text:
Frnakenstein: multiple target inverse RNA folding
© Lyngsø et al.; licensee BioMed Central Ltd. 2012
Received: 7 July 2012
Accepted: 23 September 2012
Published: 9 October 2012
RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard.
In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets.
Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available athttp://www.stats.ox.ac.uk/research/genome/software/frnakenstein.
RNA Inverse folding Genetic algorithm RiboswitchBackground
The function of the RNA molecule depends on the way it folds – structural changes can change protein binding sites, or affect activity for ribozymes, for example. RNA folding allows the single strand of nucleotides to fold upon itself and form more complex structures such as helical junctions and pseudoknots; almost as soon as RNA started to be sequenced, methods were established to determine the structure from the sequence of nucleotides. Early attempts include[1], who simply summed over all possible secondary structures and evaluated them with respect to free-energy functions. Biological and thermodynamical principles have since been applied to formulate more advanced free-energy functions facilitating more accurate and efficient predictions, which have been used to great effect in methods such as UNAFold[2] and RNAfold[3]. Stochastic Context-Free Grammars have also been used to great effect in programs such as Pfold[4, 5]. For a review of RNA secondary structure prediction, see[6] or[7].
The inverse RNA folding problem is defined as follows: given a particular RNA secondary structure (target structure), find a sequence of base pairs that would fold into this structure. One could adopt two possible solution techniques: either find an exact match, i.e. a sequence whose predicted structure matches the target structure exactly, or look for a sequence whose predicted structure is as close as possible to the target structure (a suboptimal solution). Then, the inverse folding problem becomes an optimization problem: the goal is to minimize the distance metric defined between a given target structure and the predicted structure of a sequence. Here we consider only base pairs {A−U,U−A,C−G,G−C,G−U,U−G}, and, since experimental verification of the folded structure is not feasible, the structure predicted computationally by RNAfold is used as a proxy for the true secondary structure of a designed sequence.
There are several existing approaches to the RNA Inverse Folding Problem. RNAInverse[3] is the most basic method, inspired by local guided search. Given a target structure, it produces a random sequence that is then randomly changed at points where its predicted structure differs from the target structure. RNA-SSD[8], INFO-RNA[9], NUPACK: Design[10], and Inv[11] are also local guided search based methods, using various combinations of intelligent initial sequence design and/or hierarchical decomposition of the target structure. MODENA[12, 13] is the only algorithm that introduces a genetic algorithm approach. This approach is multi-objective: it aims to maximise the closeness to the target structure and minimize the free energy of a solution. It facilitates a better exploration of the search space, and avoids the limited prediction capabilities of the local guided search methods. However, a strong focus on energy minimisation causes an extreme bias towards C-G base pairs.
However, there are currently no implementations available capable of solving the inverse folding problem under multiple structural constraints. To our knowledge, the only existing method for inverse folding with multiple structure targets was published by[14]. This method has not been made publically available as part of the Vienna package. With the current interest in using bio-molecules in nano-technology, the ability to design artificial riboswitches reacting to changes in conditions will become increasingly important. Hence an implementation capable of solving the inverse folding problem for multiple structures is a key development in structure design.
The inverse folding is implemented by a fairly standard genetic algorithm (GA) approach[15], expanding a population by mutations and recombinations and selecting the most fit individuals for propagation to the next generation. The main deviation from a completely generic GA is that the method is aware of the aim of designing sequences folding into one or more target structures. Rather than search the full sequence space, we direct the search by ensuring all sequences can fold into the target structure(s) forming only canonical base pairs. This can be viewed as a similar approach to the local search/adaptive walk on a hierarchical decomposition of the target structure implemented by some methods[8, 10, 11, 16], except that the recombination operation chooses a random decomposition and assesses two complementary structural components in conjunction, rather than independently.
In addition to a random search, our method also implements several strategies for more directed evolution. Instead of making uninformed evolutionary changes and leave it to the selection part of the GA to direct the search, it is also possible to bias the choice of change towards e.g. mutating positions with a predicted structure that does not match the target, or in a recombination towards parts that have a good match to the target structure in the regions where they contribute sequence. These strategies are all available through command line options (and as classes when the implementation is used as a library rather than stand-alone program) to allow experimentation and tailoring to specific applications. Through experimentation, a set of parameters was found which worked reasonably on all types of structure, which is set as a pre-defined default. In the following, we will use to denote a target consisting of a non-empty set of structures, all of length n, and s to denote a sequence in the GA population.
Positional fitness
A key concept in the GA is the fitness of positions. This allows directing evolutionary changes by choosing unfit positions for mutations – an approach also taken in[8, 10] and to a lesser extent in[3, 9, 11] – and regions with fit positions for recombination. Positional fitnesses take a value of 1 for maximally unfit positions and a value of 0 for maximally fit positions.
We define positional fitness schemes relative to a single target structure τ. If consists of multiple target structures, the final positional fitness is computed as the average positional fitness over all structures in. Let τ i denote the required structure for position i in τ, i.e. either forming a base pair with another position j or unpaired. Let σ denote the optimum structure predicted for s (i.e. the minimum free energy structure), and let denote the set of possible structures for position i, i.e. base pairs with position i as one base in the pair and the unpaired configuration. Finally, let be the marginal Boltzmann probability in the form of a mapping from positional structure to marginal probability. Our method provides the following choices for the fitness of position i, denoted f[i].
Scheme 1. Binary indicator of whether position has correct predicted structure, f[i]= 1 − δσ [i],τ[i] where δ is the Kronecker delta. This corresponds to the μ(s τ) based objective in[10], providing a binary view of whether the design matches at position i that may be too coarse grained. However, it does also capture σ is correct at position i, or the design needs to change.
Scheme 2. Boltzmann probability of target structure, f[i] = 1 − p(τ i). This corresponds to the n(s τ) objective in[10], providing a measure of how likely a structure drawn from the Boltzmann ensemble is to match τ at position i. This provides more fine grained information than scheme 1, but measures proximity rather than match to τ.
Scheme 3. Truncated negative logarithm of Boltzmann probability of target structure, f[i] = min{−log(p(τ i))/100,1}. This penalises decreasing probability to match τ with increasingly severity, and is particularly useful for multiple structure targets where the average corresponds to a sum of logarithms, thus penalising designs failing to match just one of the target structures. Truncation is performed to allow mapping to [0,1].
Scheme 4. Binary indicator of whether probability of target structure exceeds threshold. This allows requiring all elements of τ to be present with a given probability when sampling the Boltzmann ensemble, but being oblivious to further improvements beyond that. It is particularly useful when specifies a multi-stable design, i.e. a target with multiple structures for the same temperature, by measuring the number of target structures the design matches with probability at least θ at position i.
Scheme 5. Sigmoid transformed difference between Boltzmann probability of target structure and most probable alternative structure, where. This allows accepting lower probabilities of τ i in regions where the structure is generally less well defined, although a position is still most fit iff p(τ i) = 1. The transformation corresponds to, normalised to yield values in [0,1], and causes changes to have larger effects when the probability of τ i and the most probable alternative are close to being equal.
The p and σ are computed at the temperature specified for τ, and may thus differ between the τ's when a multiple structure target is specified.
Finally, the following positional fitness schemes specifically designed for multiple structure targets are defined.
Scheme 6. Minimum Boltzmann probability of target structures,.
Scheme 7. Product of Boltzmann probabilities of target structure,.
For single structure targets, they are equivalent to the Boltzmann scheme, scheme 2. For multiple structure targets, scheme 6 exclusively focuses on the worst fitness over all target structures, while scheme 7 includes Boltzmann probabilities from all target structures. However, by multiplying the probabilities, having a low fitness on just a single target structure will have a much more notable effect, than under the sum implicit in the averaging of scheme 2.
In addition to a single of the above schemes, there is the possibility of using a weighted combination of any subset of them to define positional fitness. E.g. combining the first two schemes would divide positions based on whether they have a predicted structure matching the target, but further graduate the fitness by the marginal Boltzmann probability of the target structure at each position.
The concept of positional fitness underpins most operations of the GA: mutation, recombination, selection, and termination. Whenever fitness of a region (for recombination cross over point selection) or the entire sequence (for selection and termination) is needed, this is obtained as the sum of the positional fitnesses in the region or sequence. Different positional fitness schemes can be used for these four aspects, with the limitation that negative logarithms of Boltzmann probabilities are only used for mutation, and product of Boltzmann probabilities cannot be used for mutation.
Fitness and objective
Often fitness and objective of GAs are considered equivalent, but we make the distinction of using fitness for the selection in each round of the GA and objective for determining when an adequate solution has been found and the search can be terminated. In a standard design problem where the aim is to find a sequence folding to one specific target structure, it is natural to base the objective on whether positions are correct in the predicted structure and terminate when the number of errors reaches 0. However, a more fine grained selection may be desirable, for example substituting or combining the number of errors with scheme 2 – instead of choosing randomly between two sequences with e.g. 10% positions that are wrong in the predicted structure, we would prefer the one with higher probabilities of positions being correct.
A global, i.e. non-positional, scheme
Scheme 8. Logarithm of structure probabilities in Boltzmann ensemble and their variance: where and x τ = −logp τ is the negative logarithm of the probability of target structure τ in the Boltzmann ensemble of sequence s, and ξ ≥ 0 is the weight assigned to the contribution from the variance
based on the cost functions discussed in[14] and corresponding to the Π(s τ) objective in[10], is also available for defining fitness and objective. This provides a means of requiring an exact match to the target structures, rather than basing the fitness on the distance to predicted or expected structure as in e.g. schemes 1 and 2. This is particularly relevant when designing for multiple structures at the same or very similar temperatures, where some of the position based schemes may be confused by designs where positions exhibit a good match to varying subsets of the target structures.
Finally, to maintain diversity in the GA population, the fitness can be augmented with a weighted contribution from the average Hamming distance to already selected sequences. If denotes the set of sequences already selected in the selection stage at the end of a generation in the GA, each remaining candidate sequence s has its fitness augmented by, where h(s,t) is the Hamming distance between sequences s and t, and ζ > 0 is the weight assigned to the contribution from diversity, before selecting the next individual carried forward.
The position targeted for mutation in a sequence is chosen either uniformly at random, or with probability proportional to positional fitnesses. Similarly, sequences can be chosen for mutation either equally many times, uniformly at random, or with probability proportional to the reciprocal of the sequence fitness (with sequences with fitness 0 given twice the probability of the otherwise most fit sequences).
When choosing a new nucleotide for a position chosen for mutation, we want to maintain compatibility with all target structures. That is, the modified sequence should fold into each target structure using only canonical Watson-Crick and GU wobble base pairs. When the target consists of a single structure, unpaired positions can be updated independent of the rest of the sequence, while base pairing positions can be updated by sampling a new base pair for the two positions independent of the rest of the sequence. However, with two or more target structures, dependencies can extend to more positions, as a position can be base paired to multiple other positions in the different target structures.
The target dependency graph (TDG) (denoted dependency graph in[14]) implied by is the graph on nodes {1,…,n} where two nodes i, j are connected by an edge iff, where i · j denotes a base pairing of positions i and j. The compatibility of a position will depend, directly or indirectly, on all positions in the connected component it belongs to in the TDG, so the entire connected component may have to be updated in a mutation. It can be observed from ([14], Theorems 1 & 2), that with canonical base pairing compatible sequences will exist iff the TDG is bipartite, and if the TDG will be bipartite. If, no compatible sequence may exist. For example, if three target structures contain base pairs i·j, j·k, and i·k, respectively, then there is no assignment of nucleotides to positions i, j, and k that will leave all base pairs canonical.
In[14] formulas for sampling an assignment of nucleotides on a connected component when the maximum degree of any node is at most 2 is provided. However, we have chosen a simpler, heuristic update algorithm for two reasons. First, our method was developed to also cope with larger sets of target structures. Secondly, even for the maximum node degree may be 3 and hence one may suspect assignment of nucleotides, i.e. colouring of the nodes, uniformly at random to be difficult – with a three letter nucleotide alphabet with base pairs allowed between any two non-identical nucleotides, the problem becomes # P hard[17]. Finally, it is unclear whether sampling uniformly from the set of compatible assignments is the best strategy. As G's and U's can pair with two other types of nucleotides, while C's and A's can pair with only one other type, the set of compatible assignments will be biased towards a high GU content.
The following forms our method for sampling nucleotides on a connected component in the TDG, starting with position i, ensuring all positions form canonical base pairs following the update.
Choose σ from {A,C,G,U}∖{s[i]} and set s[i] = σ
F = {i}, N = {j∣i · j}
while N ≠ ∅ do
Choose j ∈ N uniformly at random
Choose σ from and set s[j] = σ
F = F∪{j}, N = N∪{k∣j·k}∖F
end while
where j · k denotes that two nodes are connected by an edge in the TDG and is the set of nucleotides compatible with σ. It performs a traversal of the connected component of i, at each step choosing a random node neighbouring the already updated nodes. New nucleotides are drawn from a distribution which can be specified – if the default uniform distribution is used, this will tend to favour high GU content for the same reason as for choosing complete compatible assignments uniformly at random discussed above – truncated to the possibilities allowed. If the current nucleotide is among the choices, there is an option either always to keep the current nucleotide (to limit collateral effects of a mutation) or to bias the draw with 1 − f [i] for the current nucleotide and f [i] for alternatives (to allow the current positional fitness to affect the probability of a change).
Due to the hierarchical nature of RNA secondary structures, the GA uses recombination mimicking gene conversion rather than cross over, i.e. an infix of one sequence is recombined with the corresponding prefix and suffix of the other sequence. The easiest way to keep all base pairs canonical, is to always take two positions forming a base pair in a target structure from the same sequence. If we create a recombinant on sequences s and t from a crossover point i,j by forming the sequence s[1..i] t [i + 1..j] s [j + 1..n], no base pairing positions come from different sequences iff there are no base pairs in the target structure(s) for which one of i + 1 and j is inside the base pair and the other one is outside the base pair. This means that we can partition break points into sets of pairwise permissible points, such that the aim of taking base pairing positions from the same sequence is achieved iff crossover points are chosen as pairs of points from the same set in this partition. For single structure targets, these sets are exactly the loops of the structure, when stacking base pairs are viewed as internal loops of size 0, and the set of all external positions. The following outlines the procedure used for constructing the sets of pairwise permissible points, where sets of size 1 are discarded. The target is denoted by, and when the algorithm terminates C is the set of non-singleton sets of points that are pairwise permissible.
for do
for S ∈ C do
(X ∈ { S∩[i, j)[ ,S∩ ([0,i[∪[j,n])}:|X|>1
end for
where f s and f t are positional fitnesses for s and t respectively. Similarly, the pair of sequences s, t can be chosen uniformly at random, based on individual fitness as described for mutations above, or based on the sum over all pairs i, j of permissible points of to preferentially choose pairs of sequences complementing each other.
Initialisation of sequences in the starting population can either be done randomly, by sampling nucleotides for each connected component in the TDG as outlined for mutation, but without the presence of current nucleotides, or by running RNAinverse from a random starting point. The latter option, an approach also used by RNAexinv[18], allows solutions to be found rapidly for easier targets. When RNAinverse is used and the target consists of multiple structures, a random is chosen for each run. Hence, the initial sequences may not be compatible with. Additionally there is also the option to read the initial sequences from file, for example if specific sequence motifs are present it may be desirable to litter the initial population with them – it does also provide a simple means for using an alternative inverse folding method to create the initial population of sequences.
Data was taken from two main sources, to benchmark Frnakenstein and other inverse folding methods. The first data set used in our benchmarks is the data set used in[12]. This was downloaded from the MODENA website. It consists of a structure from each of the 29 out of the first 30 families in Rfam[19], with the tmRNA family (RF00023) left out due to a high content of pseudoknot forming base pairs. We refer to this data set throughtout as the Rfam data set.
Secondly, data was taken from RNASTRAND[20], which itself takes data from many sources[21–25]. The data was filtered so that the sequences and structures could ensure reliability of predictions. We removed identical sequences and disregarded synthetic data and sequences with ambiguous base pairs. Further, any sequences with greater than 80% base pair similarity with another structure in the data set were removed, as well as all sequences with pseudoknots, as RNAfold does not predict pseudoknots. The resulting data set consisted of 397 RNA molecules, containing 363 unique secondary structures with a total length of 55,025, which we refer to as the RNASTRAND data set.
However, with both data sets, it may be possible that there is no sequence which RNAfold will fold into the reference structure, and so the method might not be able to acheive 100% accuracy, due to RNAfold, not the search heuristic. Consequently the sequences corresponding to the structures in the RNASTRAND data set were re-folded using RNAfold, so there is known to be at least one sequence which will correctly fold. This dataset will be denoted as the RNASTRAND-Refolded, and consists of 383 unique structures with a total length of 56,606.
Results and discussion
Multi-structure targets
For all benchmarks on multiple structure targets we set the number of generations to the total target length, i.e. the number of structures in the target multiplied by the length of the sequence to be designed. Again Frnakenstein was run with default values, which means that compared to the single structure target default outlined above, positions for mutations were chosen based on a 1:1:1 combination of schemes 1, 2, and 3; cross over points were chosen based on a 1:1:2 combination of schemes 1, 2, and 7; fitness was based on a 1:1:2:4 combination of schemes 1, 2, and 7, and the diversity maintaining contribution from Hamming distances, except for the SV11 example above where a fitness based on scheme 8 with ξ = 1 and an objective based on scheme 4 with θ = 1/3 was used.
To some extent the SV11 target poses an impossible challenge, as we cannot find a sequence having both conformations as the most stable structure. Hence, for bi-stable targets, we cannot measure performance by simply reporting successes and failures. To avoid this problem, we decided to test the performance of multiple structure target design by providing target structures at two different temperatures. We folded the 304 sequences with at most 200 nucleotides of the RNASTRAND data set under 20°C and 37°C, simulating a change from room temperature to normal body temperature. After eliminating duplicates, 291 two structure targets remained.
177 targets, with a total of 11,188 nucleotides, had identical structures at the two temperatures. 114 targets, with a total of 10,578 nucleotides, had different structures at the two temperatures, with an average of 16.9 positions where the structures differed. Even when the structures differ, it will be possible to design a sequence that successfully folds to the correct target structure at each temperature, allowing a simple and easy to understand measure on performance of number of successes. This does not directly test the ability to design a bi-stable molecule. However, it does test performance on multiple structure targets in a related realistic scenario for inverse RNA folding, where the aim is to design a molecule that under different conditions, either remains stable or performs as a riboswitch reacting to the change in conditions.
Performance on two structure targets
Both | One | None | |||||||||
n | | | n | | | | n | | | | |
Identical structures | 173 | 61.5 | – | 0 | – | – | – | 4 | 139.0 | – | 3.3 |
Different structures | 54 | 71.5 | 7.5 | 32 | 94.1 | 19.9 | 8.1 | 28 | 132.5 | 31.8 | 9.6 |
Successful designs were obtained for 227 targets. Of the remaining 64 targets, the design folded correctly at one temperature for 32 targets, with an average of 8.1 positions where the predicted structure of the design differed from the target at the other temperature. For the remaining 32 targets, the design did not fold correctly at either temperature, with an average of 8.8 positions being wrong. It should be remembered that targets were created by folding a specific sequence at two different temperatures using RNAfold, so in all cases we know that a perfect design does exist. Comparing this to the results obtained on RNASTRAND-Refolded, it is evident that the multiple structure target problem is considerably more difficult than the single structure target problem, in particular when the target structures differ.
Single-target structures
Since Frnakenstein works for single targets too, the performance of our method on single targets could be benchmarked against other methods that are publicly distributed as source code or executables. This includes RNAinverse[3], MODENA[12], INFO-RNA[9], NUPACK: Design[10], and Inv[11]. All benchmarks were done on a 48 core Dell PowerEdge with 2.3GHz AMD Opteron processors and 128GB 1.3GHz memory. Despite the availability of source code of RNA-SSD[8, 16], it could not be successfully compiled, so the web server was used where appropriate.
For each method being benchmarked, efforts were made to give it the same number of attempts at the problem, despite them employing different search heuristics. Our method and MODENA were both run 10 times with a population size of 50, and a number of generations equal to the number of positions in the structure (with a minimum of 50 generations). RNAinverse, RNA-SSD, INFO-RNA, NUPACK: Design, and Inv were all run 500 times with default parameters. All methods apply the Vienna RNA package for structure prediction, except for NUPACK: Design that uses the NUPACK suite, and Inv, which uses its own thermodynamic model. NUPACK allows interior loops of arbitrary sizes, whereas the Vienna package limits interior loops to a maximum size of 30. This allows NUPACK: Design to report a successful design on target structures with large interior loops, where all other methods will necessarily fail due to this limitation of RNAfold. Notably this is seen on the RF00016 and RF00024 structures in the Rfam data set, which contains interior loops with 83 and 67 unpaired nucleotides, respectively. Inv is even more restrictive on permissible structures, allowing only structures with a minimum stack size of 3, and minimum arc length of 4. This means that many trusted structures in, for instance, the Rfam database it deems as invalid, and thus will produce an error, suggesting it will perform badly in the benchmarks.
Frnakenstein was run with default values, which means mutation was biased towards fit sequences, positions were chosen based on a 2:1 combination of schemes 1 and 2; recombination was biased towards pairs of sequences with good complementary match and cross over points chosen based on a 1:1 combination of schemes 1 and 2; fitness was based on a 1:1:2 combination of schemes 1 and 2, and the diversity maintaining contribution from Hamming distance to already selected sequences, while objective was simply the number of erroneous positions in the predicted structure, cf. scheme 1. As one cannot determine statistically what fitness, mutation, and recombination schemes will optimise success of the algorithm, the defaults were determined heuristically to make Frnakenstein most likely to find a successful sequence for the target structure.
Rfam structures
Performance on Rfam data set
Acc. | Len. | Frnakenstein | MODENA | RNA-SSD | INFO-RNA | RNAinverse | NUPACK | Inv |
01 | 117 | 1.0 / 1204 | 1.0 / 17 | 0.01 / 8.2 | 0.95 / 1.2 | 0.01 / 61 | 0.29 / 11613 | ∗ |
02 | 151 | 1.0 / 13505 | 1.0 / 19 | 0.0 / – | 0.0 / 175 | 0.0 / 277 | 0.0 / 141999 | ∗ |
03 | 161 | 0.1 / 9997 | 1.0 / 37 | 0.0 / – | 0.01 / 112 | 0.0 / 304 | 0.0 / 50698 | ∗ |
04 | 193 | 1.0 / 198 | 1.0 / 27 | 0.0 / – | 0.27 / 64 | 0.10 / 164 | 1.0 / 5597 | ∗ |
05 | 74 | 1.0 / 0.14 | 10. / 4.8 | 1.0 / 0.34 | 0.99 / 0.31 | 0.87 / 1.4 | 1.0 / 148 | 0.29 / 9.2 |
06 | 89 | 1.0 / 27 | 1.0 / 5.9 | 0.98 / 3.4 | 0.66 / 4.6 | 0.06 / 20 | 0.99 / 299 | ∗ |
07 | 154 | 1.0 / 115 | 1.0 / 22 | 0.05 / 5.1 | 0.85 / 7.4 | 0.08 / 70 | 0.95 / 1611 | ∗ |
08 | 54 | 1.0 / 0.09 | 1.0 / 2.8 | 0.96 / 0.05 | 1.0 / 0.15 | 0.95 / 0.22 | 1.0 / 47 | 0.22 / 1.1 |
09 | 348 | 1.0 / 129057 | 1.0 / 123 | 0.0 / – | 0.0 / 4127 | 0.01 / 7100 | 0.78 / 111487 | ∗ |
10 | 357 | 0.0 / 245868 | 0.0 / 180 | 0.0 / – | 0.0 / 4046 | 0.0 / 8007 | 0.0 / 92211 | ∗ |
11 | 382 | 0.0 / 500078 | 0.0 / 184 | 0.0 / – | 0.0 / 7040 | 0.0 / 16634 | 0.0 / 77273 | ∗ |
12 | 215 | 1.0 / 5455 | 1.0 / 35 | 0.0 / – | 0.01 / 329 | 0.01 / 558 | 0.98 / 2825 | ∗ |
13 | 185 | 1.0 / 65 | 1.0 / 27 | 0.0 / – | 0.37 / 61 | 0.09 / 127 | 1.0 / 190 | ∗ |
14 | 87 | 1.0 / 0.15 | 1.0 / 7.3 | 0.94 / 0.09 | 1.0 / 0.30 | 1.0 / 0.27 | 1.0 / 34 | ∗ |
15 | 140 | 1.0 / 333 | 1.0 / 13 | 0.0 / – | 0.51 / 29 | 0.05 / 118 | 1.0 / 40696 | ∗ |
16 | 129 | 0.0 / 18734 | 0.0 / 11 | 0.0 / – | 0.0 / 102 | 0.0 / 124 | 0.48 / 10167 | ∗ |
17 | 301 | 1.0 / 318 | 1.0 / 117 | 0.0 / – | 0.94 / 21 | 0.23 / 263 | 1.0 / 703 | ∗ |
18 | 360 | 1.0 / 210591 | 1.0 / 180 | 0.0 / – | 0.01 / 4260 | 0.01 / 5305 | 0.0 / 101125 | ∗ |
19 | 83 | 1.0 / 1.0 | 1.0 / 6.3 | 0.4 / 0.63 | 0.98 / 0.52 | 0.57 / 3.7 | 1.0 / 46 | ∗ |
20 | 119 | 0.0 / 3149 | 0.0 / 10 | 0.0 / – | 0.0 / 7.8 | 0.0 / 15 | 0.0 / 810 | ∗ |
21 | 118 | 1.0 / 0.23 | 1.0 / 13 | 0.99 / 0.44 | 1.0 / 0.77 | 0.96 / 1.7 | 1.0 / 130 | ∗ |
22 | 148 | 1.0 / 293 | 1.0 / 16 | 0.0 / – | 0.15 / 46 | 0.02 / 97 | 1.0 / 5335 | ∗ |
24 | 451 | 0.0 / 138348 | 0.0/ 182 | 0.0 / – | 0.0 / 1530 | 0.0 / 4170 | 0.23 / 8533 | ∗ |
25 | 210 | 1.0 / 11838 | 1.0 / 29 | 0.0 / – | 0.06 / 132 | 0.0 / 463 | 1.0 / 10420 | ∗ |
26 | 102 | 1.0 / 290 | 1.0 / 6.1 | 0.0 / – | 0.04 / 50 | 0.02 / 60 | 1.0 / 1429 | ∗ |
27 | 79 | 1.0 / 0.23 | 1.0 / 8.1 | 1.0 / 0.29 | 1.0 / 0.49 | 0.82 / 1.2 | 1.0 / 112 | 0.86 / 9.7 |
28 | 344 | 0.3 / 197498 | 0.0 / 125 | 0.0 / – | 0.01 / 4627 | 0.0 / 6003 | 0.09 / 31920 | ∗ |
29 | 73 | 1.0 / 33 | 1.0 / 4.1 | 0.82 / 1.4 | 0.67 / 0.58 | 0.2 / 1.5 | 0.72 / 229 | ∗ |
30 | 340 | 1.0 / 133627 | 1.0 / 115 | 0.0 / – | 0.01 / 1896 | 0.0 / 5011 | 0.0 / 118373 | ∗ |
Total successes | 24 | 23 | 10 | 22 | 19 | 22 | 3 |
This data set was sufficiently small that RNA-SSD could be included in the benchmark by manually uploading the targets to the RNA-SSD server. Our method and MODENA, the only two genetic algorithm based methods in the benchmark, exhibits the best performance, each successfully designing sequences for 23 of the 29 targets. INFO-RNA also performs well, with 21 successful designs, while RNA-SSD and RNAinverse have more limited success, and Inv performing poorly. Every target Inv considered to not be invalid it succeeds with, but it is so limited on what it permits that it does not attempt the majority of structures.
Of the 5 target structures for which all RNAfold based method failed, two (RF00016 and RF00024) have internal loops with more than 30 nucleotides, which makes it impossible to reach a successful design as discussed above. All methods, including NUPACK: Design, failed on the remaining three (RF00010, RF00011, and RF00020). These all contain a bulge of a single nucleotide separated from either a large hairpin loop or the exterior of the structure by an isolated base pair. With the current energy parameters, it is impossible to design a sequence where the same structure with the isolated base pair removed would not be more stable[16]. Hence, Frnakenstein is the only method which does design sequences for all targets which are possible. For the remaining targets, the best designs differ in one or at most a few base pairs, e.g. by introducing an isolated base pair separating the large internal loops into two parts.
Nucleotide distribution in designed sequences
Paired | Unpaired | Total | |||||||||
Original data | 0.57 | 0.30 | 0.13 | 0.30 | 0.20 | 0.23 | 0.27 | 0.23 | 0.24 | 0.28 | 0.24 |
Frnakenstein | 0.55 | 0.36 | 0.09 | 0.32 | 0.31 | 0.09 | 0.29 | 0.25 | 0.29 | 0.19 | 0.26 |
RNAInverse | 0.46 | 0.41 | 0.14 | 0.29 | 0.25 | 0.21 | 0.25 | 0.23 | 0.24 | 0.26 | 0.26 |
Inv | 0.32 | 0.39 | 0.28 | 0.30 | 0.26 | 0.22 | 0.22 | 0.20 | 0.21 | 0.30 | 0.29 |
The other four methods have less bias in the base pair uses, although only Frnakenstein, RNAinverse, and Inv utilise wobble GU base pairs to any real degree. Indeed, the base pair distribution observed in the Frnakenstein distribution is very close to the distribution observed in the original data. There is, in the unpaired nucleotides, a mild overrepresentation of Cs and a mild under representation of Gs, though. This is perhaps due to the increased thermodynamic stability in CG base pairs– it is perhaps easy to have Cs unpaired, or Gs unpaired, but too many will form a pair eventually. RNAInverse, on the other hand, had an unpaired distribution very close to the real data set, but the base pair distribution is off a little. While it may in many cases be less important whether the distributions observed in the designed sequences are heavily biased, one consequence of this bias will be a reduced diversity in the set of solutions that are generated. In this sense, given Frnakenstein's performance against RNA Inverse and Inv, when application dictates a sensible nucleotide distribution, Frnakenstein is the clear winner.
Frnakenstein was designed with little focus on running time, choosing Python as implementation language for the ease of development and flexibility it offers. Additionally, the more advanced choices in mutation and recombination selection provide additional computational burden. Not only do you now have to calculate the full partition function for the thermodynamic model necessary to obtain Boltzman probabilities, but the selection of individuals for recombination and the recombination points themselves becomes considerably more computationally expensive. It is thus not overly surprising that among the methods tested Frnakenstein is one of the slowest. Only NUPACK: Design vies with Frnakenstein for bottom slot regarding speed. Even accounting for the fact that average running times should be divided by success ratio to get an approximate value of total time until first successful design, Frnakenstein and NUPACK: Design tend to be three to four orders of magnitude slower than the other four tested methods on some targets. For easy targets, Frnakenstein mitigates this concern by the application of RNAinverse for sequence initialisation. For applications where minimising time to find a successful design is the key priority, as opposed to nucleotide distribution, MODENA is a strong contender with run time at most a few minutes and a high rate of success on most of the Rfam targets.
RNAStrand data
Performance on RNASTRAND data set
Frnakenstein | MODENA | INFO-RNA | RNAinverse | NUPACK | Inv Frnakenstein | |
RNASTRAND-Refolded | 383 | 377 | 383 | 336 | 383 | 113 |
Length dependency of success rate
Range | 10-23 | 24-36 | 37-56 | 57-77 | 78-98 | 99-117 | 118-151 | 152-269 | 270-311 | 312-1037 |
Av. length | 17.9 | 29.4 | 46.2 | 69.8 | 86.7 | 108.0 | 127.7 | 205.6 | 293.8 | 528.0 |
Bin size | 38 | 34 | 36 | 41 | 34 | 36 | 35 | 36 | 36 | 37 |
Frnakenstein | 0.50 | 0.50 | 0.56 | 0.76 | 0.62 | 0.44 | 0.97 | 0.47 | 0.17 | 0.22 |
RNAinverse | 0.50 | 0.50 | 0.56 | 0.78 | 0.62 | 0.42 | 0.97 | 0.42 | 0.08 | 0.00 |
Inv | 0.44 | 0.38 | 0.47 | 0.51 | 0.15 | 0 | 0 | 0 | 0 | 0 |
In this paper we have described how to use a genetic algorithm approach to find useful solutions for the inverse RNA folding problem. The method allows a combination of the predicted minimum free energy structure and the computed Boltzmann distribution over the ensemble of structures to be used to guide the main aspects of the genetic algorithm, in particular mutation, recombination, and selection. It performed as well, or better, than the other methods tested on all benchmarks, without introducing strong biases in the composition of the designed sequences.
One of the major advantages of our method is that it allows multiple structures, either at identical or different conditions, to be specified as targets. To our knowledge, only one previously published method has this capability, and the software implementing this method is only available on request. While the benchmarks were done on two targets, there are no upper restrictions to how many targets can be aimed for.
Our method uses the RNA secondary structure prediction software as a black box. While a more efficient solution could be obtained by a more complex interaction with the folding software, allowing reuse of already computed values when mutating and recombining sequences, the chosen approach makes Frnakenstein much more flexible. The folding method can be replaced with relative ease, e.g. to use a grammar based method or a method capable of predicting structures with pseudoknots, simply by providing an alternative implementation of the module invoking and parsing the output from the folding software. Combining predictions from several folding methods, possibly using a multi-objective framework similar to MODENA, allows designs more robust to the uncertainties of structure prediction, and is an interesting direction for future research.
This work was carried out as part of the Oxford Summer School in Computational Biology, 2011, in conjunction with the Department of Plant Sciences and the Department of Zoology. Funding was provided by the EU COGANGS Grant. We thank S. Kelly for providing computational resources. JWJA would like to thank the EPSRC for funding.
Authors' Affiliations
- Pipas JM, McMahon JE: Method for predicting RNA secondary structure. Proc Nat Acad Sci USA 1975, 72(6):2017–2021. 10.1073/pnas.72.6.2017PubMed CentralView ArticlePubMedGoogle Scholar
- Markham NR, Zuker M: UNAFold: software for nucleic acid folding and hybridization. In Bioinformatics, Volume II. Structure, Function and Applications, number 453 in Methods in Molecular Biology, chapter 1. Edited by: Keith JM. Totowa: NJ: Humana Press; 2008:3–31. ISBN 978–1-60327–428–9 ISBN 978-1-60327-428-9Google Scholar
- Hofacker IL, Fontana W, Stadler PF, Bonhoeffer LS, Tacker M, Schuster P: Fast Folding and Comparison of RNA Secondary Structures. Monatshefte für Chemie 1994, 125: 167–188. 10.1007/BF00818163View ArticleGoogle Scholar
- Knudsen B, Hein JJ: RNA Secondary Structure Prediction Using Stochastic Context-Free Grammars and Evolutionary History. Bioinformatics 1999, 15(6):446–454. 10.1093/bioinformatics/15.6.446View ArticlePubMedGoogle Scholar
- Knudsen B, Hein J: Pfold: RNA secondary structure prediction using stochastic context-free grammars. Nucleic Acids Res 2003, 31(13):3423–3428. 10.1093/nar/gkg614PubMed CentralView ArticlePubMedGoogle Scholar
- Shapiro BA, Yingling YG, Kasprzak W, Bindewald E: Bridging the gap in RNA structure prediction. Curr Opin Struct Biol 2007, 17(2):157–165. 10.1016/j.sbi.2007.03.001View ArticlePubMedGoogle Scholar
- Gardner PP, Giegerich R: A comprehensive comparison of comparative RNA structure prediction approaches. BMC Bioinf 2004, 30(5):140.View ArticleGoogle Scholar
- Andronescu M, Fejes AP, Hutter F, Hoos HH, Condon A: A new algorithm for RNA secondary structure design. J Mol Biol 2004, 336: 607–624. 10.1016/j.jmb.2003.12.041View ArticlePubMedGoogle Scholar
- Busch A, Backofen R: INFO-RNA – a fast approach to inverse RNA folding. Bioinformatics 2006, 22(15):1823–1831. 10.1093/bioinformatics/btl194View ArticlePubMedGoogle Scholar
- Zadeh JN, Wolfe BR, Pierce NA: Nucleic acid sequence design via efficient ensemble defect optimization. J Comput Chem 2011, 32(3):439–452. 10.1002/jcc.21633View ArticlePubMedGoogle Scholar
- Gao JZM, Li LYM, Reidys CM: Inverse folding of RNA pseudoknot structures. Algorithms for Mol Biol 2010, 5: 27. 10.1186/1748-7188-5-27View ArticleGoogle Scholar
- Taneda A: MODENA: a multi-objective RNA inverse folding. Adv and App iBioinf and Chem 2011, 4: 1–12.Google Scholar
- Taneda A: Multi-objective genetic algorithm for pseudoknotted RNA sequence design. Front Genet 2012, 3: 36.PubMed CentralView ArticlePubMedGoogle Scholar
- Flamm C, Hofacker IL, Maurer-Stroh S, Stadler PF, Zehl M: Design of multistable RNA molecules. RNA 2001, 7(2):254–265. 10.1017/S1355838201000863PubMed CentralView ArticlePubMedGoogle Scholar
- Schwefel HP: Numerische Optimierung von Computer-Modellen mittels der Evolutionsstrategie. Mit einer vergleichenden Einführung in die Hill-Climbing- und Zufallsstrategie. Interdisciplinary Syst Research. 26. Basel - Stuttgart: Birkhäuser Verlag. 390pp. 1977.Google Scholar
- Aguirre-Hernández R, Hoos HH, Condon A: Computational RNA secondary structure design: empirical complexity and improved methods. BMC Bioinf 2007, 8: 34. 10.1186/1471-2105-8-34View ArticleGoogle Scholar
- Bubley R, Dyer M, Greenhill C, Jerrum M: On Approximately Counting Colourings of Small Degree Graphs. SIAM J Comput 1998, 29: 387–400.View ArticleGoogle Scholar
- Avihoo A, Churkin A, Barash D: RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences. BMC Bioinf 2011, 12: 319. 10.1186/1471-2105-12-319View ArticleGoogle Scholar
- Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, Bateman A: Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res 2005, 33: D121-D124.PubMed CentralView ArticlePubMedGoogle Scholar
- Andronescu M, Bereg V, Hoos HH, Condon A: RNA STRAND: The RNA secondary structure and statistical analysis database. BMC Bioinf 2008, 9: 340. 10.1186/1471-2105-9-340View ArticleGoogle Scholar
- Andersen ES, Rosenblad MA, Larsen N, Westergaard JC, Burks J, Wower IK, Wower J, Gorodkin J, Samuelsson T, Zwieb C: The tmRDB and SRPDB resources. Nucleic Acids Res 2006, 34(suppl. 1):D163-D168.PubMed CentralView ArticlePubMedGoogle Scholar
- Brown JW: The Ribonuclease P Database. Nucleic Acids Res 1999, 27: 314–314. 10.1093/nar/27.1.314PubMed CentralView ArticlePubMedGoogle Scholar
- Cannone J, Subramanian S, Schnare M, Collett J, D'Souza L, Du Y, Feng B, Lin N, Madabusi L, Muller K, Pande N, Shang Z, Yu N, Gutell R: The Comparative RNA Web (CRW) Site: an online database of comparative sequence and structure information for ribosomal, intron, and other RNAs. BMC Bioinf 2002, 3: 2. [M3: 10.1186/1471–2105–3-2] [M3: 10.1186/1471-2105-3-2] 10.1186/1471-2105-3-2View ArticleGoogle Scholar
- Sprinzl M, Horn C, Brown M, Ioudovitch A, Steinberg S: Compilation of tRNA sequences and sequences of tRNA genes. Nucleic Acids Res 1998, 26: 148–153. 10.1093/nar/26.1.148PubMed CentralView ArticlePubMedGoogle Scholar
- Westbrook J, Feng Z, Chen L, Yang H, Berman HM: The Protein Data Bank and structural genomics. Nucleic Acids Res 2003, 31: 489–491. 10.1093/nar/gkg068PubMed CentralView ArticlePubMedGoogle Scholar
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.


text:
A woman squadron leader of the IAF, Anandita Das, 29, has reportedly committed suicide by hanging herself from a ceiling fan at her residence at Jodhpur Air Force Station, 340 km from Jaipur, in Rajasthan.
Her husband, squadron leader Vishak Nair, found her body in the early hours of Wednesday.
According to primary investigation, the couple had a heated argument over chatting on Facebook on Tuesday night. Subsequently, Das and Nair went to separate rooms to sleep, the police said.
The IAF has ordered a probe. No suicide note has been found so far. Das was commissioned into the IAF in 2006 and was married to Nair in 2008.

subset: commoncrawl


text:
Luster ware Gondola Condiment Set German Lusterware set composed of gondola with salt, pepper and mustard pot in luster. Circa 1930-1940, boat is 8" in length, base is 2 1/4" at the widest, height is 3 3/4", Made in Germany the backstamp on the bottom is ANCO NY. This mark also appears on nodder S/P's so I would believe this to be an importer company. Set is German luster, in the most desirable color of mint green. The set is complete: salt/pepper, mustard pot with lid and spoon all of which sit in open wells of the gondola base. Shakers have original cork stoppers. The scene on the front was hand painted after firing. This is a little more unusual than the common decals or transfers placed on these when sold as souvenir items. The scene is of a teepee, mountains, pine tree and lake. Gondola edge, rings at the neck of salt and pepper and mustard pot body are done in burgundy. NO damage, chips, cracks, breaks or repairs. See photos of this and other sets we have for sale.
To purchase with MC or VISA please call Drury House Antiques 802-824-4395 EST or use PAYPAL We combine shipping and insurance on multiple orders
Need help with your order, Call us 802-8244395 EST 8 AM to 8 PM
Spring Sale Has Started, Porcelain Blowout 30 Day Sale Selling at Cost


text:
To compete with online sellers, some brick-and-mortar retailers have finally begun matching Internet prices, but according to a new ConsumerWorld.org survey, tricky provisions in their policies may limit their usefulness and shoppers' actual savings.
In recent weeks, both Best Buy and Target have temporarily expanded their existing price-matching policies to include some online stores in an effort to attract shoppers who might otherwise make their holiday purchases over the Internet to save money.
"Price-match guarantees can theoretically save shoppers a fortune, allowing them to shop locally but also get the advantage of lower online pricing," commented Edgar Dworsky, founder of Consumer World. However, Dworsky , who even successfully negotiated a price match on a coffin years ago, warned buyers that price-matching policies today have complicated requirements and exclusions that could trip up even the savviest of shoppers.
Some of the imaginative restrictions that limit the applicability of retailers' price-matching policies include restricting price matches to only certain specific websites; limiting the items subject to price matching to just certain categories such as electronics or appliances; excluding sales advertised on Black Friday, Cyber Monday, or anytime during Thanksgiving week; excluding other deeply discounted sales such as early bird, night owl, or limited quantity sales; and not allowing price matches after the purchase is made. A Wall Street Journal story even quoted a Best Buy internal document that said stores will only match online prices "when it makes sense."
Price-matching policies and low-price guarantees, which have been offered for decades, generally promise to match a local competitor's lower price for an identical in-stock item merely upon the presentation of a printed advertisement showing that lower price. Most policies provide price matches both before the sale and for a short time afterwards.
Some sellers like Walmart and Target have traditionally not even matched their own .com prices in-store, but a recent company announcement has changed that at least temporarily for Target.
Consumer World reviewed the price-match policies of major retailers for in-store purchases as posted on their websites, and discovered that once simple money back policies have morphed into complicated plans that may actually limit shoppers' savings:
Store | Basic Price Matching Policy | Deadline for Claims | Match Own
Website? |
Match Internet Sellers? | Key Exclusions, Limitations, Additional Details |
Best Buy | If you find a lower price on an identical in-stock product at a local retail competitor's store, a local Best Buy retail store or BestBuy.com, Best Buy will match that price. | Anytime during the return period, usually 30 days. | Yes | 20 specific sites only:
Amazon.com, Apple.com, Bhphotovideo.com, Buy.com, Circuitcity.com, CompUSA.com, Crutchfield.com, Dell.com, hhgregg.com, hp.com, homedepot.com, lowes.com, newegg.com, officedepot.com, officemax.com, Sears.com, Staples.com, Target.com, Tigerdirect.com, and walmart.com |
Nov. 18-26 excluded for online matches; Thanksgiving thru Cyber Monday excluded in-store; Items that are limited quantity, clearance or "deal of the day" excluded; only appliances and electronics, excluding accessories, covered for online price matches. Additional exclusions apply. |
Home Depot | If you find a current lower price on an identical, in-stock item from any local retailer, Home Depot will match the price and beat it by 10%. | At time of purchase. After purchase, at the discretion of the store, but extra 10% unlikely. | Yes, for your local Home Depot store's online prices, but extra 10% off not given. | No. | Matches only at time of purchase. After purchase, any match is at the discretion of the store. No matches on special orders or other Internet purchases. No blackout dates. |
Lowe's | If you find a lower price on an identical item at a local retail competitor, just bring in their current ad at the time of purchase, and Lowe's will beat their price by 10%. | At time of purchase for extra 10% to apply. Within 30 days after purchase for price match without 10%. | Yes, but extra 10% not given. | Yes, but extra 10% does not apply, and the cost of shipping is added to the competitor's price. | Special order and clearance sale items excluded. Will also match competitors' online prices including shipping for sales made at Lowes.com. No blackout dates. |
Sears | If you find a lower price on an identical brand and model number currently available for sale at another local competitor's retail store or at its online store (price plus shipping), Sears will match that price. | At time of purchase or up to 14 days after purchase | Yes, but not at Sears Outlet, nor for "online only" nor limited time online prices. | No, Internet-only sellers are excluded. However, online prices of local competitors will be matched if their store honors their own .com prices. | Items that are limited quantity, doorbusters, or on sale for less than six hours are excluded. Price matching does not apply Thanksgiving through Cyber Monday. Other exclusions apply. |
Staples | If you find a lower price on a new identical item, just show them the lower price when you buy the item at Staples and they will match the price. | At time of purchase or up to 14 days after purchase | Yes | Only Staples.com will match online stores' prices, and only these websites: Amazon, Best Buy, Costco, Dell, Hewlett Packard, Office Depot, Office Max, Quill, Medical Arts Press, Reliable, Sam's Club, Wal–mart, WB Mason and Xerox.
Staples stores will only match brick and mortar locations and Staples.com. Will not match "special event" sales, including their own. Complicated rules apply for rebate items and shipping. |
Target | If you find an identical in-stock item in a local competitor's printed ad that is priced lower than it is at your Target store, they will match the price. | Normally 7 days, but policy extended to Dec. 24 for the 2012 holiday season for purchases made Nov. 1 or after. | Normally, no, but will match Target.com for the 2012 holiday season. | Normally, no, but for in-store purchases, Target will match selected online sellers November 1 through December 16: Amazon.com, Walmart.com, BestBuy.com, ToysRUs.com and BabiesRUs.com. No price match for purchases made at Target.com. | Percent and dollar-off sales, sales requiring a coupon, limited time/quantity, and "deal of the day" sales excluded. Price matches to B&M competitors and Target.com from Nov. 1 – Dec. 24, excluding Nov 22-24. Additional restrictions apply. |
Toys "R" Us | If you find a lower price on an identical in-stock item at a competitor's store or on the Toys "R" Us website, they will match the price. | At time of purchase or up to 7 days after purchase | Yes, but not "online only" items at TRU.com | No, except for baby gear at a select list of national competitors. | Percent-off, doorbuster, limited quantity, "TRU online only" and coupon items excluded. Not valid on Black Friday. No price matches on TRU.com purchases. Other restrictions apply. |
Walmart | If you find a lower advertised price on an identical product at a local competitor, tell them at the register and they will match it, no ad required. | At time of purchase only. For online purchases, 7 days after purchase. | No | No. For walmart.com purchases, only price reductions found at walmart.com within 7 days of purchase will be honored, and not during Thanksgiving Week and Cyber Monday. | Percent-off and closeout sales excluded. In-store policy does not apply after purchase. |
Amazon | If you find a lower price on a television on another qualifying website or being sold by Amazon itself, they will refund the difference. | 14 days after shipment | Yes for TVs only. | Price matches on televisions only allowed on these sites: bestbuy.com, bhphotovideo.com, buy.com, buydig.com cdw.com, circuitcity.com, compusa.com,costco.com, dell.com, electronics-expo.com, frys.com, hhgregg.com, newegg.com, paulstv.com, 6ave.com, samsclub.com, sears.com, target.com, tigerdirect.com, us-appliance.com, vanns.com, walmart.com | Will only match prices on TVs after purchase. Time-limited sales including doorbusters and Black Friday are excluded. Other restrictions apply. |
Store | Basic Match Policy | Deadline | Own .com? | Match Internet Sellers? | Key Exclusions |
Consumer World suggests that shoppers read and understand a store's price-matching policy carefully before making a purchase or a claim. Some stores, despite their stated policy, will balk at doing a price match, so be prepared to argue your case with proof in hand. For stores that don't offer a formal low-price guarantee, a savvy shopper can often negotiate a lower price merely by citing a competitor's current price. If all else fails, use a credit card that has its own "sale price guarantee" benefit offering a refund if you find a lower price within 60 days.
[Tips and chart at: consumerworld.org/pages/pricematch2012prs.htm ]
Similar Posts:
- Target Price Matching Amazon And Other Internet Retailers Year-round
- 11 Retailers That Have The Best Return Policies
- 2012 Return Policies: Most Retailers Nice: Some Naughty
- Walmart "Wins" Many Worst Categories In Consumer Reports Latest Reader Survey
- Top 10 Tips to Bag a Bargain during 2015 Black Friday Week
- Some Major Retailers Making Returns More Difficult


text:
Dereham motorists face delays as roadworks progress
PUBLISHED: 12:10 13 August 2012
Archant © 2004
Motorists have been warned to expect traffic delays in parts of Dereham this week because of roadworks affecting some of the town's busiest thoroughfares.
Resurfacing of the Station Road/London Road mini-roundabout started yesterday, and work in London Road itself started today, Monday August 13.
The roads will be closed and diversions put in place while the job, which is expected to last between three and five days, is being done.
From Sunday August 19 workmen will resurface the Commercial Road/London Road mini-roundabout in Dereham, and the road will be closed.
The one-way restriction between the Cowper Road/Norwich Street junction and the car park will be suspended while work is being done. Traffic will be controlled at the junction and the car park entrance by stop-and-go boards.


text:
Health Insurance Quotes
9 ways to lower your health insurance premiums
You can shop around for health insurance quotes just as you would for better car insurance rates. And one of the goals of the Affordable Care Act is to make that comparison shopping easier. You can compare health plans through your state's marketplace by going to HealthCare.gov.
Here are ways to get the most for your health insurance dollar.
1. Stop smoking
Health care reform altered the insurance landscape by not allowing insurers to use gender or health conditions for pricing. But they can still charge more to smokers -- up to 50 percent more for the same plan.
2. Increase your deductible
Whether you are enrolled in a group or individual plan, the more you pay out of pocket, the less you will have to pay in premiums.
3. Change your co-insurance ratio
Your co-insurance ratio is how much you will pay after you have met your deductible.
A common ratio is 80/20. This means that after you pay your deductible toward health care expenses, your insurer pays 80 percent of the bill and you pay 20 percent. Changing this ratio so you pay more will mean a lower health insurance premium. Just as with raising your deductible, you have to weigh the costs versus risks.
4. Pair a high-deductible health plan with an HSA (Health Savings Account)
Often high-deductible plans are paired with a health savings account. Pre-tax contributions can be rolled into your plan each year. Employers and their employees may contribute to this account. Then you pay health care expenses from your Health Savings Account until it's exhausted.
Compare your anticipated health expenses with potential savings. The young and healthy could fare well with an HDHP paired with an HSA. This HSA Tax Savings Calculator from Golden Rule Insurance Co. helps you estimate your savings.
5. Choose an in-network doctor
Being happy with your choice of doctors starts when you research your plan options. You'll be looking at costs and benefits, but don't forget to look at the plan's provider network. if your favorite doctors aren't participating in the plan, you could face out-of-network charges.
6. Trade up group health insurance plans
If both you and your spouse have group health insurance plans available through work, calculate which one will cover both your needs at the lowest cost. For some people, group rates might not offer the best value -- an individual family plan might offer a cheaper option.
7. Regularly reassess your health insurance needs
You may be missing out on savings simply because you've stuck with the same plan year after year while your situation has changed.
"You should periodically reassess your insurance needs," suggests Laden. "Things you should think about include: Do you have children that go to the doctor often? Do you take a lot of prescription drugs? Are tax breaks important to you? Are you willing to assume the cost of routine health in exchange for much lower premiums?"
8. Lobby for health insurance savings at work
If you buy a group health plan through work, you may think you're stuck with whatever is offered every year.
But employees, especially those in smaller companies, can rally for better coverage options. There may be numerous "optional" benefits tacked on to your group health plan that are causing your group rate to skyrocket. If you and your co-workers agree that some coverage options are unnecessary (for instance, infertility treatment), ask your employer drop them at renewal time.
9. Don't miss out on subsidies
The Affordable Care Act defines the income levels at which you're eligible for a premium subsidy. You can only get the subsidies by buying a plan through your state's health insurance marketplace, and the subsidies come in the form of tax credits. Here's a chart to determine if you're eligible.
Ready to get a quote?
Get quick and easy health insurance quotes


text:
BP Comment Quick Links
November 28, 2012 Transaction AnalysisAdequate Scott!
Reportedly signed RHP Ryan Madson to a one-year deal. [11/27] In Ken Rosenthal's November 10 column, he wrote about Jerry Dipoto's attitude toward closers. To quote Rosenthal, quoting Dipoto, "Dipoto is not concerned with finding a pure closer, though he could trade for the Indians' Chris Perez or sign Japanese free-agent Kyuji Fujikawa." Madson is a true closer by any reasonable definition. He was one of the top ninth-inning men available last winter, though the market froze him out. Madson signed a one-year deal with the Reds before missing the season due to Tommy John surgery. When Madson is healthy, his fastball-changeup combination makes him one of the better relievers in the game. The Angels are in a good position to gamble on Madson returning to health. They have options like Ernesto Frieri, Jordan Walden, and Scott Downs available should Madson falter. Otherwise, the Angels have a nice cabal of relief arms.
Signed OF-R Jonny Gomes to a two-year deal worth $10 million. [11/21] When a reporter asked Gomes about protestors running onto the field last August, he shot back that he would clear the field himself. Adding, "There ain't nothing secret about my service." Indeed, Jonny; everyone knows about your raw strength and your ability to hit left-handed pitching. Not everyone knows about Gomes' career-high True Average last season. The outfielder owes Bob Melvin a nice steak dinner, as without his manager's careful micromanaging (Gomes reached 200-plus plate appearances and faced more than 50 percent left-handers for the first time in his career) he may have settled for another one-year deal. Instead, the eccentric Gomes is heading to Boston to take over for Cody Ross. It's unclear if John Farrell will take a similar approach, though Gomes' moon-shot tendencies and the Green Monster should result in some gaudy power numbers regardless. Farrell would also be wise to keep Gomes in left field as much as possible. The occasional misplay of a carom will be tough to stomach, but the less ground assigned to Gomes the better. As an added bonus, Gomes is considered a positive clubhouse presence, known for his one-liners and his willingness to drink from Dioner Navarro's protective cup. If that isn't enough to earn the respect of your peers then what is?
Signed RHP Scott Feldman to a one-year deal worth $6 million with another $1 million in incentives. [11/27] Ho hum, Jed Hoyer hands out another one-year deal to a veteran contributor. This one goes to Feldman, a tall, Amish-looking right-hander with starting and relieving experience. Feldman uses a four-pitch mix, relying heavily on his sinker and cutter, and mixing in curves and changeups. The best peripherals of his starting career allow room for optimism despite an ugly ERA last season: Scott Feldman's Numbers as a Starter
If you need a reason for the improvement, it could be because of Feldman's increased usage of his changeup. Whether that speaks to an increase in effectiveness or confidence (or an increased confidence because of its effectiveness) is unclear. Look for Feldman to take one of the back-end spots in the Cubs rotation. If all goes well, he should finish the year in someone else's rotation. If all goes poorly, he'll finish the year in a bullpen.
R.J. Anderson is an author of Baseball Prospectus. Follow @r_j_anderson
8 comments have been left for this article.


text:
Just common sense here, but a fan would still blow OUT no matter what direction it's facing.
Unless you mean that you may spill some into a now spillable area of your PC. There's plenty of areas of your PC you can accidentally spill things into.
Just common sense here, but a fan would still blow OUT no matter what direction it's facing.
Unless you mean that you may spill some into a now spillable area of your PC. There's plenty of areas of your PC you can accidentally spill things into.
None at all, it exhausts out the back so orientation wouldn't matter, I have mine fan up because it looks cooler.
if your PSU is bottom mounted then it can make airflow into the PSU kind of wonky. Top mounted and there's no difference at all
He means upside down, as in the fan pointing up/down in the bottom of the case, not mounted at the top/bottom of the case.
I don't know of any cases that allow options for mounting your PSU at the top and bottom.
I've got a HAF 912 with 2 200mm and 2 120mm, the top and back out and the front and side in.
The gromets can be put and the bottom and the PSU at the top
I mean if it's top mounted, making it upside down isn't gonna make a difference. if it's bottom mounted, upside down is weird shit
Howso, just draws air from the case, not the table/floor.
I gave Flux a try for a week and I think I hate it.
I swear it's making my eyestrain worse. And it only gets in the way. There's no "Disable until I say enable" option, there's only "Disable for an hour." (Discounting turning the program off.)
It is
I'v spent all day on it... uhg far to long
I was like that at first too, but I was too lazy to uninstall it
now i love it
It's not that terrible, but it was bad enough to warrant being formatted and deleted from my MBR.
They certainly won't match any color schemes, but they're fucking awesome.
It was legit making my eyes burn, I couldn't stand it.
I'll give windows 8 another try tomorrow morning.
I love dat fast boot.
I fucking hate clients.
So I get to work today, and guess what my assignment is?
The client has decided that he doesn't want users to be called "users". He wants them to be called "people". Not just at the interface level (which isn't even our job, thankfully), but in the code and database as well.
The primary database (there's three) has over two dozen tables with "user" in the name. And well over half of the sixty-eight tables in the entire system have a user_id column.
The worst part was that I couldn't do a simple global search/replace, because a) a few times user was actually correct ("CREATE USER isignedanndaandcanttellyouanactualusername ENCRYPTED PASSWORD nope"), and b) the framework we're using would have far too many false positives due to stuff like user agent mechanisms and comments pointing you to the user manual.
The best part was that I could turn to the guy next to me and ask how to make this ignore stuff in .svn folders:
And in under a second, he can sayCode:find . | xargs grep -il 'user' | sort | uniq
(I checked the man pages - there doesn't seem to be an easy option in find for 'ignore hidden files and folders', which was my first guess on how to do it)Code:find . | grep -v '\.svn' | xargs grep -il 'user' | sort | uniq
They perform pretty well from what I heard. You can also take them apart to spray paint it.
So at work, I was working (gasp)
And, being a software company, I was working on our program, specifically, automating the regression testing.
So we have this scheduling function that apparently logs every time it fires off, and I use the scheduler to help automate stuff, and the root directory of the program was taking forever to load.
I opened up cmd, did a dir of the folder, 66,200 files.
After a delete, it was left with 137.
Have you ever been at a large company?
The amount of internal email and information on a company intranet is massive.
It's not awful. Literally this is the first time my mother has said something like this.
Everything has been peachy. I really just hope I can get YT to a good point before my job ends.
When people say "peachy" I always think it's a negative thing because of how my dad would use that word.
"how was your day? "fucking peachy" ":("
Meaning the only conflict was my grades up till this point.
Grades are retarded.
My school said I failed math and some other class when I have proof I passed and they're too lazy to fix it.
As of today though I brought my GPA up to a 3.4, but I'm only half way though the semester. According to my school's records I have a 1.42 last semester despite me having proof I have a solid 3.0 UGHGGGGGYUHGFDfghddf
Also my prof for that office class accepted the grade. She's so nice.
I have yet to hear back on my "unanswered essay questions".
My art teacher runs a studio, and he was nice enough to let me take classes there for free if I wanted to just because of my financial situation.
What kind of class did you take there?
Torvalds knows how the Internet works:
I actually have no clue how any of that works.
I might actually have to, dunno how that'd exactly work. They're aware of situation and haven't done a thing for two months.
It sounds like it would be a minefield. The school probably has all the loopholes and restrictions figured out.
Yeah probably.
They can pretty much get away with it and I'll have to retake the two classes.


text:
Register | FAQ | Blowout Cards Shop | My iTrader | Forum Rules | Members List | Search | Today's Posts | Mark Forums Read |
FOOTBALL Post your Football Cards Hobby Talk |
LinkBack | Thread Tools | Display Modes |
01-10-2013, 06:04 PM | #1 (permalink) |
AMAZING Mailday. A little for everyone.
Got home from work to 7 bubble mailers. Most of this is PC but there are some amazing cards here:
First was this Beauty National Treasures Numbered 1/25 http://s216.beta.photobucket.com/use...tml?sort=4&o=2 Next was this awesome 1/1 (Stamped on Back) Romo Playoff Metalized http://s216.beta.photobucket.com/use...tml?sort=4&o=4 Am I the only one who thinks with a real QB Andre Roberts would be a beast? National Treasures RC Patch Auto http://s216.beta.photobucket.com/use...ml?sort=4&o=11 Another for the PC. 2010 Playoff Rookie Ticket Auto http://s216.beta.photobucket.com/use...ml?sort=4&o=12 Got this for 99 cents. 2012 Momentum RC Auto Ryan Lindley http://s216.beta.photobucket.com/use...ml?sort=4&o=18 A couple of trade cards. I've had this card at least 5 times. It trades well. http://s216.beta.photobucket.com/use...ml?sort=4&o=15 And this: http://s216.beta.photobucket.com/use...tml?sort=4&o=2 I saved the Best for last. Not many collect AZ Cardinals it seems: 2011 Absolute Ryan Williams Logo Patch Jersey 3/5 http://s216.beta.photobucket.com/use...ml?sort=4&o=14 http://s216.beta.photobucket.com/use...ml?sort=4&o=13 Today was a good day!
Bucket: http://s216.beta.photobucket.com/user/soberdick/library/ Last edited by hawaiisean; 01-10-2013 at 06:07 PM. |
Bookmarks |
Thread Tools | |
Display Modes | |


text:
In SpellForce 2 - Shadow Wars, the player takes over the role of the Avatar, preventing the world of Eo and its many races from being overrun by a sinister new enemy. You will be able to solve quests and overcome obstacles as in classical RPGs, but also experiences strategic challenges while leading armies as in an RTS - thus offering a complete synthesis of both genres in a perfect blend.
You as the Avatar will try to resist the invasion of the Pact, forcing you to forge new alliances to oppose them... but you soon realize that even more sinister forces are at work right within your own body. You will in turn lead each one of three factions, The Realm, The Clan and The Pact and build bases to gather resources and rally troops - to prepare for the epic battles that are the hallmark of SpellForce! You will also be supported by a band of heroes who are customizable with a multitude of unique skills, spells and a great variety of items, weapons and armor.
The forces of light and the minions of darkness will clash in 2006!
- Innovative Role Playing Strategy Genre
- Over 100 Avatar skills for individual characters and game-play style development
- Highly detailed & living fantasy worlds which react to the actions of the player
- Click'n'Fight: revolutionary control system that guarantees new tactical possibilities in battle
- Players will lead different fractions to victory, with 12 very different units consisting of infantry, cavalry and flyers
- Single-player campaign with 50+ hours of game-play with a gripping storyline and a wealth of sub-quests
- Different multi-player modes in over 30 stunning multi-player maps for Player vs. Player & Player vs. AI/Monsters, including exciting online interaction with intelligent and adaptive enemy AI
- Server based avatars gain levels & equipment and can be used in both, Player vs. Players and co-op multi-player games


text:
Hi Brandon,Nice picture with that ray of light. Can you tell me how the dynamic range is of the X100. I know it's better than a normal compact cam but does it do the same as an prosumer DSLR?Thanks in advance!!MarkThe Netherlands
One look at this image and I'd say the DR is rather large. I continue to be impressed with how flat the X100 images are out of camera. Definitely not for those adverse to processing but for the rest of us, the files look to have a ton of malleability.
yeah, i was amazed how well this camera did with snow shot exposures as shown in the official sample images. this camera makes me want to travel!
Oh, and nice photo Brandon!


text: Our Imaginary Boyfriend Mark Ruffalo Speaks Out For Women's RightsErin Gloria Ryan1/22/14 1:00pmFiled to: roe v worldmark ruffalocenter for reproductive rightsabortionabortion accesspro choicepro lifemarch for life4817EditPromoteShare to KinjaToggle Conversation toolsGo to permalinkMark Ruffalo, fantastic actor and boyfriend to one and all, has appeared in a new video wherein he explains his enduring support for Roe v. Wade, released just in time for the landmark Supreme Court ruling's 41st anniversary. AdvertisementThe video, produced by the Center for Reproductive Rights, isn't flashy — it's just 2 minutes of Mark Ruffalo saying what seems to me, as someone who is constantly surrounded by mostly people who agree that women are people who can be trusted to make the right decisions about what goes on within their own bodies, like basic, basic, no-brainer stuff. Like this:It becomes kind of a moral issue about who you are, and how you view the women in your life. There's a common sense and a wisdom and a decency in women that needs to be upheld and doesn't warrant being pushed back 30 years into the whole nightmare that brought about the abortion rights movement that we fought for, that we created laws around, that we codified into those laws. I just can't, as a man, I see no wisdom in going backwards. "Women: also people!" seems a depressingly bare bones premise to continue to have to argue, but: here we are. Think of what's going on right now in Texas, in Wisconsin, in Kansas, in the US House of Representatives. Think of what's going on today in Washington, DC, where tens of thousands of anti-abortion protesters are Marching For Life in the snow, protesting choice after rolling up to parking lots in cars baring license plates that ironically encourage people to "choose" life.AdvertisementThis isn't the first time Ruffalo has spoken out for the Center for Reproductive Rights; the husband and father of three has written and spoken in favor of abortion access for years, and he's far from the only celebrity speaking out in favor of choice (Sarah Silverman, Kerry Washington, and Amy Poehler have been particularly outspoken). But Ruffalo's continued visibility isn't about making boundary breaking policy arguments; it's about sharing his story and being a visible man in a movement that many men think has nothing to do with them. So, amen, imaginary boyfriend Mark Ruffalo, and happy 41st anniversary, Roe v. Wade. Here's hoping lawmakers don't continue their hard work of turning abortion access back into a feminist fantasy.Reply48 repliesLeave a reply


text:
This is your resource to discuss support topics with your peers, and learn from each other.
hi there.
When I update my database, it always hanged by prepare()! After 30 seconds, close() called finally.
Exception will be throwed if I operate the database during the 30 second before it closed.How Can I overcome this?
public void update(String sku, String name, int percent, int fileSize, int totalSize) { String sql = "UPDATE _download_table SET _percent = ?, _file_size = ?, _total_size = ? WHERE _name = " + "'" + name + "'"; Log.i(this, "update(): sql = " + sql + ", percent = " + percent); Database db = null; Statement s = null; try { db = open(); s = db.createStatement(sql); s.prepare(); s.bind( 1, percent ); s.bind( 2, fileSize ); s.bind( 3, totalSize ); s.execute(); } catch(Exception e) { Log.alert(this, "update(): Exception = " + e.getMessage()); } finally { Log.i(this, "update(): finally"); close(s); close(db); } }
[0.0] (i) DBHelper update(): sql = UPDATE _download_table SET _percent = ?, _file_size[0.0] = ?, _total_size = ? WHERE _name = 'IQ-Increase', percent = 100 [0.0] (i) DBHelper open()
//It takes about 30 secondsevery time.
[0.0] (i) DBHelper update(): finally [0.0] (i) DBHelper close()
# I tried to change the world, but I couldn't find the source code #
Solved! Go to Solution.
The only reason that prepare statement is thrown a exception is when ur sql statement is incorrect, not just ur UPDATE statement that u mentioned might be incorrect also chk the create table statement of that table, even that could be incorrect.... better u run the statements and chk using firefox sqlite extention....
# I tried to change the world, but I couldn't find the source code #
You need to be careful here.
If you are doing this in a listener call back Thread, then you are not running in your own Application context and you may be running on the Event Thread. As I understand it, all SQLite processing is blocking, so you should really run it off the Event Thread and you should really run it within your own Application. So I would encourage you to review the way you have implemented this in order to try to achieve these two objectives:
a) Run in your own Application
b) Run off the Event Thread
One way you can achieve (a) is using a Global Event Listener.
To achieve (b), just start a Thread to do the Update.
I suspect doing both of these will resolve your problem, unless you have different parts of your own Application that are locking the database. Sorry this is not an area of expertise, I hope some-else can help regarding database locking.
Hope this helps.
04-24-2012 05:59 AM - edited 04-24-2012 06:01 AM
That's it. Thanks for reply.
Think about this, I need to update download percent and record percent in database.
I will update download percent if user click to stop download, like this:
void stopDownload()
... update(_percent);
furthermore, if download complete I will update database as well, like this:
// implements CompleteListener
void onComplete()
...update(_percent); ...
update works fine in stopDownload beacause click() is in the UI thread,
but onComplete is invoked by download thread and thing became complecated.
# I tried to change the world, but I couldn't find the source code #
I am dubious abut this statement:
"update works fine in stopDownload because click() is in the UI thread,"
I do not see any reason why updating the database needs to run on the Event Thread. So something else in your update process is causing a problem, presumably because it does need to run on the Event Thread. And I'd guess that this requirement is what is stopping the onComplete.
So you could try using
UiApplication.getUiApplication().invokeLater( .... );
approach to running your onComplete, then it will run on the Event Thread. If this works, then you have some processing in there that requires the Event Thread. The SQL processing does not. I would move the SQL processing off the Event Thread.
# I tried to change the world, but I couldn't find the source code #
04-24-2012 07:04 AM - edited 04-24-2012 07:07 AM
invokeLater() did the trick at present! and I will do more test on it.
I wonder why sqlite will be hanged by statement.prepare() without using invokeLater(), you know I 'm not familiar with sqlite in multithread.
# I tried to change the world, but I couldn't find the source code #
As I mentioned earlier, I think there are things going on in your code that you don't know about. They might come back to bit you, they might not. I would learn about Threads and do the SQLite update using a Thread, but I guess if it working, on device, then you will probably get away with it.
I suspect it was not the prepare that was causing the problem, but if it was, it was the way it was being used rather than the statement itself.
Hi Thecr0w,
Can you please show the more code that how you implement the invokeLater for DB transactions.
I have used synchronized block around the database opeations.
But still I am getting 'sqlite Pending operation' at statement.prepare(), if calling DB operation from thread.


text:
The Basic School
Following Officer Candidates School, newly commissioned officers head to The Basic School to learn how to lead and inspire fellow Marines. Guided by the mentorship of experienced Marines, new officers develop the leadership, knowledge and esprit de corps that define the Marine Corps.
While The Basic School curriculum emphasizes the skills needed to command an infantry platoon, lessons here apply to Marine Officers in every leadership role. You will build a foundation of military knowledge and gain experience in the responsibilities of leadership, from accomplishing a mission to working with your Marines.
Training progresses through four phases; the first focuses on the individual technical and tactical skills required of an officer. In the second and third phases, you'll build on those skills and prepare to lead by example in command of a platoon. Finally, in the fourth phase, you will study the strategic organization that makes the Marine Corps our nation's expeditionary force in readiness, and will prepare you to apply your leadership skills in action.
Marine Corps Martial Arts
Disciplined training in hand-to-hand combatWater Survival
Practicing floatation techniques, waterproofing packs and avoiding hypothermia
Combat Intelligence
Collecting and interpreting information to gain a strategic advantage
Marine Corps History and Traditions
The legacy that distinguishes the Marine CorpsNavigation
Reading military maps and terrain features, developing situational awareness
Military Law
Legal and ethical standards for Marines, including the Uniform Code of Military Justice
Equipment, procedures and information security
Amphibious Operations
Strategies for maneuvers across land and sea
Aviation Support
Planning and communicating the use of aviation assets
Coordinating the movement of Marines and equipment to supply a mission
Field Engineering
Manipulating the terrain for offensive and defensive tactics
Organizing reconnaissance and security operations
Infantry Weapons
The M16 rifle, the M9 Beretta, rockets, missiles, mortars, machine guns and grenades
Supporting Arms
Planning efficient and effective weapon support for combat missions
Vertical Envelopment Operations
Planning combined arms air/ground maneuvers


text:
Ask a Question Please complete this question form so we can get back to you! Thank you.
Catalina Pottery Nautical Art Ware #C-358 Murex Shell A This item is no longer available This is an offering for a rarely seen Catalina Pottery Nautical Art Ware #C-358 shell art bowl. The glaze is satin ivory and gloss coral. Made in U.S.A. ink mark. This pristine example measures about 8-1/2" long and 5-3/4" high. Not a hint of use and has no nicks, chips, cracks or...
What is the maximum you'd pay for this?
$ Currently priced at $ 195.00.
How many is this for?
Any Questions?
Your Name
Thank you
Store Home · About Us · Contact · FAQ / Policies · Privacy · Security · TIAS home · Site Map · Tell a Friend! · Join our Mailing List ·
The Pottery Peddler Contact us! 11151 318th Place NECarnation, WA 98014United States Updated Sunday, March 26 2017Product descriptions copyright© 2017 The Pottery PeddlerAll else copyright© 1995-2017 TIAS.com All rights reserved.


text:
comScore unveils audience analytic
Online measurement firm comScore launched a "panel-centric hybrid" product for measuring digital audiences, to be implemented in August 2009.The service, Media Metrix 360, will combine the company's "two million person global panel" with website metrics, in order to "reconcile traffic metrics reported from client server-side and ad server data," according to a company release. "This new approach will effectively…provide unified numbers that are fully consistent with the ad server counts used for advertising payments," said Magid Abraham, president and CEO, in the statement. "In this sense, Media Metrix 360 represents the web's first true measurement 'currency.'"


text:
Agreement signed between Linn State Technical College and Lincoln University
An agreement between the two schools will make it faster for you to earn a degree
JEFFERSON CITY, Mo. - Two Mid-Missouri colleges are trying to help you get your degree faster. Linn State Technical College and Lincoln University signed an agreement that would allow students with an associate degree in computer technology at Linn State to get financial assistance for a bachelor's degree at Lincoln. Lincoln University is getting a $1-million grant to make this possible.
This is going to serve a total of about 130 students. Governor Jay Nixon says by the time these students get their bachelors degree at Lincoln, they will be ready to contribute in the real world immediately. They claim local businesses are clamoring for people qualified in information technology.
Nixon says the state's economy is getting better by the month. With this agreement between Lincoln University and Linn State it should help that trend continue.
"They'll be able to continue to move forward more quickly by articulating between these two organizations we can literally accelerate careers for jobs that exist and will exist in the near future here," Nixon says.
When students get their computer technology associates degree at Linn State, they have the opportunity to get a bachelors degree at Lincoln University. They could even get up to $7,500 in assistance. Local business leaders believe this is not only a big opportunity for students, but for their businesses too.
"As business partners, we've been working with the schools to try to define the hiring needs and the skill sets that we need in the area for our businesses," one of the business partners, Jill Hansen tells ABC 17 News.
College leaders say this should pay dividends for the local economy.
"Our students learn locally and stay local to provide our local business with a qualified workforce in information technology," Lincoln University Interim President Dr. Connie Hamacher says.
High school students also have a chance to participate in the program. They can get dual credits in computer technology and move through the college programs faster. Jefferson City, Helias, Fatima, Osage County schools are all participating.


text:
Ed Lauter, 74, a character actor who carved out a niche in the 1970s playing mostly heavies in movies and TV and kept up a busy schedule in recent years with appearances in Clint Eastwood's "Trouble With the Curve" and Oscar winner "The Artist," died Wednesday at his home in Los Angeles of mesothelioma, a form of cancer that affects tissue surrounding internal organs. Family spokesman Edward Lozzi announced his death.
"A lot of people say, 'I know you,' but they don't know my name," Lauter told The Times in 2012. "But I've had a great run."
The 6-foot-2, balding actor had memorable roles in "Family Plot" -- which was Alfred Hitchcock's final film, in 1976 -- along with "Born on the Fourth of July," "Seabiscuit," "Breakheart Pass," "Death Wish 3," "French Connection II" and "The Longest Yard," both the 1974 version and the 2005 remake about a football game pitting inmates against prison guards.
PHOTOS: Notable deaths of 2013
In "The Artist," which won the Academy Award for best picture in 2012, Lauter played Peppy's butler, and in "Trouble With the Curve," he portrayed a baseball scout and friend of Eastwood's character.
Edward Matthew Lauter was born Oct. 30, 1938, in Long Beach on New York's Long Island. He graduated from what was called the C.W. Post campus of Long Island University, where he majored in English and played basketball.
He studied acting and worked as a stand-up comic before landing a small part in the 1968 Broadway production of the boxing drama "The Great White Hope."
Lauter moved to Los Angeles to pursue television and movie work. His TV credits range from the early 1970s in "Mannix," "Kojak," "The Rockford Files" and the miniseries "How the West Was Won," into the '80s and '90s with "The A-Team," "Miami Vice," "Walker, Texas Ranger," and more recently in "ER," "Grey's Anatomy" and the Showtime series "Shameless."
Lauter nearly always stood out.
"Years ago, I was thinking about getting my nose changed," he said in the Times interview, "but I am so glad I didn't."
Roger Richman, 69, agent represented celebrities' estates
Tom Clancy, 66, author of spy thrillers made into movies
Oscar Hijuelos, 62, Pulitzer-winning author of 'Mambo Kings'
Twitter: @clairenoland
PHOTOS: Faces to watch 2014 | Movies
ENVELOPE: The latest awards buzz
DOCUMENTARIES: 10 best of 2013, and a new crop in 2014


text:
This entry was posted by JoeMartinFitness on November 13, 2011 at 9:03 pm, and is filed under Video. Follow any responses to this post through RSS 2.0. You can leave a response or trackback from your own site.
Getting it done right. Huntsville Adventure Boot Camp uses SafeUnsubscribe which reliably removes your email address from our lists.


text:
Painting Workshop: Blue Forest
This will be a 16 x 20 canvas painting. People of all ages are welcome. Please choose age/skill appropriate paintings when bringing children. Please call about Home School Student discounts available during our early classes: 423-321-2317. Price includes all materials, take-home canvas and artist's instruction. Feel free to bring any snacks you may want. Cancellations made within 48 hours are subject only to a credit.
Artsy-U of Chattanooga 5084, Suite 15 South Terrace, City of Chattanooga, Tennessee 37412 View Map


text:
Sponsored Posts
It's no secret that we're a little obsessed with NET-A-PORTER here at SMP. Just the mention of its name elicits all sorts of giddy, shop happy squeals from around the office. After all, it's THE go-to place for luxury fashion. But did you know they also have The Wedding Shop where you can find everything from your dream designer dress to the perfect honeymoon attire? Browsing through their insanely amazing selections is like waking up in wedding heaven surrounded by all things girly and fabulous. It's everything you'd expect from the world's premier online luxury fashion retailer and then some. Which is why it was nearly impossible to pick our favorite pieces (wait, we can't pick ALL of them?!) But somehow we managed and compiled four totally different yet equally gorgeous head-to-toe looks. So without further ado, here's our top picks for all you Classically Chic, Bohemian, Modern Minimalist, and Fashion Focused brides out there. Enjoy!
Classic Chic Bridal Look:
1. Berry Crystal Earrings / 2. Sophie Lace Gown / 3. Glass Pearl Embellished Tulle Bridal Veil / 4. Satin Platform Peep-Toe Pumps / 5. Photography by Elizabeth Messina
Bohemian Bridal Look:
1. Tulle Trimmed Lace Gown / 2. Photography by Jose Villa / 3. Metallic Leather Sandals / 4. Rose Gold Diamond Bracelet / 5. Poppy Embellished Dress
Modern Minimalist Bridal Look:
1. Gold Pyramid Stud Hoop Earrings / 2. Agnes Pleated Crepe-Jersey Gown / 3. Photography by Erin Hearts Court / 4. Palais Satin Peep-Toe Pumps / 5. Rose Gold-Plated Crystal Cone Bracelet
Fashion Focused Bridal Look:
1. Pyramid 18-karat Gold Diamond Stud Earrings/ 2. Top Bun Photography by Jessica May Photography / 3. Artemis One-Shoulder Silk-Georgette Dress / 4. 24-Karat Gold-Plated Leaf Necklace / 5. Rosette-embellished Satin Sandals


text:
Xp68.tk Whois Record
(Updated 1913 days ago)
Registration Information
ICANN Registrar : | |
Referral URL : | |
Whois Server : | tk.whois-servers.net |
Nameservers : | |
Registrar Status : |
Whois Contact Information
Rights restricted by copyright. See http://www.dot.tk/en/pageF00.html Domain name: XP68.TK Organisation: BV Dot TK Dot TK administrator P.O. Box 11774 1001 GT Amsterdam Netherlands Phone: +31 20 5315725 Fax: +31 20 5315721 E-mail: abuse: firstname.lastname@example.com Domain Nameservers: NS01.DOT.TK NS02.DOT.TK NS03.DOT.TK NS04.DOT.TK Your selected domain name is a Free Domain. That means that, according to the terms and conditions of Free Domain domain names the registrant is BV Dot TK in Amsterdam, Netherlands. Due to restrictions in Dot TK's Privacy Statement personal information about the user of the domain name cannot be released. ABUSE OF A DOMAIN NAME If you want to report abuse of this domain name, please send a detailed email with your complaint to firstname.lastname@example.com. In most cases Dot TK responds to abuse complaints within one business day. COPYRIGHT INFRINGEMENT If you want to report a case of copyright infringement, please send an email to firstname.lastname@example.com, and include the full name and address of your organization. Within 5 business days copyright infringement notices will be investigated. Record maintained by: Dot TK Domain Registry |


text:
With its precision and control, the Vita-Prep is an invaluable tool on the line. The Variable Speed Control allows for chopping, grinding, puréeing, or blending dense ingredients at exactly the right speed.
Variable Speed Control
The manually-operated dial provides precise speed control to regulate the texture of ingredients from a coarse chop to the smoothest purée.
2-HP Motor
Trust our durable, ≈2 peak output horsepower motor to deliver exceptional performance through the demands of a commercial kitchen, blending even the toughest whole-food ingredients with ease.
Our Tamper allows you to blend thick and frozen mixtures without stopping the machine. Its collar is specially designed to prevent it from coming in contact with the blades.
Durable Container
Our durable 64-oz. high-impact container comes with a removable lid plug, making it easy to add ingredients while blending.
Product Specifications
≈2 peak output horsepower motor
120 V, 50/60 Hz, 11.5 Amps
12.2 lb. (13.8 lb. with box)
20.3 x 8.0 x 9.0 in. (H x W x D)
The Vita-Prep motor base is backed by a three-year component warranty with one year on labor. Blade assembly, container, etc., are covered by a one-year warranty. For more information regarding this warranty, please contact your local dealer or a Vitamix service representative at +1.440.782.2450.
Note: Outside the U.S., refer all warranty inquiries to your in-country Vitamix distributor.
Product Resources
Having a Problem?
Contact Customer Service


text:
My second niece, Abigail Cora, was born a couple of days ago to my brother Colin and his wife Stephanie! She is a beautiful little sweetheart and we were so excited to meet her today!
The following two tabs change content below.
I'm Heather, a married mama of two teen girls, a stillborn baby girl (7/1/12), and a sweet and wild preschool girl (4/2/14). I've been blogging at The Destiny Manifest since 2001. I like to write about appreciating all of the beautiful little things that surround us, particularly in the face of grief, infant loss and mental health issues. Every day is an adventure!
Latest posts by Heather O. (see all)
- Living My Life & Finding The Words - July 8, 2016
- Katie is One Years Old! - April 2, 2015
- The Great Bedroom Swap… and Unschooling - March 24, 2015
- Homeschool: The World Is Our Classroom - March 9, 2015


text:
Urinary Disorders |
Dilute Urine and Overactive Bladder02/18/2009 |
I am a 25 year old female, I have had an "overactive bladder" urinating 4-9 times a day and 4-10 times at night. I don`t drink much fluids maybe 40oz +-12oz a day, since more makes me urinate more. Lately I`ve been noticing that my urine is completely dilute (no color whatsoever) this has been for 2 days. I have noticed episodes of this is the past, but then a few days later (or when I feel dehydrated) my urine is concentrated and yellow again. I`ve been tested for diabetes mellitus, had a bladder US and lab work for BUN and creat and told everything is fine. I also get horrible migraines that are not able to be controlled by medication as fell as fatigue and sleep difficulties. I am just windering if something else could be going on? I am told the bladder issue is just overactive bladder. I was given medication but had to stop because of the horrible dry mouth.
The color of the urine may reflect your hydration status or some of the dyes from the food that you have eaten. A very clear, watery urine, generally is a dilute urine. It is difficult to determine the etiology of the frequency you describe. I would suggest that you be seen and examined by a urologist.
Donald R Bodner, MD Professor of Urology School of Medicine Case Western Reserve University |