermore, the calculation of the numerical sensitivities carried out by these methods may become unaffordable when the problem dimension is too high. A heuristic local search method seems to be the most convenient choice when dealing with large-scale problems because, even if the local convergence might not be ensured, avoiding the calculation of sensitivities or search directions may save a large amount of calculation time. For this reason, and after extensive initial tests, we have selected a heuristic method known as "Dynamic Hill Climbing"[29], available in the eSS framework. This method provided the best results for the problems tested.
Even if intensification strategies should be favoured in large-scale optimization due to the limited computational time usually available in real applications, diversification strategies should not be neglected because stagnation of the search may appear even in early stages of the process. In this regard, eSS implements diversification strategies which make use of memory to infer whether a solution is stagnated in a local optimum or if it is too close to previously found solutions. When these solutions are identified, they are automatically replaced to avoid spending computational effort searching in areas already explored.
Cooperative optimization
A common way of reducing the computational cost of a given algorithm is to parallelize it. This entails performing several of its calculations simultaneously in different processors. Except for some special cases, which are usually called "embarrasingly parallel", it is not trivial to separate the problem into parallel tasks. Here we are interested in the parallelization of a metaheuristic optimization algorithm, the enhanced scatter search method described in the previous section.
Before we describe the proposed methodology, we clarify the use of a few words in order to avoid confusion. We refer to a context where there are a number of processors available for computing, which can work simultaneously (in parallel). All of the processors are assumed to be physically identical, that is, they have the same hardware characteristics. A program running in a processor is called thread; both terms are interchangeable. In our methodology we use a master processor, with the task of coordinating the remaining processors (slaves). All of the slave processors implement the same program, which means they perform similar calculations, using different data sets and different settings.
There are not many examples of research in the area of parallelization of metaheuristics exploiting cooperation in the way we present here. In[30] three different parallelizations of the scatter search were proposed and compared. In the first one, each local search was parallelized. In the second one, several local searches were carried out in parallel. In these two cases it was possible to reduce the computational time. A third option was to run the algorithm for different populations in parallel, but without any communication between threads.
More recently[31] a more ambitious approach was presented, where different kinds of metaheuristics were combined in order to profit from their complementary advantages. Information was shared between algorithms and it was dynamically tuned, so the most succesful algorithms were allowed to share more information. For a detailed review of the state of the art in parallelization of metaheuristics, see[32].
Sharing information can be seen as a way of cooperating. Such cooperation produces more than just speed-up: it can change the systemic properties of an algorithm and therefore its macroscopic behaviour. This was acknowledged in[33], where four parameters that may affect this behaviour were identified: (i) information gathered and made available for sharing; (ii) identification of programs that share information; (iii) the frequency of information sharing among the sequential programs; and (iv) the number of concurrent programs.
- 1.
Information available for sharing: the best solution found and, optionally, the reference set (RefSet), which contains information about the diversity of solutions.
- 2.
Threads that share information: all of them.
- 3.
Frequency of information sharing: the threads exchange information at a fixed interval τ.
- 4.
Number of concurrent programs: η.
Each of the η threads has a fixed degree of "aggressiveness". "Conservative" threads make emphasis on diversification (global search) and are used for increasing the probabilities of finding a feasible solution, even if the parameter space is "rugged" or weakly structured. "Aggressive" threads make emphasis on intensification (local search) and speed up the calculations in "smoother" areas. Please note that both conservative and agressive threads should be able to locate the globally optimal solution of the class of problems considered here, but their relative efficiency will vary depending on the region of the parameter space where the individual threads are operating. In this way, we achieve a synergistic gain. Communication, which takes place at fixed time intervals, enables each thread to benefit from the knowledge gathered by the others. This knowledge may include not only information about the best solution found so far, but also about the sets of diverse parameter vectors that may be worth trying for improving the solution. Thus this strategy has several degrees of freedom that have to be fixed: the time between communication (τ), the number of threads (η), and the strategy adopted by each thread (Ψ). These adjustments should be chosen carefully depending on the particular problem we want to solve. In the following lines we give some guidelines for doing this.
Time between information sharing, τ
where n eval is the maximum number of function evaluations allowed between cooperation instants. Therefore, τ, as defined above, is a dimensionless and machine-independent parameter that sets the duration of the intervals between information sharing. The logarithm is used for the convenience of avoiding very large numbers. For all the problems considered in this study, we have empirically found that a value in the interval 2.5 < τ < 3.5, with a default value of 2.5, results in a good trade-off between efficiency and robustness of the cooperative strategy.
Number of concurrent threads, η
As η increases, the expected speed up increases too. However, this increase cannot grow in a linear way for an arbitrarily large number of threads, due to a number of reasons. One reason is that, as the number of threads increases, so does the communication overhead. More importantly, the risk of overlapping - that is, carrying out similar searches in different threads - increases too due to the relatively small size of the RefSet. Hence, when the number of threads is very large, the resulting speed up is smaller than the increase in computational effort. For the problems considered here, we have empirically found that an η = 10 led to good results and thus can be recommended as a default value.
Settings (strategy) for each thread, Ψ
For cooperation to be efficient, every thread running in parallel must perform different calculations. Due to the random nature of metaheuristic algorithms, this can be achieved simply by choosing different random initializations, or "seeds", for each thread. This results first in different sets of initial guesses, and subsequently in the exploration of different points of the search space. However, this is not the only difference that may be made between threads: we can also select a different behaviour (more or less aggressive) for each of the threads. An "aggressive" thread performs frequent local searches, trying to refine the solution very quickly, and keeps a small reference set of solutions. This means that it will perform well in problems with parameter spaces that have a smooth shape. "Conservative" threads, on the other hand, have a large reference set and perform local searches only sporadically. This means that they spend more time combining parameter vectors and exploring the different regions of the parameter space. Thus, they are more robust, and hence appropriate, for problems with rugged parameter spaces. Since the exact nature of the problem to consider is always unknown, it is advisable to choose a range of settings that yields conservative, aggressive, and intermediate threads. For the eSS algorithm this can be obtained by tuning the following settings:
Number of elements in the Reference Set (dim_refset).
Minimum number of iterations of the eSS algorithm between two local searches (local.n2).
Balance between intensification and diversification in the selection of initial points for the local searches (balance).
Number of diverse solutions initially generated (ndiverse).
All these settings have qualitatively the same influence on the algorithm's behaviour: if they are large, they lead to conservative threads; if they are small, to aggressive threads. The four parameters that define the degree of aggressiveness of each of the η threads can be stored in an array Ψη×4. By default, we recommend to use a broad spectrum of aggressiveness using the default values 0.5·n par < dim _refset < 20·n par ; 0 < local.n 2 < 100; 0 < balance < 0.5; and 5·n par < ndiverse < 20·n par .
Algorithm 2
Basic pseudocode of the cooperative strategy
MASTER, PROCESSOR 0: Initialization
Set parameters that are common for all threads: τ, η, n iters
Set array of aggressiveness parameters: Ψη×4 = {dim_refsetη×1,ndiverseη×1,local.n2η×1,balanceη×1}
Initialize global reference set array: Globa l ref = []
for i = 1 to n iters do
for j = 1 to η do
SLAVE, PROCESSOR j (concurrent processing): run optimization according to Algorithm 1
(Thread j uses aggressiveness settings vector Ψ{j,:} and initial points Globa l ref )
end for
if CPUtime ≥ τ then
for j = 1 to η do
Read results of thread j
if ref j ∉ Global ref then
Global ref = [Global ref ,ref j ]
end if
end for
end if
end for
Final solution = best solution in Global ref
Results and discussion
As a preliminary validation, we first applied CeSS to a problem taken from the competition on Large Scale Global Optimization of the 2012 IEEE World Congress on Computational Intelligence[34]. Testing the performance of our method with this problem has two advantages: first, the benchmark is well known in the large-scale global optimization community, which facilitates the critical examination of the results; and second, the objective function selected from the benchmark has a smaller computational cost than the ones from our models (despite having one thousand parameters), which allows to carry out more extensive tests in less time. The results are shown in the supplementary material, see Additional file1. From them it is concluded that eSS performs well with the benchmark problem, and that its performance is considerably improved by using its cooperative version, CeSS. This confirms the validity of the proposed approach for large-scale global optimization problems.
Overview of model features
Model 1
Model 2
Metabolic, transcriptional
Static / Dynamic
Model 1: E. coli CCM
where u is an enzyme level (mmol),, and are reactant constants (mM), and k± are turnover rates (s−1). The CM rate law resembles the convenience kinetics, with a slight difference for molecularities m± ≠ 1 (in convenience kinetics, the denominator term for product C would read).
The resulting model has 918 parameters: internal metabolites concentrations; activation, inhibition, and Michaelis-Menten constants; and velocity and equilibrium constants. Their values are given in the supplementary material, see Additional file2. They are estimated by least squares minimization of the difference between the model predictions and artificially generated data regarding internal metabolic concentrations (49) and fluxes (66), yielding a state vector with 115 elements.
Suspecting that a more sophisticated method may be able to find a better solution, we test our enhanced Scatter Search (eSS) algorithm. Since the multistart calculations were carried out in a single processor, with a total running time of 10 days, it is fair to compare the results with those obtained by 10 processors in one day. We thus select 10 different settings for the eSS algorithm and launch the corresponding 10 optimizations. Since eSS provides the possibility of launching local searches, we select the local method that yields best results with the multistart procedure, DHC. After one day, the best objective function value achieved is f best = 7.86, which represents a reduction of 73% with respect to what was obtained with a multistart of local searches.
Model 2: E. coli metabolic model including enzymatic and transcriptional regulation
The model calibrated in the previous subsection was purely metabolic. Here we consider a previously published E. coli model[18] that also takes into account the enzymatic and transcriptional regulation layer. It consists of 47 ODEs and 193 parameters (affinity constants, specific activities, Hill coefficients, growth rates, expression rates, etc), of which 178 are considered unknown and need to be estimated. We have reformulated the model to use it in an optimization context, where the objective function to be minimized consists of the difference between the simulated concentration profiles obtained with the nominal and the estimated parameters. Upper and lower bounds for the parameters are fixed to values 10 times larger and 10 times smaller than the nominal, except for the Hill coefficients, which are assumed to be between 0.5 and 4. More information is included as supplementary material, see Additional file3.
This model was created to reproduce the way in which E. coli adapts to changing carbon sources. With this aim, it is subjected to a sequence of three consecutive environments, where the carbon source is first glucose, then acetate, and finally a mixture of both. Under these conditions, the 47 concentration profiles are sampled every 1000 seconds, for a total of 162 time points (45 hours). Therefore the overall number of available samples is 47 × 162 = 7614. The equations are integrated using LSODE (Livermore Solver for Ordinary Differential Equations)[36], which is suited for stiff systems. Integrating these equations is a computationally expensive task; one evaluation of the objective function takes several seconds.
It must be noted that in[18] a divide-and-conquer approach was adopted for estimating the parameter values of the rate equations. In this approach, the large-scale optimization problem is divided into a set of small subproblems, where only a few parameters are estimated at a time. This allows to reduce the complexity of the task and consequently the computation times. However, it is an ad hoc procedure that cannot be applied to most systems biology problems. Here we adopt a general purpose, large-scale global optimization approach that does not require any special structure of the model equations.
Next, the enhanced Scatter Search (eSS) algorithm is tested. For this particular problem it was decided to use eSS with DHC as the local solver because, once again, it offers the best balance between quality of the solution and computational time. After selecting 10 different settings and letting the corresponding 10 optimizations run for 24 hours, the best objective function value achieved is f best = 2.37·102 and the worst is f best = 1.48·103. Thus the eSS algorithm clearly outperforms any local method.
Finally, we would like to comment on the default values recommended for the search parameters of the cooperative strategy. The main potential disadvantage of using such default settings for a new problem is that the method could perform worse in two extreme situations: easy (mildly non-convex) problems, where a simple multi-start local method could perform very well, and extremely hard (highly non-convex problems) where there is no structure at all and local searches do not help. Since for each new problem we do not have any a priori information about the topology of the search space, we simply recommend a broad spectrum of values for the aggressiveness of the threads, so even in the extreme situations the cooperative strategy would be able to solve the problem. Of course, any a posteriori information about the topology, after a few runs with the default settings, can be exploited by tuning ψ. This reasoning applies for the case of new arbitrary problems, but we should add that for the particular large-scale parameter estimation problems considered above, the default recommended values have shown a good performance.
Typically, systems biology models have a large number of parameters and are highly nonlinear. Furthermore, the information content of the available experimental data is frequently scarce. As a consequence, it is hard to find the set of parameter values that gives the best fit to experimental data. This task, known as model calibration, is commonly formulated as an optimization problem, which in these cases must be solved with global optimization techniques.
Here we have presented a new method for solving this problem, called Cooperative enhanced Scatter Search (CeSS), which is specifically designed to profit from a parallel environment with several processors. Each of the processors executes a program (or "thread") which implements the enhanced Scatter Search (eSS) algorithm[24, 25]. This is a state of the art metaheuristic capable of competing succesfully with other global optimization methods. The key feature of the strategy presented here is the cooperation between threads, which means that they exchange information at certain fixed instants. This information consists of the reference set of solutions they have found so far; it depends on the best solution found, the shape of the solution space, and the settings of each algorithm.
We have tested this strategy with two large-scale E. coli models of different sizes and characteristics. The first one models the central carbon metabolism (CCM) using a recently proposed common modular rate law[11]. The second is a previously published model that combines metabolism with a transcriptional regulatory layer[18]. In both cases the presented method clearly outperformed several state of the art techniques. The performance and capabilities of the method have also been evaluated using benchmark problems of large-scale global optimization, with excellent results.
The results for the cooperative strategy presented here shows how cooperation of individual parallel search threads modifies the systemic properties of the individual algorithms, improving its performance and outperforming other competitive methods. Importantly, it is a general purpose framework that can be easily applied to any model calibration problem. Furthermore, the underlying cooperative parallel mechanism is relatively simple and can be extended to incorporate other global and local search solvers and specific structural information for particular classes of problems.
We are grateful to the financial aid received from the EU through project "BioPreDyn" (EC FP7-KBBE-2011-5 Grant number 289434), from Ministerio de Economía y Competitividad (and the FEDER) through the projects "MultiScales" (DPI2011-28112-C04-03 and DPI2011-28112-C04-04), and from the CSIC intramural project "BioREDES" (PIE-201170E018). We acknowledge support of the publication fee by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). We thank Wolfram Liebermeister for supplying the metabolic model of E. coli ("Model 1").
Authors' Affiliations
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This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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I'm a developer / jack of all trades working for BoingBoing.net and living in San Francisco. I'm making a book from my great-grandfather's WWI photos, backed by Kickstarter. If you met me, we probably talked about one of these things: my wwi photo book my smiley faces my gif collection my photos
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LOS ANGELES (CNS) – Gov. Jerry Brown, House Minority Leader Nancy Pelosi and Los Angeles Mayor Eric Garcetti are among the scheduled speakers today at the California Democratic Party Convention at the Los Angeles Convention Center.
Other planned speakers during the convention's general sessions include Lt. Gov. Gavin Newsom, Attorney General Kamala Harris and Maryland Gov. Martin O'Malley.
Rep. Keith Ellison, D-Minn., is set to speak at a luncheon, and San Antonio, Texas Mayor Julian Castro and Rep. Barbara Lee, D-Oakland, at a dinner.
Various interest-group caucuses will also be held today.
Garcetti will discuss "how Democrats get things done, including water conservation during the drought, building new rail lines throughout our city, upgrading our terminals at" Los Angeles International Airport and "creating 10,000 summer jobs for L.A. youth," aide Jeff Millman said.
Peace and Freedom Party gubernatorial candidate Cindy Sheehan and her supporters plan to picket outside the convention for three hours, protesting a variety of Brown's policies that she said have enriched "banks and the 1 percent," while the state's prisons are filled and "California's schools continue to fail."
Delegates will finalize statewide, congressional and legislative endorsements and adopt the 2014 party platform when the three-day convention concludes Sunday.
More than 3,000 delegates, officials, exhibitors and observers are expected to attend.
O'Malley is expected to recount his accomplishments as mayor of Baltimore from 1999 to 2007 and governor since 2007, including increasing spending on education and infrastructure amid budget cuts and working to make Maryland 'a more open and welcome state" by supporting same-sex marriage and signing a bill making the children of immigrants in the nation without legal authorization eligible for in-state college tuition under certain conditions, according to Lis Smith, a communications adviser to O'Malley's political action committee, O'Say Can You See PAC.
O'Malley, who has said he is looking at the possibility of running for the 2016 Democratic presidential nomination, will also hold private meetings with "various stakeholders in California Democratic politics," while in Southern California, Smith said.


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Homeschooling in Bulgaria - Guide for Expats
Child Tracking: The Crisis in Bulgaria
Homeschooling Legalized; Strings Attached
Proposed Bill May End Decade-Long Effort to Legalize Homeschooling
Homeschool Wins IT Competition; Spurs National Debate
Homeschool Conferences in Bulgaria: Eight Years Strong
Bulgarian National TV Network Airs Documentary about Home Education
I am a Homeschooler
Bulgaria: NGOs Attack the Freedom of Families to Homeschool
Officials Cease Prosecution
Pastor Charged with Criminal Child Abuse Over Home Education
Bulgaria a Battlefield for Anti-Family Social Engineering
Bulgaria: Children's Rights vs. Parental Rights?
Lifework Forum's Mission in Bulgaria
International Homeschooling—Watch Video from a Dozen Countries
Homeschool Leader Interviews
Homeschooling Promotes Social Integration
Bulgaria: Homeschoolers will Change the World
The Forgotten Education
Homeschool Pioneers in Bulgaria: Endurance through Adversity
Bulgarian Newspaper Highlights Homeschooling
Bulgarian Homeschoolers Face Resistance
Education Bill Would Criminalize Homeschooling
Bulgaria Needs Homeschool Freedom
Compulsory Education Ages: 6–16 years (classes - preschool and then 1st to 8th grade total 9 years)
Legal Status: Homeschooling is prohibited. Only the children with special (physical or mental) educational needs can study at home. They still must follow the government's educational programs closely and consecutively, and must be integrated with a registered legal public or private school.
Number of Homeschoolers: Less than 100 families
Bulgarian Homeschool Association
22 Ianko Todorov str., ap.2
Bulgaria Needs:
1. Books—new or second hand—including curriculum, teacher aids, Christian literature for kids, and other materials that will be good for homeschooling.
2. Other homeschoolers who could share about homeschooling.
3. Assistance to get rights for publishing homeschooling books and materials in Bulgarian. In Bulgaria we have homeschooling moms who know English and can translate books and articles into Bulgarian.
Last updated January 1, 2016


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In October I filed a new claim for Sleep Apnea, GERD, PTSD, and convulsive tic. I was never diagnosed in service of any of these conditions other than getting heartburn pills prescribed while in the service to combat my reflux on deployment. In November I received a decision letter and everything was denied service connection with PTSD Deferred. I was scheduled for a GERD C&P exam December 27th where a Nurse Practioner was my examiner. The exam lasted 5 minutes and I am now currently pending decision approval. Is this normal of the VA to deny service connection then back a step and give an exam? I still haven't heard anything about a PTSD exam. Does anyone have any similar experiences with a denial of service connection then a C&P exam?
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Post in My VA claim estimated completion date changed to 05/03/2019- 04/30/2019 Good sign or bad ?
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Do-it-yourself remedies, such as holding the photo over a simmering pot or prying it off with dental floss, don't workand usually lead to even more damage. "Photos stuck to glass are almost always a lost cause because removing the photo usually tears the emulsion away from the photographic paper," says Heather Tudhope, a Denver-based photographic conservator. A professional conservator might be able to reattach the emulsionthe coating that contains the imagebut your photo won't look the same.
The best course of action is to make a good copy of your stuck photo. Scan it glass-side-down on a flatbed scanner at a high resolution, then print it onto photographic paper using a photo printer. If you don't have a scanner, use a do-it-yourself kiosk at a large retailers such as Target or Walgreen's.
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In its later past, the Phoenix Wright: Ace Attorney – Spirit of Justice for Nintendo 3ds arrangement has moved far from utilizing mystery and more fantastical components in its plot. That all progressions with Spirit of Justice, in which you'll wind up addressing exactly how grounded the underlying foundations of arrangement's legend and myth are. Brandishing a cast of recognizable appearances and a modest bunch of convincing new ones, Spirit of Phoenix Wright: Ace Attorney – Spirit of Justice for Nintendo 3ds might be the most included Phoenix Wright title as of late, with complex homicide trials that come full circle in you feeling both brilliant and mitigated. It's reviving to see the arrangement go full-powerful this time around and venture up its trouble, a feedback of the last amusement. There are a couple of minutes where the pressure and dramatization slack on account of some characterless court jokes, however this is little potatoes contrasted with the wonderfully made web of interest covering whatever is left of the experience.
Soul of Justice opens with Phoenix Wright: Ace Attorney – Spirit of Justice for Nintendo 3ds on furlough in Khura'in, a flighty nation without detachment of chapel and state. Here, liable verdicts are controlled by conjuring the last recollections of homicide casualties, and there are no resistance lawyers to talk about on account of a law binds legal counselors' destinies to their customers. In the wake of consenting to shield his visit guide against a homicide accusation and a keep running in with Rayfa, the hot-headed princess of Khura'in, Phoenix and whatever is left of the Wright Anything Agency are cleared up in the tide of unrest undermining to surpass the nation. A bright cast of natural countenances from past recreations and crackpot newcomers round out the enterprise, which takes Phoenix and organization over the world and back on a mission to expose (or demonstrate) myths and stem the tide of war.
You invest your energy in Phoenix Wright: Ace Attorney – Spirit of Justice for Nintendo 3ds of Justice doing one of two things: exploring wrongdoing scenes or rationally competing in court. Examination segments take prompts from point and snap experiences; utilizing the 3DS touchscreen and stylus, you indicate objects in the earth for a nearer examination. In some cases you'll find the opportunity to watch questions all the more nearly by utilizing the touchscreen to turn and zoom in on better points of interest. Along these lines you'll discover shrouded pieces of information and fingerprints, little things with huge potential for finding the genuine guilty party. Periodically characters associated with the occasions will show up, and you'll get the chance to meeting them to uncover more subtle elements of the wrongdoing.
Filtering through a wrongdoing scene doesn't simply yield certainties around a case, be that as it may. In this circumstances, you'll frequently start some engaging chitchat between characters. Junior legal counselor Apollo will quarrel with kindred lawyer Athena over his trepidation of statures, Phoenix's received little girl Phoenix Wright: Ace Attorney – Spirit of Justice for Nintendo 3ds will play with Apollo, and Rafya will verbally tear Phoenix another one preceding making jokes about his potential execution with a grin all over. These examination scenes likewise offer chances to become more acquainted with Khura'in, a domain new to the arrangement, and all its horde quirks. Khura'in itself, with its profound binds to most profound sense of being and fixation on supplication and soul-purging, can be viewed as a character here, and it's beautiful traditions makes it a fascinating, consideration getting district to invest energy in.


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When the bed bugs are in your home, they'll be going from 1 location to another. Bed bugs are intrusive bugs Currituck, NC that may be difficult to find. They are best treated by an experienced specialist.
Bed bugs are rather more resilient and resistant than each bug, consisting of rats and cockroaches in Currituck, NC . Unless a bed bug was found, the very first sign of an problem is typically the existence of skin inflammation. When bed bugs have actually attacked your house, they can be rather difficult to obtain rid of. They can be more difficult to treat than other home insect insects for a couple of reasons. Because they are tough to see, utilize a magnifying glass. They do not stay on the human that they are feeding upon therefore they will typically conceal in clothes and attempt to get to a brand-new place. They are unable to make it through heats, making heat a highly efficient treatment approach .
Charge of bed bugs can spend some time and numerous follow-up treatments. Overall control takes a carefully prepared and created integrated method. Bed bug control doesn't need to be costly Currituck, NC .
You will have to know the signals of a insect infestation. An invasion is something which can take place to anyone Currituck, NC . As an example, be certain to look at where you have to take care of your bed bug problem. If you're worried you own a bed bug infestation, begin searching for physical indications of their presence. Bed bug invasions can impact a single bed in 1 room or a entire home or residential or commercial property. Chemical methods aren't the only method to control bed bug infestations.
Ways To Get Going with Bed Bugs Exterminator or Pest Control Operator Currituck, NC ?
Generally, skilled pest control organisation will employ a couple of selections of treatment approaches like vacuuming, cleaning, steaming and other mechanical approaches to absolutely get rid of the bed bug problem. There are several pest control business that might assist you for the exact very same. Usually speaking, a lot of good bug control services will initially send out down a expert to run a visual inspection of your home prior to quoting you a cost Currituck, NC .
If you're not needed to leave your home for more than a number of hours during the extermination, or in case you are preparing for the pest control specialist, there are a number of techniques to prevent taking bed bugs with you. When you are able to observe that bed bugs have undoubtedly entered your house, it's never too early to try and locate an exceptional bed bugs pest control specialist Currituck, NC Currituck, NC . During a fumigation, your house will be handled in tarpaulin, which is usually anchored using huge containers of water you need to supply. Whether a complete house is infested, it might be essential to spray listed below the house, which would increase the overall price of services. Your home does not need to be infested that you get bed bugs. Aim to remember that Do It Yourself insecticides alone are unlikely to rid your house of bed bugs, particularly products which do not keep killing after they dry.
The Fundamentals of Bed Bug Extermination Process Revealed Currituck
If your bed has metal tubes for legs you have to treat inside the tubing together with outside 6. Next you'll need to make it hard for the bed to turn into infested again. In the event the bed bugs are in a room, you need to resolve yourself to the simple fact that you're going to need to select the room completely apart.
If you haven't yet sealed your home against bed bugs, now's the opportunity to do it. The tighter you seal your home the not as likely you're going to have bed bugs. Whether a whole home is infested, it might be necessary to spray below the home, which would increase the general price of services.
Extensive application of pesticides for bed bug control isn't recommended and might not be legal as a result of hazards involved. The entire procedure takes 6-10 hours, we'll request that you leave after breakfast however, you may return in time for dinner. You'll also learn how you're able to locate the very best bed bug extermination process in your region.
Contrary to what a lot of people believe, you don't have to live with bed bugs! With an exterminator, you'll be in a position to knock out bed bugs instantly, or basically within a few hours or days, as some exterminators have various ways to tackle different bed bugs. So, the best method to remove bed bugs safely is to employ a specialist exterminator with an established history. Deciding how to eliminate bed bugs can leave you with a few difficult choices. Run your dryer on high heat for a minimum of 20 minutes, and you'll effectively kill any bed bugs in there. Bed bugs can be exceedingly hard to detect with the naked eye, even though they leave telltale indications of their residence. You might also find the bugs together with the light brown discarded skins of the bed bug nymphs once they have molted.
Be certain to look into any seams and about the button tufting to make certain you get at any bugs that might be present. Bed bugs are somewhat more common than you believe. While they can be difficult to eradicate, they are not worth risking your home or property. They have been around for thousands of years. They have been a common household pest for hundreds of years. They are some of the most annoying to deal with on a daily basis if your bed bugs crawl on you while you are in bed or they come in big numbers. In addition, there are steps you may take to prevent bringing bed bugs home.
If you've got a particular type of bed bu infestation you don't understand how to knock out, they will tell you in their website if they may help you out the most. A bed bug infestation has to be addressed quickly and efficiently. Bed bug infestations can affect one particular bed in 1 room or a whole house or property. Chemical methods aren't the only method to control bed bug infestations.
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Private Scholarship Search
Students can use the Internet to search for other potential scholarship opportunities.
Free scholarship search engines
Scholarship applications may require a résumé, statement of goals, essay, demographic information, or other application materials. Attention to detail and professional appearance when completing scholarship applications could enhance the chances of winning a scholarship.
Other sources for scholarship applications could be
- guidance counselors,
- school libraries,
- local libraries,
- civic organizations,
- businesses, and
- organizations.
State of Kansas opportunities
State of Kansas students are also encouraged to apply for the State of Kansas Scholarships through the Kansas Board of Regents.
Be sure to view our presentation on searching for private scholarships (pdf) for more tips and advice.
Before beginning your scholarship search, please carefully review our information regarding scholarship scams.
The K-State Office of Student Financial Assistance is providing this information as a courtesy and does not promote, validate, or maintain the websites listed. URL addresses and website contents frequently change. The web addresses listed were accessible as of April 2017. Any website appearing here does not imply that Kansas State University or the Office of Student Financial Assistance agrees with the material contained or linked in the websites.


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BEIJING, China - Basketball star Dennis Rodman is heading to North Korea for the second time this year for what he says is a friendly visit to his friend, the communist nation's leader, Kim Jong Un.
But he is playing down speculation his trip is aimed at freeing jailed American missionary Kenneth Bae — saying there's been "nothing promised." Rodman spoke briefly to reporters Tuesday while transiting at Beijing's airport on his way to Pyongyang.
"I'm going to North Korea to meet my friend, Kim," he said. "It's a friendly gesture."
Rodman first met Kim — a basketball fan — during a visit in February to promote the sport and make a film. U.S. officials frowned on the trip for giving Kim a propaganda boost, but Rodman suggested "basketball diplomacy" could warm relations.


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SANTA BARBARA — Hollywood's unique awards calculus wouldn't seem to take a film festival at this posh coastal enclave into account.
The Santa Barbara International Film Festival, after all, is not a prestige movie launching pad such as the Toronto International Film Festival or an indie acquisitions bazaar like Utah's Sundance. But over the last decade, the Central Coast festival has carved an important niche in the movie ecosystem.
Arriving exactly two weeks after Academy Awards nominations were announced, the Santa Barbara festival is distinguished as a tactical pit stop on the way to the Oscars. The event functions as a de facto coda to the Golden Globes and awards from screen actors, directors, producers and writers guilds — the final word in cinematic valediction before the Academy Awards.
Consider that this year's festival, which runs through Sunday, is attracting Oscar nominees Cate Blanchett, Leonardo DiCaprio, Bruce Dern, Martin Scorsese, David O. Russell, Jared Leto and June Squibb to this scenic beach town 90 miles north of L.A.
One reason: More than 160 motion picture academy members are registered for the festival, and many others keep secondary residences here.
The SBIFF, which kicked off Thursday, touts itself as "a must-stop for front-runners on the awards season fast track." As such, the fest has staked its reputation hosting tributes in recent years for a substantial number of eventual Oscar victors including Sandra Bullock, director Kathryn Bigelow, Christoph Waltz, Christopher Plummer and last year's lead actress winner, Jennifer Lawrence.
This year, in addition to several Oscar nominees, Robert Redford and Oprah Winfrey are among the A-listers receiving honors at the festival.
On Saturday night, Blanchett traveled up the coast to receive the festival's outstanding performance of the year award for her Oscar-nominated portrayal of a booze- and pill-addled Manhattan socialite in Woody Allen's "Blue Jasmine."
After cringing her way through a video montage from her two-decade film career — "Awful," she said, watching herself from the stage of Santa Barbara's venerable Arlington Theatre — she reminisced about the time "a tarantula crawled on Ron Howard's crotch" and then she retired to a small after-party where she was toasted with 200-year old Hennessy Cognac.
The 2005 Oscar winner, who recently landed a Golden Globe and a Screen Actors Guild award and is considered the favorite for the Academy Award come March, recalled being pregnant the last time she was honored in Santa Barbara with the festival's Modern Master award in 2008.
"It's a prestigious festival!" Australia's Blanchett said. "It's a small community that really loves film and it's really coming into its own. To be singled out this way by the Santa Barbara International Film Festival is absolutely thrilling. They've clearly made a mistake, but too late now."
A decade ago, the festival was a more parochial concern. Attracting no shortage of independent movie stalwarts and admirable films, its glam quotient and wow factor were comparatively dim. More of a getaway diversion, the festival was off the radar for top-tier talent.
That started to change in 2004 when Roger Durling was installed as executive director. At the time, the festival took place closer to springtime — after the Oscars — and had yet to adopt its star-studded celebrity tributes.
"It is convenient that we're a festival that happens to take place after the Oscar nominations," Durling said. "Every town in the U.S. seems to have an international film festival. This helps define us. It gives a clear indication as to what this festival is all about."
To be sure, the Santa Barbara fest provides a showcase for nearly 200 movies, including 35 American premieres and 24 world premieres, and is expected to draw around 70,000 attendees over its 11-day run. The 29th installment of the festival will also feature a series of panels on directing, screenwriting and other entertainment-industry-skewing topics.
But tributes — reverential career retrospectives that Durling likens in format to Bravo's "Inside the Actors Studio" — remain the fest's signature programming.
In addition to Blanchett's tribute and one last week for filmmaker Russell — who is in the Oscar hunt for his corruption caper "American Hustle" and was awarded outstanding director by the festival — fellow Academy Award nominees Leto ("Dallas Buyers Club") and Squibb ("Nebraska") are set to receive festival honors.
On Thursday, DiCaprio and Scorsese, the Oscar-nominated star and director, respectively, of the controversial biopic "The Wolf of Wall Street," are scheduled to appear at the Arlington Theatre and receive the Cinema Vanguard award. And on Saturday, "Nebraska" star Bruce Dern, another lead actor nominee for his performance as a cantankerous retiree, will arrive in Santa Barbara to be feted with the fest's Modern Master award.
According to Lea Yardum, a longtime Paramount Pictures awards strategist who helped organize the appearances by DiCaprio, Scorsese and Dern, Santa Barbara provides several "for your consideration" upsides, including the chance to bring Oscar contenders to academy voters off the Hollywood grid.
"The entertainment community goes to a lot of huge festivals and each has its individual charms," Yardum said. "But Santa Barbara is smaller; it's gorgeous. From an awards perspective, there's a good amount of members there. And you know you're going to celebrate talented people's accomplishments in a really intimate way."
She added: "When you get outside the primary cities where Oscar voters live, you are only helping your cause."
Santa Barbara local Michelle Bruner has been coming to the festival since the early '00s and remembered one under-attended tribute for "Dreamgirls" director Bill Condon, who received the festival's Montecito award in 2007.
"The theater was half full and they were giving out free tickets," Bruner said. "They had to have volunteers go and pick people off the streets."
This year, nearly all of the panels sold out before the festival's start date.
On Saturday, a panel called "Creative Forces: Women in the Biz" showcased the working methodology of several of the year's most celebrated female producers: Dede Gardner ("12 Years a Slave"), Rachel Winter ("Dallas Buyers Club"), Gaby Tana ("Philomena") and Sara Woodhatch ("Before Midnight").
Gardner remarked on the hothouse festival environment and its importance in promoting prestige films.
"It's not often you're in a small town filled with people who love movies," said the producer, president of Brad Pitt's Plan B Entertainment.
Blanchett, after being handed the outstanding performer of the year award by an uncharacteristically effusive Rooney Mara (her costar in the upcoming psychological drama "Carol"), included a moment of appreciation for the SBIFF.
"I will come back again if you can invent another award for me," Blanchett said with a laugh.


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The J-31, China's second fifth-generation stealth fighter designed by Shenyang Aircraft Corporation, is capable of outperforming all US fourth-generation fighters in aerial combat, according to a US fighter pilot cited in our sister newspaper Want Daily.
With its appearance similar to the US F-22 and F-35 fighters, the J-31 was developed based on US technology stolen by Chinese spies, the pilot claimed. He gave his view that all US fourth-generation fighters including the AV-8, F-15 and F/A-18 would be unable to go head to head against the J-31 in a dogfight.
The plane will be the perfect fighter for the People's Liberation Army to carry out anti-access and area-denial strategies in the Western Pacific, he said.
The Chinese fighter will also present a challenge to the F-35 in the overseas export market, the pilot predicted. It may not be as advanced as the F-35, but it is much cheaper than its US counterpart.
Putting the J-31 on display during the Zhuhai Airshow may signal that China is trying to attract attention from potential buyers, the pilot said. It will certainly be more popular among developing nations, he added.
The key weakness of the J-31 and J-20 is that China is still unable to design sufficiently powerful and reliable engines for them, however. Until now, China has depended on purchasing engines from Russia.
New designs of Chinese aircraft are now replacing this dependency, though they are still kept secret, the pilot said. What the United States should worry about regarding the J-31 is quantity rather than quality, he added. Though the US has better trained pilots, it will still find it difficult to face a swarm of J-31s, he said.


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Coming to a School Near You
Part of the Religious Liberties Series
Series About:
Robb and Robin Wirthlin were aware that the Massachusetts Supreme Court legalized same-sex marriage in November 2003 - but they never dreamed the issue would affect them so quickly and in such a personal way.
In March of 2006, their son came home and told them about a book his teacher had read to his 2nd grade class. In the book, a prince went in search of a princess to marry, but chose instead to marry another prince. After emailing the teacher with their questions, however, they learned that she had read the book, King and King, to the entire class – a book promoting same-sex marriage.
The Wirthlins requested that the school inform them of future class discussions on this topic. School officials refused. The Wirthlins went to court to secure their right to be informed of and direct their child's education. The judge ruled against them, deciding that the state must teach same-sex marriage in public school--even when parents disagree, and regardless of a family's beliefs.


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Discover! Simulations
Kinds of Matter
1. Get Set to Explore
- compound: A substance made up of two or more elements.
- element: A substance that cannot be broken apart into other substances; there are just over 100 known elements.
Building Background
- Review the vocabulary words and their definitions with the class. Run a brainstorming session for students to name all the elements they can think of, with you listing the elements they name on the board. Have volunteers name one element at a time. Try to involve all students in adding to the list. If students happen to name a compound rather than an element, use the opportunity to differentiate between elements and compounds, reinforcing the definitions. Keep the list of elements up on the board.
- Ask students to talk about the universe and the types of objects in it. If necessary, have them look back at Student Edition Chapter 11. Guide students to realize that stars are the most common objects in the universe. There are more than 200 billion stars in an average galaxy like the Milky Way. Scientists estimate that there are about 125 billion galaxies.
- Challenge students to recall the main elements that form stars. Write down their answers on the board. Suggest students answer without looking at their textbook.
- Ask the Discover! question. Referring to the list of elements on the board, let volunteers name the one they think is the most common in the universe and explain why. Let the class vote, tallying their votes on the board. Keep the tally to refer to later.
2. Guide the Exploration
- Let students launch the Discover! Simulation. They should click each of the five objects shown to learn the main elements found in each. The percentages are figured by using the total number of atoms, not by using mass or volume.
- You may wish to explain that the set of lines shown for each star is what scientists use to identify the elements in a star. Stars are made of very hot gases. Any gaseous element can be identified by heating the gas and passing the light through a spectroscope. The spectroscope resolves the light into a unique set of lines. Scientists compare the lines that result when starlight passes through a spectroscope with those given off by different elements to deduce the elements present in stars.
- Students should spend some time comparing the different objects and hypothesizing which element is most common. Before students go on to Step 3, have them share their hypotheses and reasons for them. Let the class vote again on the most common element in the universe. Then, tell students to complete the simulation.
3. Review/Assess
- Discuss Step 3's Wrap-Up text with the class. Point out that since stars and galaxies are the most common and most massive items in the universe, hydrogen—which composes 90% or more of most stars and galaxies—is the most common element.
- Have students return to the simulation to work on the Extension questions. Assign them to work in small groups and help them understand the following answers:
- Helium is the second most common element in the universe, because it makes up 10% of galaxies and most stars.
- The composition of Earth differs, as Earth contains little helium.
If time permits, present students with the following questions:
- Critical Thinking: Synthesize The simulation explains that since the densest part of Earth includes the crust, mantle, and core, and these are composed mainly of iron, oxygen, and silicon, these three elements are the most common on Earth. Why is density important to determine the most common elements on Earth? Answer: Density is a ratio of mass to volume. The higher the density, the greater the amount of mass per unit volume. A greater mass, in this case, implies a larger number of atoms. The larger the number of atoms, the more common the element.
- Inquiry Skill: Compare Review Student Edition pages E16–E17—the periodic table. How does the atomic number of the most common elements in the universe compare with those of less common elements? Give a hypothesis about why this might be so. Answer: Hydrogen and helium are the most common elements and they are the lightest elements. One hypothesis might be that the other elements form only from lighter atoms fusing together; the conditions under which this occurs may not be common.
4. Reaching All Learners
On Level: Logical/Visual Learners
Encourage students to make circle graphs to compare the composition of the five different space objects shown in the simulation. Let students use their circle graphs to help others better understand the composition of the different space objects.


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"WOOL" entries
WOOL author Hugh Howey is a tech optimist: The O'Reilly Radar podcast
In separate interviews, authors Hugh Howey and Ramez Naam discuss science fiction and their views of the future.
Editor's note: you can subscribe to the O'Reilly Radar Podcast through iTunes, SoundCloud, or directly through our podcast's RSS feed. You can download this individual episode via this link.
Science fiction long has fueled the imaginations of scientists and inspired (or foreshadowed) technological advancement. We have only to look back at the works of Isaac Asimov, or even Kurt Vonnegut, and episodes of "Star Trek" or movies like "Minority Report" for science fiction technologies that are (or nearly are) coming into existence today.
In this podcast episode, author, scientist, and futurist Ramez Naam explains to O'Reilly's Mac Slocum that science fiction had a direct influence on his current interests in human enhancement and telepathy. Naam grew up reading science fiction ("like a lot of geeks," he says) and once he started reading scientific journals and papers, he started seeing the connections. Naam says, "I found out that a lot of science fiction ideas were becoming actually possible — that scientists were implanting electrodes in the brains of animals and getting them to move robot arms by thought, to help people who were paralyzed."