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22 Jan 2014: Hampton J, Lladser ME (2014) Correction: Estimation of Distribution Overlap of Urn Models. PLOS ONE 9(1): 10.1371/annotation/cd4610af-3595-4ea2-9409-71770712f2a9. https://doi.org/10.1371/annotation/cd4610af-3595-4ea2-9409-71770712f2a9 View correction
A classical problem in statistics is estimating the expected coverage of a sample, which has had applications in gene expression, microbial ecology, optimization, and even numismatics. Here we consider a related extension of this problem to random samples of two discrete distributions. Specifically, we estimate what we call the dissimilarity probability of a sample, i.e., the probability of a draw from one distribution not being observed in draws from another distribution. We show our estimator of dissimilarity to be a -statistic and a uniformly minimum variance unbiased estimator of dissimilarity over the largest appropriate range of . Furthermore, despite the non-Markovian nature of our estimator when applied sequentially over , we show it converges uniformly in probability to the dissimilarity parameter, and we present criteria when it is approximately normally distributed and admits a consistent jackknife estimator of its variance. As proof of concept, we analyze V35 16S rRNA data to discern between various microbial environments. Other potential applications concern any situation where dissimilarity of two discrete distributions may be of interest. For instance, in SELEX experiments, each urn could represent a random RNA pool and each draw a possible solution to a particular binding site problem over that pool. The dissimilarity of these pools is then related to the probability of finding binding site solutions in one pool that are absent in the other.
Citation: Hampton J, Lladser ME (2012) Estimation of Distribution Overlap of Urn Models. PLoS ONE 7(11): e42368. https://doi.org/10.1371/journal.pone.0042368
Editor: Yu Zhang, Pennsylvania State University, United States of America
Received: March 19, 2012; Accepted: July 6, 2012; Published: November 6, 2012
Copyright: © 2012 Hampton, Lladser. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was partially supported by the National Science Foundation grant DMS #0805950, the National Institutes of Health (HG4872), and the Crohns and Colitis Foundation of America. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
An inescapable problem in microbial ecology is that a sample from an environment typically does not observe all species present in that environment. In [14], this problem has 1been recently linked to the concepts of coverage probability (i.e. the probability that a member from the environment is represented in the sample) and the closely related discovery or unobserved probability (i.e. the probability that a previously unobserved species is seen with another random observation from that environment). The mathematical treatment of coverage is not limited, however, to microbial ecology and has found applications in varied contexts, including gene expression, microbial ecology, optimization, and even numismatics.
The point estimation of coverage and discovery probability seem to have been first addressed by Turing and Good [2] to help decipher the Enigma Code, and subsequent work has provided point predictors and prediction intervals for these quantities under various assumptions [1], [3]–[5].
Following Robbins [6] and in more generality Starr [7], an unbiased estimator of the expected discovery probability of a sample of size is(1)where is the number of species observed exactly -times in a sample with replacement of size . Using the theory of U-statistics developed by Halmos [8], Clayton and Frees [9] show that the above estimator is the uniformly minimum variance unbiased estimator (UMVUE) of the expected discovery probability of a sample of size based on an enlarged sample of size .
A quantity analogous to the discovery probability of a sample from a single environment but in the context of two environments is dissimilarity, which we broadly define as the probability that a draw in one environment is not represented in a random sample (of a given size) from a possibly different environment. Estimating the dissimilarity of two microbial environments is therefore closely related to the problem of assessing the species that are unique to each environment, and the concept of dissimilarity may find applications to measure sample quality and allocate additional sampling resources, for example, for a more robust and reliable estimation of the UniFrac distance [10], [11] between pairs of environments. Dissimilarity may find applications in other and very different contexts. For instance, in SELEX experiments [12]–a laboratory technique in which an initial pool of synthesized random RNA sequences is repeatedly screened to yield a pool containing only sequences with given biological functions–the dissimilarity of two RNA pools corresponds to the probability of finding binding site solutions in one pool that are absent in the other.
In this manuscript, we study an estimator of dissimilarity probability similar to Robbins' and Starr's statistic for discovery probability. Our estimator is optimal among the appropriate class of unbiased statistics, while being approximately normally distributed in a general case. The variance of this statistic is estimated using a consistent jackknife. As proof of concept, we analyze samples of processed V35 16S rRNA data from the Human Microbiome Project [13].
Probabilistic Formulation and Inference Problem
To study dissimilarity probability, we use the mathematical model of a pair of urns, where each urn has an unknown composition of balls of different colors, and where there is no a priori knowledge of the contents of either urn. Information concerning the urn composition is inferred from repeated draws with replacement from that urn.
In what follows, and are independent sequences of independent and identically distributed (i.i.d.) discrete random variables with probability mass functions and , respectively. Without loss of generality we assume that and are supported over possibly infinite subsets of , and think of outcomes from these distributions as "colors": i.e. we speak of color-, color-, etc. Let denote the set of colors such that , and similarly define . Under this perspective, denotes the color of the -th ball drawn with replacement from urn-. Similarly, is the color of the -th ball drawn with replacement from urn-. Note that based on our formulation, distinct draws are always independent.
The mathematical analysis that follows was motivated by the problem of estimating the fraction of balls in urn- with a color that is absent in urn-. We can write this parameter as(2)where
(3)The parameter measures the proportion of urn- which is unique from urn-. On the other hand, is a measure of the effectiveness of -samples from urn- to determine uniqueness in urn-. This motivates us to refer to the quantity in (2) as the dissimilarity of urn- from urn-, and to the quantity in (3) as the average dissimilarity of urn- relative to -draws from urn-. Note that these parameters are in general asymmetric in the roles of the urns. In what follows, urns- and - are assumed fixed, which motivates us to remove subscripts and write instead of .
Unfortunately, one cannot estimate unbiasedly the dissimilarity of one urn from another based on finite samples, as stated in the following result. (See the Materials and Methods section for the proofs of all of our results).
Theorem 1 (No unbiased estimator of dissimilarity.) There is no unbiased estimator of based on finite samples from two arbitrary urns- and -.
Furthermore, estimating accurately without further assumptions on the compositions of urns- and - seems a difficult if not impossible task. For instance, arbitrarily small perturbations of urn- are likely to be unnoticed in a sample of a given size from this urn but may drastically affect the dissimilarity of other urns from urn-. To demonstrate this idea, consider a parameter and let , and . If then while, for each , .
In contrast with the above, for fixed , depends continuously on e.g. under the metricwhere denotes the total variation of a signed measure over such that . This is the case because
The above implies that is continuous with respect to any metric equivalent to . Many such metrics can be conceived. For instance, if denotes the probability measure associated with samples with replacement from urn- that are independent of samples with replacement from urn- then is also continuous with respect to any of the metrics , with , because
Because of the above considerations, we discourage the direct estimation of and focus on the problem of estimating accurately.
Consider a finite number of draws with replacement and , from urn- and urn-, respectively, where are assumed fixed. Using this data we can estimate , for , via the estimator:(4)where
(5)We refer to as the -statistics summarizing the data from both urns. Due to the well-known relation: , at most of these estimators are non-zero. This sparsity may be exploited in the calculation of the right-hand side of (4) over a large range of 's.
Our statistic in is the U-statistic associated with the kernel , where is used to denote the indicator function of the event within the brackets (Iverson's bracket notation). Following the approach by Halmos in [8], we can show that this U-statistic is optimal amongst the unbiased estimators of for . We note that no additional samples from either urn are necessary to estimate unbiasedly over this range when . This contrasts with the estimator in equation (1), which requires sample enlargement for unbiased estimation of discovery probability of a sample of size .
Theorem 2 (Minimum variance unbiased estimator.) If and then is the unique uniformly minimum variance unbiased estimator of . Further, no unbiased estimator of exists for or .
Our next result shows that converges uniformly in probability to over the largest possible range where unbiased estimation of the later parameter is possible, despite the non-Markovian nature of when applied sequentially over . The result asserts that is likely to be a good approximation of , uniformly for , when and are large. The method of proof uses an approach by Hoeffding [14] for the exact calculation of the variance of a -statistic.
Theorem 3 (Uniform convergence in probability.) Independently of how and tend to infinity, it follows for each that(6)
We may estimate the variance of for via a leave-one-out or also called delete- jackknife estimator, using an approach studied by Efron and Stein [15] and Shao and Wu [16].
To account for variability in the -data through a leave-one-out jackknife estimate, we require that and let(7)
On the other hand, to account for variability in the -data, consider for and the statistics(8)
Clearly, ; in particular, the -statistics are a refinement of the -statistics. Define and, for , define(9)where
Our estimator of the variance of is obtained by summing the variance attributable to the -data and the -data and is given by(12)for ; in particular, is our jackknife estimate of the standard deviation of .
To assess the quality of as an estimate of the variance of and the asymptotic distribution of the later statistic, we require a few assumptions that rule out degenerate cases. The following conditions are used in the remaining theorems in this section:
- .
- there are at least two colors in that occur in different proportions in urn-; in particular, the conditional probability is not a uniform distribution.
- urn- contains at least one color that is absent in urn-; in particular, .
- and grow to infinity at a comparable rate i.e. , which means that there exist finite constants such that , as tend to infinity.
Conditions (a–c) imply that has a strictly positive variance and that a projection random variable, intermediate between and , has also a strictly positive variance. The idea of projection is motivated by the analysis of Grams and Serfling in [17].
Condition (d) is technical and only used to show that the result in Theorem 5 holds for the largest possible range of values of namely, for . See [18] for results with uniformity related to Theorem 4, as well as uniformity results when condition (d) is not assumed.
Because the variance of , from now on denoted , and its estimate tend to zero as and increase, the unnormalized consistency result is unsatisfactory. As an alternative, we can show that is a consistent estimator relative to , as stated next.
Theorem 4 (Asymptotic consistency of variance estimation.) If conditions (a)–(c) are satisfied then, for each and , it applies that(13)
Finally, under conditions (a)–(d), we show that is asymptotically normally distributed for all , as and increase at a comparable rate.
Theorem 5 (Asymptotic normality.) Let i.e. has a standard normal distribution. If conditions (a)–(d) are satisfied then(14)for all real number .
The non-trivial aspect of the above result is the asymptotic normality of when , e.g. , as the results we have found in the literature [14],[19],[20] only guarantee the asymptotic normality of our estimator of for fixed . We note that, due to Slutsky's theorem [21], it follows from (13) and (14) that the ratiohas, for fixed , approximately a standard normal distribution when and are large and of a comparable order of magnitude.
As proof of concept, we use our estimators to analyze data from the Human Microbiome Project (HMP) [13]. In particular, our samples are V35 16S rRNA data, processed by Qiime into an operational taxonomic unit (OTU) count table format (see File S1). Each of the samples analyzed have more than successfully identified bacteria (see File S2). We sort these samples by the body location metadata describing the origin of the sample. This sorting yields the assignments displayed in Table 1.
We present our estimates of for all possible sample comparisons in Figure 1, i.e., we estimate the average dissimilarity of sample- relative to the full sample-. Due to (4), observe that . At the given sample sizes, we can differentiate four broad groups of environments: stool, vagina, oral/throat and skin/nostril. We differentiate a larger proportion of oral/throat bacteria found in stool than stool bacteria found in the oral/throat environments. We may also differentiate the throat, gingival and saliva samples, but cannot reliably differentiate between tongue and throat samples or between the subgingival and supragingival plaques. On the other hand, the stool samples have larger proportions of unique bacteria relative to other stool samples of the same type, and vaginal samples also have this property. In contrast the skin/nostril samples have relatively few bacteria that are not identified in other skin/nostril samples.
Heat map of sorted by site location metadata. Here, the -axis denotes the sample from the environment corresponding to urn-, and similarly for the -axis. The entries on the diagonal are set to zero.
The above effects may be a property of the environments from which samples are taken, or an effect of noise from inaccurate estimates due to sampling. To rule out the later interpretation, we show estimates of the standard deviation of based on the jackknife estimator from (12) in Figure 2. As is zero, the error estimate is given by . We see from (7), with , that
Heat map of sorted by site location metadata. Here, the -axis also denotes the sample from the environment corresponding to urn-, and similarly for the -axis, and the entries on the diagonal are again set to zero.
Assuming a normal distribution and an accurate jackknife estimate of variance, will be in the interval with at least approximately 95% confidence, for any choice of sample comparisons in our data; in particular, on a linear scale, we expect at least 95% of the estimates in Figure 1 to be accurate in at least the first two digits.
As we mentioned earlier, estimating accurately is a difficult problem. We end this section with two heuristics to assess how representative is of , when urn- has at least two colors and at least one color in common with urn-. First, observe that:(15)
In particular, is a strictly concave-up and monotonically decreasing function of the real-variable . Hence, if is close to the asymptotic value , then should be of small magnitude. We call the later quantity the discrete derivative of at . Since we may estimate the discrete derivative from our data, the following heuristic arises: relatively large values of are evidence that is not a good approximation of .
Figure 3 shows the heat map of for each pair of samples. These estimates are of order for the majority of the comparisons, and spike to for several sample- of varied environment types, when sample- is associated with a skin or vaginal sample. In particular, further sampling effort from environments associated with certain vaginal, oral or stool samples are likely to reveal bacteria associated with broadly defined skin or vaginal environments.
Heat map of , sorted by site location metadata, following the same conventions as in the previous figures.
Another heuristic may be more useful to assess how close is to , particularly when the previous heuristic is inconclusive. As motivation, observe that , because of the identity in (15), where
Furthermore, , where is certain finite constant. We can justify this approximation only when is well approximated by a linear function of , in which case we let denote the estimated value for obtained from the linear regression. Since , the following more precise heuristic comes to light: is a good approximation of if the linear regression of for near gives a good fit, is small relative to , and is also small.
To fix ideas we have applied the above heuristic to three pairs of samples: , and , with each ordered pair denoting urn- and urn-, respectively. As seen in Table 2 for these three cases, is at least 14-times larger than ; in particular, due to the asymptotic normality of the later statistic, an appropriate use of the heuristic is reduced to a good linear fit and a small value. In all three cases, was computed from the estimates , with .
For the -pair, and the regression error, measured as the largest absolute residual associated with the best linear fit, are zero to machine precision, suggesting that is a good approximation of . This is reinforced by the blue plot in Figure 4. On the other hand, for the -pair, the regression error is small, suggesting that the linear approximation is good for . However, because , we cannot guarantee that is a good approximation of . In fact, as seen in the red-plot in Figure 4, , with , exposes a steady and almost linear decay that suggests that may be much smaller than . Finally, for the -pair, the regression error is large and the heuristic is therefore inconclusive. Due to the green-plot in Figure 4, the lack of fit indicates that the exponential rate of decay of to has not yet been captured by the data from these urns. Note that the heuristic based on the discrete derivative shows no evidence that is far from .
Plots of , with , for three pairs of samples of the HMP data.
Materials and Methods
Here we prove the theorems given in the Results section. The key idea to prove each theorem may be summarized as follows.
To show Theorem 1, we identify pairs of urns for which unbiased estimation of is impossible for any statistic. To show Theorem 2, we exploit the diversity of possible urn distributions to show that there are relatively few unbiased estimators of and, in fact, there is a single unbiased estimator that is symmetric on the data. The uniqueness of the symmetric estimator is obtained via a completeness argument: a symmetric statistic having expected value zero is shown to correspond to a polynomial with identically zero coefficients, which themselves correspond to values returned by the statistic when presented with specific data. The symmetric estimator is a U-statistic in that it corresponds to an average of unbiased estimates of , based on all possible sub-samples of size and from the samples of urn- and -, respectively. As any asymmetric estimator has higher variance than a corresponding symmetric estimator, the symmetric estimator must be the UMVUE.
To show Theorem 3 we use bounds on the variance of the U-statistic and show that, uniformly for relatively small , converges to in the -norm. In contrast, for relatively large values of , we exploit the monotonicity of and to show uniform convergence.
Finally, theorems 4 and 5 are shown using an approximation of by sums i.i.d. random variables, as well as results concerning the variance of both and its approximation. In particular, the approximation satisfies the hypotheses the Central Limit Theorem and Law of Large Numbers, which we use to transfer these results to .
In what follows, denotes the set of all probability distributions that are finitely supported over .
Proof of Theorem 1
Consider in probability distributions of the form , and , where is a given parameter. Any statistic which takes as input draws from urn- and draws from urn- has that is a polynomial of degree at most in the variable ; in particular, it is a continuous function of over the interval . Since has a discontinuity at over this interval, there exists no estimator of that is unbiased over pairs of distributions in .
We use lemmas 6–11 to first show Theorem 2. The method of proof of this theorem follows an approach similar to the one used by Halmos [8] for single distributions, which we extend here naturally to the setting of two distributions.
Our next result implies that no uniformly unbiased estimator of is possible when using less than one sample from urn- and samples from urn-.
Lemma 6 If is unbiased for for all , then and .
Proof. Consider in probability distributions of the form , , and , where are arbitrary real numbers. Clearly, is a linear combination of polynomials of degree in and in and, as a result, it is a polynomial of degree at most in and in . Since has degree in and in , and is unbiased for , we conclude that and .
The form of given in equation (4) is convenient for computation but, for mathematical analysis, we prefer its -statistic form associated with the kernel function .
In what follows, denotes the set of all functions that are one-to-one.
Proof. Fix and suppose that color occurs -times in . If then any sublist of size of contains , hence , for all . On the other hand, if then . Since the rightmost sum only depends on the number of times that color was observed in , we may use the -statistics defined in equation (5) to rewrite:
The right-hand side above now corresponds to the definition of given in equation (4).
In what follows, we say that a function is -symmetric whenfor all and permutations and of and , respectively. Alternatively, is -symmetric if and only if it may be regarded a function of , where and correspond to the order statistics and , respectively. Accordingly, a statistic of is called -symmetric when it may be represented in the form , for some -symmetric function . It is immediate from Lemma 7 that is -symmetric.
The next result asserts that the variance of any non-symmetric unbiased estimator of may be reduced by a corresponding symmetric unbiased estimator. The proof is based on the well-known fact that conditioning preserves the mean of a statistic and cannot increase its variance.
Lemma 8 An asymmetric unbiased estimator of that is square-integrable has a strictly larger variance than a corresponding -symmetric unbiased estimator.
Proof. Let denote the sigma-field generated by the random vector and suppose that the statistic is unbiased for and square-integrable. In particular, is a well-defined statistic and there is an -symmetric function such that . Clearly, is unbiased for and -symmetric. Since , Jensen's inequality for conditional expectations [22] implies that , with equality if and only if is -symmetric.
Since is -symmetric and bounded, the above lemma implies that if an UMVUE for exists then it must be -symmetric. Next, we show that there is a unique symmetric and unbiased estimator of , which immediately implies that is the UMVUE.
In what follows, denote integers. We say that a polynomial is -homogeneous when it is a linear combination of polynomials of the form , with and . Furthermore, we say that satisfies the partial vanishing condition if whenever , and .
The next lemma is an intermediate step to show that a -homogeneous polynomial which satisfies the partial vanishing condition is the zero polynomial, which is shown in Lemma 10.
Lemma 9 If is a -homogeneous polynomial in the real variables , with , that satisfies the partial vanishing condition, then whenever , and .
Proof. Fix such that and and observe thatbecause is a -homogeneous polynomial. Notice now that the right hand-side above is zero because satisfies the partial vanishing condition.
Lemma 10 Let be a -homogeneous polynomial in the real variables , with . If satisfies the partial vanishing condition then identically.
Proof. We prove the lemma using structural induction on for all .
If then a -homogeneous polynomial must be of the form , for an appropriate constant . As such a polynomial satisfies the partial-vanishing condition only when , the base case for induction is established.
Next, consider a -homogeneous polynomial , with , that satisfies the partial vanishing condition, and let denote its degree with respect to the variable . In particular, there are polynomials in the variables such that
Now fix such that and . Because satisfies the partial vanishing condition, Lemma 9 implies that for all . In particular, for each , whenever , and . Thus each satisfies the partial vanishing condition. Since is a -homogeneous polynomial, the inductive hypothesis implies that identically and hence identically. The same argument shows that if , with , is a -homogeneous polynomial that satisfies the partial vanishing condition then identically, completing the inductive proof of the lemma.
Our final resultbefore proving Theorem 2 implies that cannot admit more than one symmetric and unbiased estimator. Its proof depends on the variety of distributions in , and uses the requirement that our estimator must be unbiased for any pair of distributions chosen from .
Lemma 11 If is an -symmetric function such that , for all , then identically.
Proof. Consider a point and define and as the cardinalities of the sets and , respectively. Furthermore, let denote the distinct elements in the set and define to be the number of times that appears in this set. Furthermore, let be a probability distribution such that and define . In a completely analogous manner define , , and .
Notice that is a polynomial in the real variables that satisfies the hypothesis of Lemma 10; in particular, this polynomial is identically zero. However, because is -symmetric, the coefficient of in isimplying that .
Proof of Theorem 2
From Lemma 8, as we mentioned already, if the UMVUE for exists then it must be -symmetric. Suppose there are two -symmetric functions such that and are unbiased for . Applying Lemma 11 to shows that , and admits therefore a unique symmetric and unbiased estimator. From Lemma 7, is -symmetric and unbiased for hence it is the UMVUE for . From Lemma 6, it follows that no unbiased estimator of exists for or .
Our next goal is to show Theorem 3, for which we prove first lemmas 12–13. We note that the later lemma applies in a much more general context than our treatment of dissimilarity.
Lemma 12 If, for each , is an integer such that then(17)(18)uniformly for as .
Proof. First observe that for all sufficiently large and , it applies that
Note that , for all . As a result, we may bound the exponential factor on the right-hand side above as follows:
Since and , uniformly for all as , (17) follows.
To show (18), first note the combinatorial identity(19)
Proceeding in an analogous manner as we did to show (17), we see now that the term associated with the index in the above summation satisfies thatfor all sufficiently large and . Since and , the above inequalities together with (17) and (19) establish (18).
Lemma 13 Define , where is a bounded -symmetric function, and letbe the U-statistic of associated with draws from urn- and draws from urn-; in particular, . Furthermore, assume that
- ,
- there is a function such that ,
- ; in particular, .
Under the above assumptions, it follows that
Proof. Define ; in particular, and , and , for any , as . The proof of the theorem is reduced to show that(20)(21)
Next, we compute the variance of following an approach similar to Hoeffding [14]. Because is -symmetric, a tedious yet standard calculation shows that(22)where
Clearly, . On the other hand, if is any random variable with finite expectation and are sigma-fields then , due to well-known properties of conditional expectations [22]. In particular, for each , we have that(25)
Consequently, (22) implies that(26)
Indeed, using an argument similar as above, we find that
Due to assumptions (i)-(ii) and the Bounded Convergence Theorem, the right-hand side above tends to , and the claim follows.
It follows from (26) and (27) that
Finally, because of assumption (iii),
Since each term on the right-hand side above tends to zero as , (20) follows.
We now show (21). As and , it follows by (22) and Lemma 12 thatuniformly for as . In particular,
Due to the definition of the coefficients , the right-hand side above tends to zero, and (21) follows.
Proof of Theorem 3
Note that , with . We show that the kernel function and the U-statistics satisfy the hypotheses of Lemma 13. From this the theorem is immediate because -convergence implies convergence in probability.
Clearly is -symmetric and , which shows assumption (i) in Lemma 13. On the other hand, due to the Law of Large Numbers, almost surely, from which assumption (ii) in the lemma also follows.
Finally, to show assumption (iii), recall that is the set of one-to-one functions from into ; in particular, . Now note that for each indicator of the form , with , there are choices of outside the set . Because , it follows that for all . This shows condition (iii) in Lemma 13, and Theorem 3 follows.
Proof of equation (7)
The jackknife estimate of the variance of obtained from removing a single -data is, by definition, the quantity(28)
Note that removing a color from the -data which would otherwise add to , decrements this quantity by one unit. Let denote the -statistics associated with the data when observation from urn- is removed from the sample. Note that as each draw from urn- contributes to exactly one , for all except for some where . We have therefore that
Since there are draws from urn- which contribute to , the above sum may be now rewritten in the form given in (7).
Proof of equation (9)
Similarly, corresponds to the jackknife summed over each possible deletion of a single -data, which is more precisely given by(29)where is the set of one-to-one functions from into .
Recall that is the number of colors seen times in draws from urn- and times in draws from urn-, giving that .
Fix and suppose that is of a color that contributes to , for some Removing from the data decrements and increments by one unit. Proceeding similarly as in the case for , if is used to denote the -statistics when observation is removed from sample-, thenwhere and are as defined in (10) and (11). Noting that for each there are draws from urn- that contribute to , the form in (9) follows.
In what follows, we specialize the coefficients in (23) and (24) to the kernel function of dissimilarity, . From now on, for each and , define(30)(31)
Above it is understood that the sigma-field generated by when is ; in particular, , for all .
The following asymptotic properties of are useful in the remaining proofs.
Lemma 14 Assume that conditions (a)-(c) are satisfied and define . It follows that and . Furthermore(32)(33)(34)
Proof. Observe that conditions (a)–(b) imply that . In addition, condition (b) implies that , whereas condition (c) implies that .
Next, consider the seti.e. is the set of rarest colors in urn- which are also in urn-. Also note that
(35)As an intermediate step before showing (32), we prove that(36)
Hencefrom which (36) now easily follows.
To show (32) note that (36) implieswhich establishes (32).
Now note thatwhich establishes (33).
Next we show (34), which we note gives more precise information than (27). Consider the random variable defined as the smallest such that . We may bound the probability of being large by , where is finite because of condition (a). On the other hand, note that
Define and observe that, over the event , . Since , we obtain that
The identity in equation (34) is now a direct consequence of (35).
Our next goal is to show Theorems 4 and 5. To do so we rely on the method of projection by Grams and Serfling [17]. This approach approximates by the random variable
The projection is the best approximation in terms of mean squared error to that is a linear combination of individual functions of each datapoint.
Under the stated conditions, is the sum of two independent sums of non-degenerate i.i.d. random variables and therefore satisfies the hypotheses of the classical central limit theorem. The variance of the projection is easier to analyze and estimate than the -statistic directly, which is relevant in establishing consistency for the jackknife estimation of variance.
Letbe the remainder of that is not accounted for by its projection. When is small relative to , is mostly explained by in relative terms.
The next lemma summarizes results about the asymptotic properties of , particularly with relation to the scale of as given by its variance.
Under assumptions (a)-(c), for a fixed , we have that(39)
Furthermore, under assumptions (a)–(d) we have that (40)(41)
for all .
Proof. A direct calculation from the form given in (16) gives that(42)(43)
As , (37) follows.
To show (38), first observe that(44)
Next, using the definition of the projection, we obtain thatfrom which (38) follows, due to the identity in (44). Note that the last identity implies that and are uncorrelated.
Before continuing, we note that (41) is a direct consequence of (38), (40) and Chebyshev's inequality [22]. To complete the proof of the lemma all reduces therefore to show (41) under conditions (a)–(d). Indeed, if and we let then due to the identities in (22) and (37) and Lemma 12, we obtain under (a)–(c) thatuniformly for all , as . Since for all , we have thus shown (39). Furthermore, note that for all ; in particular, due to (33) and conditions (a)–(d), we can assert that . Since , the above identity together with the one in (37) let us conclude that
as . Because of condition (d), the big-O term above tends to . As a result:
(45)On the other hand, (38) implies that . Hence, using (19) and (25) to bound from above the variance of the U-statistic, we obtain:as , where for the last identity we have used (32) and (34). Since , it follows from the above identity that
In particular, if the base- in the logarithm is selected to satisfy that , then(46)
The identities in equation (45) and (46) show (41), which completes the proof of the lemma.
Proof of Theorem 5
For a fixed , note that is the sum of two independent sums of non-degenerate i.i.d. random variables and thus,is asymptotically a standard Normal random variable as by the classical Central Limit Theorem. We would like to show however that this convergence also applies if we let vary with and . We do so using the Berry-Esseen inequality [23]. Motivated by this we define the random variables
We need to show that(47)uniformly for , as .
It follows from (37) that
But note that . Since, according to Lemma 14, decreases exponentially fast, we obtainuniformly for all , as . On the other hand, . Furthermore, (33) implies that . Since , for some finite constant we find that
The above establishes convergence in distribution of to a standard normal random variable uniformly for , as . The end of the proof is an adaptation of the proof of Slutsky's Theorem [21]. Indeed, note that(48)
From this identity, it follows for any fixed that
The first term on the right-hand side of the above inequality can be made as close to as wanted, uniformly for , as , because of (40). On the other hand, the second term tends to uniformly for because of (41). Letting , shows that
Similarly, using (48), we have:
and a similar argument as before shows now that
which completes the proof of the theorem.
We finally show Theorem 4, for which we first show the following result.
Lemma 16 Let be the set of one-to-one functions from into . Consider the kernel , and define(49)(50)(51)(52)Then, for each and ,(53)(54)
Proof. Fix . We first use a result by Sen [24] to show that, for each :(55)(56)(57)(58)
in an almost sure sense. Indeed, assume without loss of generality that . As the kernel functions found in (49) and (51) are bounded, the hypotheses of Theorem 1 in [24] are satisfied, from which (55) and (57) are immediate. Similarly, because and are discrete random variables, (56) and (58) also follow from [24].
Define(59)(60)and observe that
Furthermore, due to (55)–(58), we have that(61)(62)
But note that, for , and are independent and hence uncorrelated. Similarly, the random variables and are independent. Since and , it follows from (61) and (62), and the Bounded Convergence Theorem [22] that(63)(64)as .
Finally, by (30) and (31) it follows that
In particular, again by the Bounded Convergence Theorem, we have that and . Sincethe lemma is now a direct consequence of (63) and (64), and Theorem 1.5.4 of Durrett [22].
Proof of Theorem 4
It follows by (28) and (29) that(65)(66)where and are as in (59) and (60), respectively. Furthermore, observe that
In particular, due to (37), we obtain that
By Lemma 16, converges in probability to , while similarly converges in probability to ; in particular, the first two terms on the right-hand side of the inequality converge to in probability. Since and , the same can be said about the last two terms of the inequality. Consequently, converges to in probability, as . As stated in (39), however, conditions (a)–(c) imply that and are asymptotically equivalent as , from which the theorem follows.
Supporting Information
File S1.
Summary Metadata related to Table 1 (tab-limited text file).
We thank Rob Knight for insightful discussions and comments about this manuscript, and Antonio Gonzalez for providing processed OTU tables from the Human Microbiome Project.
Author Contributions
Conceived and designed the experiments: JH ML. Performed the experiments: JH. Analyzed the data: JH ML. Contributed reagents/materials/analysis tools: JH ML. Wrote the paper: JH ML. Directed the research project: ML.
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- 7. Starr N (1979) Linear estimation of discovering a new species. Ann Stat 7: 644–652.
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Protect Your Waters and Stop Aquatic Hitchhikers!As Americans, we love to spend time on the water. Protecting these resources is an important part of our overall enjoyment. A concern we must all address is the spreading of harmful plants, animals and other organisms. These aquatic nuisance species can hitch a ride on our clothing, boats, and items used in the water. When we go to another lake or stream, the nuisance species can be released. And, if the conditions are right, these introduced species can become established and create drastic results.
So what can we do? By following a simple procedure each time we leave the water, we can stop aquatic hitchhikers. Knowing which waters contain nuisance hitchhikers is not as important ---- as doing the procedure every time we leave any lake, stream or coastal area.
Simple Procedure
- Remove any visible mud, plants, fish or animals before transporting equipment
- Eliminate water from equipment before transporting
- Clean and dry anything that came in contact with water (Boats, trailers, equipment, clothing, dogs, etc.)
- Never release plants, fish or animals into a body of water unless they came out of that body of water.
Become Informed and Take Action!
- We can also become more informed about this issue. As recreational users, history has shown we will take action if informed. We will work to protect our environment if we know what to do. This site is designed to help us learn about the aquatic hitchhiker issue. Navigate through this site to get:
- The latest news about this growing problem
- Detailed procedures to prevent the transport of nuisance species
- Impacts caused by these species
- Facts about some of the more common hitchhikers
- Resources and ideas for you or your club to get involved with prevention efforts
- Support materials to further your understanding of and involvement with the Aquatic Hitchhiker problem.
Why Is This Important?Because these hitchhikers can:
- Reduce game fish populations
- Ruin boat engines and jam steering equipment
- Make lakes/rivers unusable by boaters and swimmers
- Dramatically increase the operating costs of drinking water plants, power plants, dam maintenance, and industrial processes
- Reduce native species
- Degrade ecosystems
- Affect human health
- Reduce property values
- Affect local economies of water-dependent communities.
Clarification of TermsFor the purposes of this campaign and the related materials, Aquatic Hitchhikers are defined as non-native, harmful aquatic plants, animals or microscopic organisms that can readily be transported to other waters via popular recreational activities. Also, different terms will be used interchangeably throughout the campaign to describe aquatic hitchhikers. These terms include: aquatic nuisance species, ANS, aquatic invasive species and non-native, harmful aquatic species. Campaign sponsors use these multiple terms to facilitate a better understanding about the issue and to assist with the ease of your reading.
This infomation was provided by the U.S. Fish and Wildlife Service. For more information, go to their campaign website www.protectyourwaters.net.

subset: commoncrawl


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The first kart racing game set in the popular BEN 10 universe features Ben and his alien friends
competing in an over-the-top, galactic grand prix through a variety of tracks on five different
planets! Compete for the best times in the high-speed grand prix modes or engage in four-player
multiplayer mayhem!


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The new LP was considered a huge leap forward for listening to pre-recorded Classical music. A pop song took, on average, two or three minutes to play, which was just perfect for a 10 or 12 inch 78 rpm record. A symphony required up to 5 or 6 records on 78 rpm and had to be changed 10 to 12 times with the music often interrupted in the middle of a musical phrase. There were automatic 78 rpm record changers, but they were clunky and could damage your records. You also had to account for the amount of storage space needed for the brittle, breakable shellac 78s. The most dramatic part of Goldmark's demonstration was when he was photographed holding a few dozen LPs while the equivalent in 78s were stacked six feet high next to him.
The introduction of the LP was not without controversy. Columbia's great rival RCA Victor was developing its own system of 7" short playing vinyl records that played at 45 rpm. RCA engineers insisted that quality control problems with LPs would doom it. This started what was to be known as "The War of the Speeds" in which both companies spent a ton of money on print ads to woo the public before RCA conceded and converted to LP. When it was settled, it set up the paradigm that lasted for nearly 40 years: LP for albums, 45s for pop singles.


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The Sugarcane Hitchhiker
A daughter's attempt, in words and original artwork, to complete the untold story her father left behind.
The TV was still on when I walked into my father's bedroom at the top of that narrow, creaking staircase. The bedroom he shared with his brother as a kid, the bedroom he shared with my mother years later. I was conceived in that bedroom. And when I saw my father's empty bed I collapsed on it and cried and wished I'd never been born.
They were already carrying his body out on a stretcher when I got there. Zipped up in a bag. I begged the police officer to let me see him. "I'm sorry honey, we can't do that. We can't do that."
But the TV was still on, and the ashtrays overflowing. Glass jars filled with paintbrushes lining the windowsills. Piles of magazines and sketchbooks and journals everywhere. The smell of cigarettes was still thick in the air, the fine residue of crushed pills still visible on his desk. My father had been a mess, like me. And now this mess was all I had left of him.
It's been nearly three years since my father died. I've managed to hold on to almost everything he left in that room, every unfinished watercolor and half-written essay…every faded photograph. He was telling a story, my father, in images and words…the story of his adolescence, of running away with Timothy Leary and drinking with Janis Joplin. He was telling the story of the years we spent apart…my childhood. It was better that way, he told me later — better that the darkest and most self-destructive moments of his life happened far away in the booze-soaked bayou. As a kid, whenever people asked me about my dad, I always said he was in New Orleans. It was true, but I didn't know what it meant at the time. I would find out eventually.
I am my father's daughter, down to the brittle bone. I am the only person alive who can finish his story. Through a combination of his artwork and writing and my own, The Sugarcane Hitchhiker is my attempt to do just that.


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Up Next: Ubuntu 9.04
If you're set to try the new Ubuntu 9.04 release when it comes out on April 23rd you may enjoy a few of these resources.
As if you haven't already been flooded with enough news about the new Ubuntu features here's a list of what you'll be missing if you don't check out the latest release of Ubuntu. GNOME 2.26, new desktop notifications, better multi-display support, cloud support, upgraded X.Org server 1.6, Linux kernel 2.6.28 and support for the ext4 file system. Although version 9.04 does include some new features, Ubuntu has changed little on the desktop. Users looking to score Ubuntu for free may look at downloading or picking it up on CD for $1.95 before waiting 10 weeks for the subtle changes displayed in the RC release. Only time and this poll will tell.


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Our intention is to acquire and make available ALL picture books featuring Indigenous people and people of color published in the U.S. since 2002, including reprints. Inclusion of a title in the collection DOES NOT EQUAL recommendation. See our related readings page for suggested links for evaluating books.
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My friend Mei Jing
Monifa met Mei Jing on the first day of school and they've been best friends ever since. The girls have much in common, from their love of arts and crafts to their dream of becoming veterinarians. Monifa thinks Mei Jing's family customs are pretty neat, too, like getting red envelopes for Chinese New Year and eating with chopsticks


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Our flavor of the month for December is cranberry… it's always appropriate around the holidays, right? Here's what we have been enjoying this month.
- MAC Cranberry Eyeshadow – this eyeshadow is old school MAC at its finest. This is one of MAC's oldest shades (it is the one in the middle seen above in my old palette) they have and it is just simply gorgeous. It is a red plum shade with a pink shimmer. I love this packed on lower lid and blended out towards the crease… so pretty!
- MyChelle White Cranberry Cleanser – I picked up a MyChelle sampler box awhile back and this cleanser was one of the products I ended up picking up out of the samples I tried. This cleanser from the all natural line is not harsh on my skin even though it has glycolic, azelaic and salicylic acids in it.
- Glade Fragrance Collection Pomegranate & Cranberry Candle – I've been burning these candles all month long and it put me in the festive spirit! The candle burns evenly and the scent fills the room without being overwhelming. Plus it is a bargain! I received a sample and wanted to keep it going all month long so it has been easy on my wallet. It is available in a reed diffuser as well.
- Kiehl's Lip Balm #1 in Cranberry – we stockpile this lip balm in the winter and cranberry is in regular rotation! It's got a light scent, not too overpowering and works like a charm. Seriously, this lip balm creates a barrier between your lips and the wind, cold and other weather harshness. It absorbs slowly into your lips and makes them soft. And even though the balm consistency isn't sticky, it's very long-lasting. Laurie's threshold is if it survives her morning commute…and it does!
- The Body Shop Merry Cranberry Frosted Shimmer Lotion – this lotion is such a delight! If you're not careful, shimmery lotions can either give that tin-man effect or transfer to clothes. But not this stuff. It's got a silvery sheen to it that translates as a glow on your skin. The smell is very festive and wintery, like a subtle candied cranberry. We're all for brightening up our skin in the winter!
What are your cranberry picks? Let us know in the comments.


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Fluent in both English and Spanish, and that's it
Quote from: GabyM on August 13, 2011, 07:52:41 PMFluent in both English and Spanish, and that's itI hope your Spanish is better than Mirna's
Filipino will be quite handy this weekend!!
You never know! We could have used you during Luke's season!
I can help with Vietnamese
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The Hope College Brown Bag Concert Series will continue with a variety of student performances on Friday, Dec. 6, at noon at the Holland Area Arts Council.
The public is invited. Admission is free.
Founded in 2008 and directed by Hope College piano professor Dr. Andrew (Drew) Le, the series is built on the premise that classical music should be accessible by all. Accordingly, Brown Bag presents classical art music in a setting that is completely free of pretense: performers are required to wear jeans and talk to the audience about their selections, people of all ages are encouraged to come and go as they please, and everyone is encouraged to bring a brown bag lunch and make as much or as little noise as they wish. Light beverages are also served.
The Holland Area Arts Council is located west of Columbia Avenue at 150 E. Eighth St.


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Lexus has already faked out the spy community, through which word of a V8 powered Lexus IS spread like Influenza A virus subtype H5N1. Through them, we'd heard the so-called IS 500 would debut at the '06 Detroit show, which came and went without word one that such a car was in the pipeline. Now, the spooks have caught sight of what they believe is the IS 500 in apparent shakedown testing on the N rburgring. Could Detroit '07 be the venue for the hi-po Lexus S4/M3 fighter? Only agent Ken Watanabe (and a few of his henchmen) know for sure.
Spy photos: Lexus IS 500 [Edmunds Straightline Blog]
Lexus Prepares V8-Powered IS Concept for Detroit [internal]


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Is Weight Gain Normal During Puberty?
I am 13. I am 5 foot 6 inches and I weigh 130 pounds. Is this normal for a girl my age? Or am I overweight? I feel fat but I`m told I`m fine. I think my thighs are also fat. Am I really fine?
As a teenager, you are in a period of rapid growth and development, with dramatic changes in your body composition. In adolescent girls, fat becomes a larger percentage of total body weight and body shape begins to change. It is important to accept these physiological changes and to feel positively about your body image.
Height and weight can be used to calculate a measure called Body Mass Index or BMI. According to growth charts used by pediatricians (developed by the Centers for Disease Control and Prevention), most 13-year old girls have BMIs in the range of 15-22. Your BMI is 21. So you are in the healthy BMI range for your age. In other words, your weight is in the healthy range for your height and age.
To stay in the healthy weight range, remember to eat healthful foods, particularly fruits, vegetables, low-fat dairy products (such as milk, cheese, and yogurt) and lean meat, poultry, and fish. Limit your intake of foods that are loaded with calories but not many nutrients, such as french fries, fried foods, cakes, cookies, doughnuts, and sugary soft drinks.
Also remember to be physically active every day. Take a walk, swim, bike, dance, or participate in other types of physical activity or sports that you enjoy. Ask a friend or family member to join you in your activity. If you can make healthy foods and physical activity part of your lifestyle now, you will be more likely to remain in a healthy weight range throughout your life!
For more information:
Go to the Healthy Weight Center health topic.


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Kraftster wrote:Martin for Suter's rights without having a deal in place is incredibly stupid.
I'd still give away Martin for free even with Michalek gone. That's how little I think of him.
Moderators: Three Stars, dagny, pfim, netwolf
Kraftster wrote:Martin for Suter's rights without having a deal in place is incredibly stupid.
malkinshair wrote:Will miss Z...best of luck.
Shero has decided to blow up the team...
for a chance at another superstar.
Which one, we don't know yet...but Parise or Suter have to be in play at this point.
DelPen wrote:Marc Cheverie is from Cole Harbour so I'm sure he knows Crosby.
FallenHero96 wrote:So I looked up Harrison Ruopp on Youtube, and it's full of fights.
lemieuxReturns wrote:DelPen wrote:Marc Cheverie is from Cole Harbour so I'm sure he knows Crosby.
They are friends actually.
DesertPenguin wrote:Only way Martin gets dealt out of here now is if Shero brings a top 4 veteran in first and signs him. Ray Shero will not take any action that risks the pens starting the season with:
Letang - Orpik
Like him or not, Martin is here to stay until Shero has a guy under contract to eat the 22+ minutes a night he is responsible for.
ville5 wrote:Ah, so Shero, drunk off all the D he acquired, thought he was bringing back mike rupp. Instead he got ruopp.
And I was hoping all those PIMS were from slammin bodies through the glass. Oh well.
Ossa wrote:If you're going to do a salary dump then atleast get something good in return. Heck, I'd take a 2nd round pick pick straight up for Z over this deal.
KG wrote:I watched the Shero media scrum. The staff/scouts were high on Ruopp last year and almost drafted him.
Another chip...
Users browsing this forum: Pruezy11881 and 13 guests


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07 April 2011
GREAT collected its first terahertz photons from the M17SW star forming cloud on 6 April 2011. Superposed on a near-infrared false-colour image obtained with the Spitzer Space Telescope (NASA/JPL-Caltech/M. Povich, Univ. Wisc.), you will see selected spectra of ionized carbon ([CII], white line) and warm carbon monoxide (CO, green line). The high spectral resolution of GREAT is necessary to study the velocity structure across the cloud, as unveiled by the different line profiles. The field studied in the sky is overlaid on the infrared image, and the velocity integrated distribution of [CII] and CO is displayed in the inserts at the bottom. The data obtained with GREAT shows the warm interface of the M17 molecular cloud exposed to the ionizing radiation of nearby massive stars.
GREAT team / NASA/DLR/SOFIA/USRA/DSI. Spitzer image (background): NASA/JPL-Caltech/M. Povich, Univ. Wisconsin.
The Stratospheric Observatory For Infrared Astronomy (SOFIA) on its maiden test flight with a completely opened telescope hatch on 18 December 2009 over the Californian Mojave Desert. The 2.7 metre telescope, built in Germany, is visible through the opening in the fuselage of this Boeing 747SP. The test flight with an open hatch enabled engineers to examine the movement of air in and around telescope and door under experimental conditions for the first time.
NASA/C. Thomas.
The GREAT receiver (metallic silver) mounted on the telescope (in blue) on the SOFIA airborne observatory.
NASA/Tom Tschida.
On 6 April 2011, German scientists carried out their first astronomical observations on board the Stratospheric Observatory for Infrared Astronomy, SOFIA. A joint project between NASA and the German Aerospace Center (DLR), SOFIA is the world's only operational airborne observatory. The first observations with the German Receiver for Astronomy at Terahertz Frequencies, GREAT, included spectra of the Omega Nebula (M17) an active star-forming region in the Milky Way, and the galaxy IC 342, located a few million light years away.
On 6 April 2011, German scientists carried out their first astronomical observations on board the Stratospheric Observatory for Infrared Astronomy, SOFIA. A joint project between NASA and the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR), SOFIA is the world's only operational airborne observatory. Flying at altitudes above 10 kilometres, SOFIA is able to perform observations not possible with ground-based telescopes, due to atmospheric water vapour absorption. The first observations with the German Receiver for Astronomy at Terahertz Frequencies, GREAT, included spectra of the Omega Nebula (M17), an active star-forming region in the Milky Way, and the galaxy IC 342, located a few million light years away.
At 06:40 local time (15:40 CEST) on 6 April, with SOFIA touching down once again at its home base, the Dryden Aircraft Operations Facility in Palmdale, California, Rolf Güsten and his team successfully concluded their first science flight with GREAT. The instrument had been pointed at, among other objects, IC 342, a prominent intermediate spiral galaxy in the constellation Camelopardalis, and M17, an active massive star-forming region 5000 light years away. For both sources, the radiation from ionised carbon at 1.9 terahertz (158 microns) and the high rotational transitions of warm carbon monoxide were measured, providing a tool to probe the interstellar medium in the environments around newly-formed massive stars.
Rolf Güsten, the Principal Investigator for GREAT, was delighted by the success: "These very first spectra are the reward for many long years investing in cutting edge technology developments and they showcase the scientific potential of airborne far-infrared spectroscopy. Thanks to the large collecting area of the 2.7-metre diameter telescope, together with enormous progress in terahertz technology, the collection of data is 100 times faster compared to earlier experiments, opening a new pathway for unique scientific experiments." The GREAT instrument was developed by a team from the Max Planck Institute for Radio Astronomy (MPIfR) and the University of Cologne, led by Rolf Güsten, in collaboration with the Max Planck Institute for Solar System Research and the DLR Institute of Planetary Research.
"GREAT's first science flight is the beginning of German-American scientific collaboration on SOFIA. We are confidently looking forward to the upcoming routine operations," said Alois Himmes, SOFIA Project Manager at DLR. After these first observing flights with GREAT, the observatory will be open to astronomers outside the project. "Astronomers from all German institutes have been able to apply for scientific observation time with SOFIA during the summer of 2011. They will use either GREAT or the US Faint Object InfraRed-CAmera for the SOFIA Telescope, FORCAST," explained Alfred Krabbe, Head of the German SOFIA Institute (Deutsches SOFIA Institut; DSI) at the University of Stuttgart."
GREAT, the German Receiver for Astronomy at Terahertz Frequencies, is a receiver for spectroscopic observations in the far-infrared spectral regime at frequencies between 1.2 and 5 terahertz (60–220 microns), which are not accessible from the ground due to absorption by water vapour. GREAT is one of two first generation German instruments for SOFIA developed by the Max Planck Institute for Radio Astronomy (MPIfR) and the University of Cologne, in collaboration with the Max Planck Institute for Solar System Research and the DLR Institute of Planetary Research. Rolf Güsten (MPIfR) is the project manager for GREAT. The development of the instrument was financed by the participating institutes, the Max Planck Society, the German Research Foundation (Deutsche Forschungsgemeinschaft; DFG) and DLR.
About SOFIA
SOFIA is a joint project of the German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt; DLR) and the National Aeronautics and Space Administration (NASA). The project is being carried out under the auspices of DLR, with funds provided by the German Federal Ministry of Economics and Technology (Bundesministerium für Wirtschaft und Technologie; BMWi) under a resolution passed by the German Federal Parliament, and with funding from the State of Baden-Württemberg and the University of Stuttgart. Scientific operations are coordinated by the German SOFIA Institute (DSI) at the University of Stuttgart and the Universities Space Research Association (USRA).
M17SW is a molecular cloud containing about 10,000 solar masses of gas that is illuminated by a cluster of young stars with a total radiation output of more than one million solar luminosities. The radiation from the cluster ionises and heats the molecular gas, possibly compressing it into a state where more stars form. The SOFIA observations allow researchers to distinguish the effect of this radiative compression from the heating effect that would instead lead to expansion. In this way, the future of the molecular cloud with regard to its star formation activity can be predicted.
IC 342 is the nearest gas-rich spiral with active star formation in its nucleus. Within its central 30 arcseconds, two molecular arms end in a lumpy central ring of dense gas surrounding a young star cluster. The young stars heating the surrounding gas and dust are responsible for the rich chemistry and intense emission of these regions, known as Photon Dominated Regions (PDRs). The strong emission from these PDRs allows an in-depth study of the chemical and physical conditions in these distant massive star-forming regions.
Last modified:29/04/2011 13:41:54


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The Best Years of Our Lives (1946)
At the end of my long and movie-filled holiday break, I finally got around to seeing director William Wyler's The Best Years of Our Lives, a movie that had been on my "to watch" list for many years. Talk about ending my vacation on a high note! The film is one of the best I've seen in a long time. It's the story of three WWII veterans who return to their midwestern hometown after the war, and their difficulties readjusting to life with their families, friends and jobs after years away.
Fredric March plays a middle-aged banker who served as an infantry sergeant in the Pacific and returns to his lovely, understanding wife (Myrna Loy) and two children (Teresa Wright and Michael Hall) who've grown up in his absence. In spite of all he has, he struggles to acclimate to the life and career he knew before. He feels he no longer knows his children, chafes against the rules and regulations of the bank at which he works, and copes with his post-war trauma and uncertainty by drinking a great deal more than he should.
Dana Andrews gives a charismatic and nuanced performance as a guy who was a soda jerk from the wrong side of the tracks prior to the war, but who in the service became a captain and a decorated bombardier. All he wants is to return to his wife (Virgina Mayo), find a good job, and move to the suburbs. Unfortunately the shallow woman he married after a brief wartime romance is unimpressed with him now that he's not a glamorous army flier, and jobs for men with the skills he gained in the service are hard to come by now that planes are being decommissioned and nobody's dropping bombs. That Dana Andrews wasn't even nominated for an Academy Award for this role is an absolute travesty. To me his was the most fascinating character in the film – a man whose wartime opportunities allowed him to escape a poverty-stricken upbringing and become a success, however briefly. Seeing him come crashing back to earth when post-war realities set in is heartbreaking.
Harold Russell, a disabled WWII veteran who'd never acted prior to this movie and turns in a memorable and touching performance, plays a sailor who lost both hands in an explosion and fire. Although he's learned how to cope with the physical side of his injuries quite well, lighting matches, dressing, and even shooting targets using his new prosthetic hooks, the emotional repercussions of his loss are harder to shake off. He can't stand to be pitied by those he loves, and pushes his family away in an effort not to be a burden.
Every performance and storyline in the movie is pitch-perfect and honest. It's not melodramatic or emotionally manipulative, and it doesn't particularly try to be a tearjerker. The emotion comes from seeing these decent if imperfect men deal with displacement, awkwardness, and post-traumatic stress in the aftermath of the war, and from seeing their loved ones also come to grips with their return and the fact that the men they're welcoming home aren't quite the ones they sent away years before.
There are many memorable scenes in the movie: the three vets flying home in the nose of an army plane, looking down at the country they fought for; Fredric March reuniting with Myrna Loy; Teresa Wright gently and matter-of-factly calming Dana Andrews after a nightmare; Harold Russell letting his sweet, girl-next-door fiancee (Cathy O'Donnell) see just how helpless his disability has made him; Dana Andrews walking through a graveyard of decommissioned planes, climbing into one as he tries get the past out of his system. The movie is full of moments that are honest, warm, heartrending and hopeful, and the characters are such real people that you grow to love them.
In spite of The Best Years of Our Lives being on lists of the greatest movies ever made, a winner of multiple Oscars and starring actors I like, I'd put off watching it for years. For one thing, I knew it would make me cry, and for another it's almost three hours long and these days my attention span isn't what it used to be. I shouldn't have avoided it for so long, though! The tears I shed were worth it, and the movie was so engrossing that three hours sped by in a flash. In fact, I watched it a second time later that week and felt I got even more out of it with a repeat viewing. I can't say enough good things about this film.
The Best Years of Our Lives is available on DVD and airs on TCM February 26th and March 19th. I highly recommend checking out this very special movie if you haven't seen it before. Don't wait years and years like I did!


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SCARBOROUGH — Kyle St. Clair, a boy whose mysterious ailments largely confined him to his bedroom and hospitals, but whose story became an inspiration to thousands, died Tuesday morning at the age of 8, according to his family.
St. Clair, who earlier in 2012 confessed to his sister he didn't think he would survive to see his eighth birthday, reached the milestone on Oct. 27, and then lived to spend one more Christmas and New Year's Day with his family.
On Tuesday, the boy's family posted the following on a Facebook page devoted to Kyle:
"After 8-plus years of fighting, our love doesn't need to fight anymore. Kyle William St. Clair passed away here, at home, this morning with his family by his side. We can't say enough about what joy this boy has brought to us in his short time on Earth. So much love. Thank you to all for the support you have given to him and to us."
St. Clair was born prematurely in 2004 and spent more than seven years in different hospitals around the eastern U.S., as a range of specialists treated a cascading list of ailments which restricted his breathing and digestion.
Mysteriously, the boy's digestive tract worked in reverse, confounding doctors, who never did provide a definitive diagnosis of the underlying problem, Kyle's parents said in early November. That reverse motility drove dangerous digestive acids back up through organs such as his lungs and esophagus, effectively destroying them.
Over the course of more than 50 surgeries, doctors replaced most of his internal organs with plastic, external stand-ins to keep him alive. Tubes connected to sacks and medical equipment extended from his torso. A feeding tube provided nutrients, as his throat no longer connected to anything but another tube leading out of his body.
Kyle needed a new set of lungs, stomach, bowel, intestines, liver and esophagus, and specialists who treated him ultimately determined he would never be able to withstand such a dramatic overhaul.
But while Kyle St. Clair was never able to eat a morsel of food, he was credited with inspiring thousands during his short life.
A website and Facebook pages chronicling his good days and bad days were set up by his mother, Town Councilor Kate St. Clair, and the sites went viral. Nearly 11,000 people began following Kyle through the most recent and regularly updated Facebook page, titled "Team Kyle."
Many followers sent Kyle notes saying his battle inspired them in the face of their own medical ailments. The boy received more than 500 birthday cards from strangers all over the world when he reached the eighth birthday he once considered out of reach.
Through those online networks, Kate and father Mark St. Clair, helped Kyle organize multiple charity efforts, including the sale of bracelets and T-shirts to benefit institutions such as the Barbara Bush Children's Hospital at Maine Medical Center and Angel Flight Northeast, among others.
Perhaps the most original of Kyle's projects involved distributing about 400 small cards reading "Live for today" on the front and urging the finder to do something nice for another person before passing it along. The "pay-it-forward" cards were scattered all across the country by friends and supporters, and emails began coming back to the St. Clairs from card-receiving kids who had started lemonade stands to benefit local charities or adults who simply paid the coffee tab for the stranger in line behind them one morning.
Kyle's baffling ailments and his efforts to spread acts of kindness made him a kind of local and Internet celebrity, even as he was requiring powerful drugs hourly to withstand the pain of his ravaged internal organs.
The boy was made an honorary member of the Scarborough High School football team, whose members frequently visited him at his home and played games with him.
Local establishments, such as the restaurant Anjon's, held fundraisers to both help the St. Clair family pay for medical expenses and to donate to their favored causes.
Over the first four hours since the St. Clairs posted news of Kyle's death on their Team Kyle Facebook page, more than 1,700 comments of reaction were posted by followers.
When the St. Clairs moved Kyle back to Scarborough in February 2012 after the last of his many surgeries in Ohio, doctors gave the boy four days to live, his mother said.
On Jan. 1, nearly a year later, his family posted that his health had taken a downturn and that they had to double many of his medications to compensate, but that he vowed to fight on.
On Tuesday, they posted that he had died, at home, and surrounded by family.
Sidebar Elements
Kate St. Clair cuddles her son Kyle, 8, for a moment while he plays a game on his iPad in November 2012 at their home in Scarborough. Kyle died Tuesday, Jan. 8.
Town Council postpones workshop
SCARBOROUGH — Due to the death of Councilor Kate St. Clair's son Kyle, Wednesday's planned 6:30 p.m. Scarborough Town Council goal-setting workshop was postponed. The workshop will be rescheduled at a later date.
Leonard Pitts: 'Honorary whiteness' must be a powerful drug
Letter to the Editor: Technological achievement no measure for civilization
Mayor Strimling: City's welcoming response a source of pride
Maine Voices
Maine Voices: CMP's billing woes point to bigger problems
PBR Hard Coffee creating a buzz in Maine test market


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Juan Felipe Herrrera is the 21st U.S. Poet Laureate, appointed for 2015-2016, the first Latino poet to receive this honor.
Juan Felipe Herrera was appointed as the U.S. Poet Laureate in 2015. The son of migrant farm workers, he was educated at UCLA and Stanford University, and received his MFA from the University of Iowa Writers' Workshop. His numerous poetry collections include 187 Reasons Mexicanos Can't Cross the Border: Undocuments 1971-2007, Half of the World in Light: New and Selected Poems (2008), and Border-Crosser with a Lamborghini Dream (1999). His latest poetry collection is Notes on the Assemblage (2015). In addition to publishing more than a dozen collections of poetry, Herrera has written short stories, young adult novels, and children's literature.
In 2012, Herrera was named California's poet laureate. He has won the Hungry Mind Award of Distinction, the Focal Award, two Latino Hall of Fame Poetry Awards, and a PEN West Poetry Award. In April 2016, Herrera received the Robert Kirsch Award for lifetime achievement from the Los Angeles Times. His other honors include the UC Berkeley Regent's Fellowship as well as fellowships from the National Endowment for the Arts, the Bread Loaf Writers' Conference, and the Stanford Chicano Fellows. He has also received several grants from the California Arts Council.
Herrera is also a performance artist and activist on behalf of migrant and indigenous communities and at-risk youth. His creative work often crosses genres, including poetry, opera, and dance theater. His children's book, The Upside Down Boy (2000), was adapted into a musical. His books for young people have won several awards, including Calling the Doves (2001), winner of the Ezra Jack Keats Award, and CrashBoomLove (1999), a novel-in-verse for young adults, which won the Americas Award. His poetry collection Half of the World in Light was a finalist for the National Book Critics Circle prize in 2009. Herrera lives in Fresno, CA.
261 Columbus Avenue at Broadway, San Francisco, CA 94133
phone: (415) 362-8193 • fax: (415) 362-
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Thank you for visiting our website! Below you will be able to find the answer to Londoner's lockup crossword clue which was last seen on USA Today Crossword, November 12 2017. Our site contains over 2.8 million crossword clues in which you can find whatever clue you are looking for. Since you landed on this page then you would like to know the answer to Londoner's lockup. Without losing anymore time here is the answer for the above mentioned crossword clue:
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|Pool iterations
|No friends of union members
|Half-___ (coffee option)
|Cookie with a PB&J variety
|Typical role for Hitchcock
|Ahead of the tag
|Strong conviction
|Don't mention
|Sign on a free-samples tray
|It's worth 0 grade points
|CSS Virginia crewmen, for short
|Gets a promotion
|Dances with wild abandon
|Leading the pack
|Surveyors' calculations
|Have down cold
|Umbrella inverter, maybe
|Souvenir of battle
|San Diego pro
|Org. concerned with workplace injuries
|Ranch worker
|Cork's land, to poets
|Hypnotist's command
|Victors' shout
|Walk like a penguin
|Apply, as fingerpaint
|Londoner's lockup
|"Om" and others
|Lincoln debate opponent of 1858
|Bancroft who played Mrs. Robinson
|Double shot at the bar
|Paint can direction
|Baby food or applesauce
|Natural emollient
|Gives birth to
|Elvis' trademark look
|"Live and Let Die" spy
|What a 9-iron provides
|Pavarotti delivery
|Corporate exec's freebie
|Unspecified amount
|Public to-dos
|Spy in Canaan
|"What ___ bid?"
|Common taco filler
|Dagwood's napping spot
|Albert who wrote "The Fall"
|Like Chicago in 1871
|Honors in style
|Like oldies hits
|Monotone speakers, usually
|Part of a pension plan, briefly
|Tending to an icy road, maybe
|Sitcom with Hawkeye and Radar
|Bicolored ocean predator
|Hannity of talk radio
|Cause of mineral buildup in faucets
|One of a devil's pair
|Shorn female
|Corn syrup brand since 1902
|Like Goodwill goods
|Silverstein who wrote "A Boy Named Sue"
|Recording medium that's "rolled"
|Bench in a nave
|"To your health!"
|Muff an easy one
|Low-frequency speaker
|Box office bonanza
|Plankton-eating ray
|Seat of County Clare
|Cost of a TV spot, say
|Snakes encountered by Indiana Jones
|Sci-fi phaser setting
|Get one's mitts on
|Disney friend of Stitch
|Soon, to poets
|Depot posting, for short
|49-Down's land (Abbr.)
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Lewis B. Walker finally made it to No. 1 on our top 50 list of residential water users. In other words, he's the Top Water Hog in Northeast Florida for 2013.
Walker's property on Timuquana Road on Jacksonville's Westside has been on the list for six of the seven years we've been outing the major water consumers in Northeast Florida. This year, Walker spent $9,061 for 1.48 million gallons of water, according to records obtained from the JEA. Walker's telephone number was not listed, and he did not respond to a letter from Folio Weekly.
The Water Hog information was compiled from a list Folio Weekly obtained, for $175, from the JEA under a public records request. The list contained the customer's name, home address, county, gallons of water sold in the 2011-'12 fiscal year and the annual amount of each customer's bill. We also looked up the property on the databases of property appraisers' offices in Duval, Nassau and St. Johns counties for information on the size of properties, square footage of each house and its market value, and records of recent sales.
The information from JEA shows the top 50 users consumed 53,428,817 gallons of water in the past year, with the top 29 users consuming more than 1 million gallons of water each. The other 21 on the list all used more than 900,000 gallons each.
Those are amazing amounts, considering the average customer uses about 6,000 gallons a month (or 72,000 gallons a year) for home use and about 3,000 gallons a month (36,000 gallons a year) for irrigation, according to Gerri Boyce, JEA's media relations coordinator.
We mailed letters to the top 20 Water Hogs, but only a handful responded. One woman was so embarrassed that her name appeared on the list, she called three times apologizing for heavy water use and saying it must be a mistake. Another woman called and asked that her name be removed from the list, while a man called and attributed his heavy use to his having "three daughters."
Seven of the top 50 Water Hogs live on Ponte Vedra Boulevard in St. Johns County. Some of the homes along that stretch of road near the ocean are new construction, requiring lots of water for irrigating new lawns or filling swimming pools, while some have reported broken or leaking irrigation systems.
The biggest water users also live on what used to be called "silk stocking row." Four of the top 15 live in houses with a market value of more than $1 million — the average market value of the top 15 is $692,433. In 2012, the median value of a single-family home in Duval County was $115,642, according to the Property Appraiser's annual report.
On a positive note, our top Water Hogs have become a little less piggish. The amount of water used by the top 15 has continued to decline over the years, from 28 million gallons in 2007 to 18.7 million gallons this year.
Last year's top 15 Water Hogs also did better for fiscal 2011-'12. That group, minus homes sold or where information was not available, saved more than four million gallons of water over the previous year. Of that group, only Lewis Walker increased his water use by 128,950 gallons, from 1.358 million gallons to 1.483 million gallons.
In some cases, JEA customers used more water but had lower water bills than some of the other big water uses. Boyce said there are a number of factors that contribute to that, including adjustments for broken pipes.
In the past, JEA did not notify customers if they were running up huge water bills by high usage. Now, JEA is launching the JEA Tracker, an online tool for customers to keep track of both their water and electric usage. JEA customers who log onto their accounts at jea.com will have access to the service. As part of the tracker, customers can set limit notifications, so if they hit that limit, they will be notified. Customers can also go online and see how much water they're using on a daily and monthly basis.
Our goal for running this annual survey is to make everyone aware of use and misuse of this precious resource. Please see the box on water conservation tips and websites that offer more information.


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From crisis to resilience: why inequality matters | Anuradha Seth
17 Aug 2012
Global financial and economic crises now occur so often they appear to have become a systemic feature of the international economy.
We need now to rethink what's behind these crises, recognize their unique impact on developing countries, and find ways to make these emerging economies more resilient in the face of serious shocks.
One approach views currency, debt, or banking crises as driven mainly by fragile, imbalanced financial systems in developing economies. But this assumes markets are self-regulating and inherently efficient, which is open to question in many instances.
Another focuses on identifying structural causes and the channels through which economies are exposed to crises. This approach regards the growing export-dependence of many developing countries as increasing their vulnerability to economic and financial shocks, although experts disagree on the specifics.
But rising income inequality also poses major risks.
The world's richest five percent now earn in 48 hours what the poorest earn in a year. This staggering escalation in inequality fosters inefficiency, instability, risky investment behavior, and lower overall productivity.
Understanding the links between income surging inequalities and worsening financial and economic crises is central to crafting policies that build resilience and promote less volatile growth.
Income inequality reduces the purchasing power of middle- and low-income households, reducing total demand, while the search for high-return investments by those who benefit from inequality leads to the emergence of asset bubbles. Poor regulation and loose monetary policy further fuel financial instability and lower economic growth.
Coping with crises only after they erupt limits options for concerted action to tackle inequality and craft the longer-term policies needed to build systemic resilience.
The recent and lasting economic and financial crisis offers a chance to comprehensively assess macroeconomic vulnerability in developing countries. We must find new ways of shoring up capacity to withstand shocks, while advocating global coordination aimed at minimizing the frequency and severity of global crises. And we need to do it now.
How can we ensure sustainable economic growth and minimize crisis risk?


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Why China's Falling Out of Love With the Oreo
China's love affair with the Oreo is crumbling.
Mondelez International Inc., the maker of Oreo cookies, Cadbury chocolates and Ritz crackers, announced Wednesday that its revenue was down in the fourth quarter and for the full year in part because China's appetite for the crème-filled sandwich cookie fell. Distributors had excess biscuit inventory, Mondelez reported.
Oreo has been one of the country's most popular cookie brands since it launched in China in 1996, with Mondelez holding the largest market share in China's biscuit segment at 16%, according to market-research firm Euromonitor International. Cookie sales in China have more than tripled from 2003 to 50.4 billion yuan, or roughly $8.3 billion, last year.
But industry watchers say China is one tough cookie, and Mondelez is facing bigger obstacles to growth here. Consumers in the world's most populous country are curious and willing to try out new things, but that means as more brands enter the market, there are more snacks to distract them from Oreos, said Ben Cavender, a senior analyst at consultancy China Market Research in Shanghai.
Mr. Cavender said most companies are finding that Chinese consumers bore easily, so it's key for food makers to innovate and introduce new brands. "You have to keep the market constantly hooked," he said, noting that changing the packaging often isn't enough.
Mondelez has been broadening its distribution channels, expanding deeper into China's biggest cities and working with well-known figures such as former basketball star Yao Ming to promote its brands. The company has also been innovating, stocking store shelves with mini-Oreos, Ritz crackers and Chips Ahoy cookies in portable cuplike packages that resemble ramen-noodle containers. There are also more flavors in China than ever before, including green tea and birthday confetti.
Consumers like Zhou Mengmeng, who says she's stopped buying Oreos because she doesn't think they're healthy, pose another problem. Ms. Zhou, a petite 24-year-old from central Henan province, said Chinese people who ate a lot of packaged food several years ago have stopped. "We just didn't know they weren't that good for you," Ms. Zhou said, noting that she's since switched to eating more fruit.
More In Food
- How Chinese Science Could Lead to a Tastier Tomato
- Shanghai Disney Resort Rolls Out Menu with Chinese Characteristics
- Pork Shortage in China Leads to Soaring Prices, Rush to Import
- McDonald's to Supersize Its China Presence with 1,000 New Restaurants
- China Real Time Tries Pizza Hut's New Durian Pizza So You Don't Have To
- Taste of China 2016: The Top Food That Fueled WSJ's China Bureau
Mondelez executives have said they are aware that Chinese consumers are becoming more health-conscious. To address that concern, the company developed a cracker line, Pacific, with flavors such as sesame and red date are typically associated with health and traditional Chinese medicine.
Some other international biscuit makers are gaining ground in China, such as Korea's Orion Confectionery Co., which sells Choco Boy mushroom-shaped biscuits and the Choco Pie sandwich snacks, and Japan's Ezaki Glico, maker of the Pocky multi-flavored chocolate-coated pretzel sticks. Orion boosted its share of the fragmented market to 2.8% last year, up from 1.3% in 2008, according to Euromonitor. Ezaki's market share rose to 2.6% from 1.7% in the same period, according to Euromonitor.
Mondelez reported a profit of $1.77 billion, or $1 a share, in the fourth quarter, up from $569 million, or 32 cents a share, a year earlier. The company has said it is investing in emerging markets like Brazil and China, as well as restructuring to improve cost structure.
-- Laurie Burkitt. Follow her on Twitter @lburkitt


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The 10 Best Art Kisses of All Time
The Depression-era song "A Kiss to Build a Dream On," which Louis Armstrong made famous in the '50s, finishes with the lyrics: "Oh give me your lips for just a moment/ And my imagination will make that moment live/ Oh give me what you alone can give/ A kiss to build a dream on." Over the course of art history, painters, sculptors, poets, and photographers have — as the song suggests — used their vivid imaginations to bring the kiss to life as a symbol of fresh love, renewed love, and even black-and-blue love.
With Valentine's Day in mind, we've selected the 10 best art kisses — ranging from erotic embraces in paintings by Gérôme and Klimt and sensual smooches in sculptures by Rodin and Brancusi to lustful lip-locking in works on paper by Picasso and Man Ray — so that you, too, can share the love. If we missed one of your favorite make-out moments in art, tell us about it in the comments.
Click through below for a gallery of images.
Jean-Léon Gérôme's 1890 painting of Pygmalion and Galatea, from New York's Metropolitan Museum's collection, depicts a tale from Ovid's Metamorphoses of Pygmalion creating a sculpture of Galatea, which he envisions as the ideal woman and wishes could be real, being brought to life by the goddess Venus and joyfully embraced by the artist in his studio.


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Who hasn't spent a few hours trying to decided what you would fill your fantasy garage with after winning the lottery? When William Stidham recently won $600,000 he knew right away what he was buying—the 1969 Camaro he had spent the last 20 years rebuilding.
Stidham had recently made the painful decision to sell his beloved project car (not pictured) to help with the mortgage on his family home and to finance his daughter's wedding. Upon selling the car the Washington State resident wisely made an agreement with the seller that he would be able to buy the Camaro back from its new owner if he was ever able to afford it.
When MSNBC spoke with Stidham right after he found out he won the $600,000 "Hit 5" lottery, he had already made plans to bring the car home. Although we're sure William was pleased with everything about winning big, according to MSNBC "he couldn't stop talking about how excited he was to get his Camaro back."
Photo Credit: RussBowling


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Professor Chosen for Middle East Seminar in Jordan
Dr. Kim Jarvis, assistant professor of history, is one of 12 professors nationwide who will spend three weeks in Amman, Jordan, to further their teaching of Islam and Middle Eastern Culture.
The seminar "Teaching About Islam and Middle Eastern Culture" is funded by the U.S. Department of State and takes place at the American Center of Oriental Research in Amman, Jordan, Dec. 28-Jan. 19. (The center is an academic institution founded in 1968 that serves as a liaison between Jordanian institutions and international scholars.)
Sponsored by the Council of Independent Colleges and Council of American Overseas Research Centers, the seminar is designed for independent college and university professors who are not experts in Islam or Middle Eastern culture, but who are teaching or developing related courses. The three weeks in Jordan help them learn and understand the region and its effect on modern times. It includes visits to archaeological sites such as Petra and meetings with local experts and dignitaries.
Jarvis studied Islamic history while completing her doctorate. At Doane, her courses include Middle East history and an honors class on Islamic culture. She also is developing additional courses about the Middle East as part of Doane's expanding "Cultural Perspectives" component of the general education requirement.
The seminar will deepen her understanding of Middle East topics, which will benefit future Doane students as well, Jarvis said.
"Before Sept. 11, we didn't think about the Middle East so much. If we did, it normally was news about fighting. Now, it's a matter of foreign policy and daily news messages."
In her current coursework, she tries to capture for students "the dangers of assuming everyone thinks like they do."
"And I try to show the region's diversity, its influence and contributions in history, and that most Muslims condemn (terrorists) and what they are doing."
She is anxious to transfer what she learns to the classroom.
"We should be able to give students as broad an experience as we can. That's the beauty of higher education -- offering viewpoints they haven't experienced before."
While in Jordan, Jarvis also hopes to touch base with 2006 Doane graduate Kamleh Shaban, a Fulbright scholar who will spend a year in Jordan comparing Western and Islamic medicine.


text: A few years ago I had an idea for an online project that needed embedded fonts. After considering my options, I decided "I should just make my own! It can't be that hard!" In my ignorance, I greatly underestimated the magnitude of this endeavor. Although making fonts is not that "hard," it is tediously time-consuming work. It is also addictive.


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It is Monday and again I am joining in the meme over at Mentor Texts.Hop on over and join in over at the Mentor Text Blog. Just click on the picture
Virginia Roth
Second in Trilogy
Goodread's Summary
One choice can transform you--or it can destroy you. But every choice has consequences, and as unrest surges in the factions all around her, Tris Prior must continue trying to save those she loves--and herself--while grappling with haunting questions of grief and forgiveness, identity and loyalty, politics and love.
This was a reread for me. I had listened to the audio version, but decided I really needed to read it as well to follow it and prepare myself for the third one later in the year. I enjoyed reading it, and once I got started I didn't take long. I found myself grappling with - Who is that now? I was somewhat relieved to hear one of my students say she thought she would have to go back to the first book in a trilogy she is reading because she can't remember all the bits and pieces as she moves into reading the third. I thought it was old age creeping in! There is a buzz in my class about this trilogy and someone said they heard a movie is possibly being made?
Coming up I plan to read the second book in The Rosie Black Chronicles - Equinox by Lara Morgan. Thankfully the third in this trilogy is published so it won't be too long before I read the third, and I only read the first a few weeks ago!


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Digital prints – process through high resolution digital printers.
Giclee Printing- also termed Iris printing. Considered the highest form of art reproduction. Uses the highest resolution along with the finest dot matrix systems. Images are reproduced as good or better than the original. Printed on paper or canvas with 200 year archival inks. The canvas prints should be stretched. Paper Giclee prints should be mounted matted and framed under glass.
Original art paintings are available upon request.
Painted while ministering the Word thru art at Metro-West Bridge Natick, MA. '07 I was hearing in my spirit a song by Peter Gabriel, 'In Your Eyes. The light, the heat - I am complete - in Your Eyes.