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Statisticians can reuse their data to quantify the uncertainty of complex models
Cosma Shalizi
Statistics is the branch of applied mathematics that studies ways of drawing inferences from limited and imperfect data. We may want to know how a neuron in a rat's brain responds when one of its whiskers gets tweaked, or how many rats live in Manhattan, or how high the water will get under the Brooklyn Bridge, or the typical course of daily temperatures in the city over the year. We have some data on all of these things, but we know that our data are incomplete, and experience tells us that repeating our experiments or observations, even taking great care to replicate the conditions, gives more or less different answers every time. It is foolish to treat any inference from only the data in hand as certain.
If all data sources were totally capricious, there'd be nothing to do beyond piously qualifying every conclusion with "but we could be wrong about this." A mathematical science of statistics is possible because, although repeating an experiment gives different results, some types of results are more common than others; their relative frequencies are reasonably stable. We can thus model the data-generating mechanism through probability distributions and stochastic processes—random series with some indeterminacy about how the events might evolve over time, although some paths may be more likely than others. When and why we can use stochastic models are very deep questions, but ones for another time. But if we can use them in a problem, quantities such as these are represented as "parameters" of the stochastic models. In other words, they are functions of the underlying probability distribution. Parameters can be single numbers, such as the total rat population; vectors; or even whole curves, such as the expected time-course of temperature over the year. Statistical inference comes down to estimating those parameters, or testing hypotheses about them.
These estimates and other inferences are functions of the data values, which means that they inherit variability from the underlying stochastic process. If we "reran the tape" (as Stephen Jay Gould used to say) of an event that happened, we would get different data with a certain characteristic distribution, and applying a fixed procedure would yield different inferences, again with a certain distribution. Statisticians want to use this distribution to quantify the uncertainty of the inferences. For instance, by how much would our estimate of a parameter vary, typically, from one replication of the experiment to another—say, to be precise, what is the root-mean-square (the square root of the mean average of the squares) deviation of the estimate from its average value, or the standard error? Or we could ask, "What are all the parameter values that could have produced this data with at least some specified probability?" In other words, what are all the parameter values under which our data are not low-probability outliers? This gives us the confidence region for the parameter—rather than a point estimate, a promise that either the true parameter point lies in that region, or something very unlikely under any circumstances happened—or that our stochastic model is wrong.
To get standard errors or confidence intervals, we need to know the distribution of our estimates around the true parameters. These sampling distributions follow from the distribution of the data, because our estimates are functions of the data. Mathematically the problem is well defined, but actually computing anything is another story. Estimates are typically complicated functions of the data, and mathematically convenient distributions all may be poor approximations of the data source. Saying anything in closed form about the distribution of estimates can be simply hopeless. The two classical responses of statisticians have been to focus on tractable special cases, and to appeal to asymptotic analysis, a method that approximates the limits of functions.
If you've taken an elementary statistics course, you were probably drilled in the special cases. From one end of the possible set of solutions, we can limit the kinds of estimator we use to those with a simple mathematical form—say, mean averages and other linear functions of the data. From the other, we can assume that the probability distributions featured in the stochastic model take one of a few forms for which exact calculation is possible, either analytically or via tables of special functions. Most such distributions have origin myths: The Gaussian bell curve arises from averaging many independent variables of equal size (say, the many genes that contribute to height in humans); the Poisson distribution comes from counting how many of a large number of independent and individually improbable events have occurred (say, radium nuclei decaying in a given second), and so on. Squeezed from both ends, the sampling distribution of estimators and other functions of the data becomes exactly calculable in terms of the aforementioned special functions.
That these origin myths invoke various limits is no accident. The great results of probability theory—the laws of large numbers, the ergodic theorem, the central limit theorem and so on—describe limits in which all stochastic processes in broad classes of models display the same asymptotic behavior. The central limit theorem (CLT), for instance, says that if we average more and more independent random quantities with a common distribution, and if that common distribution is not too pathological, then the distribution of their means approaches a Gaussian. (The non-Gaussian parts of the distribution wash away under averaging, but the average of two Gaussians is another Gaussian.) Typically, as in the CLT, the limits involve taking more and more data from the source, so statisticians use the theorems to find the asymptotic, large-sample distributions of their estimates. We have been especially devoted to rewriting our estimates as averages of independent quantities, so that we can use the CLT to get Gaussian asymptotics. Refinements to such results would consider, say, the rate at which the error of the asymptotic Gaussian approximation shrinks as the sample sizes grow.
To illustrate the classical approach and the modern alternatives, I'll introduce some data: The daily closing prices of the Standard and Poor's 500 stock index from October 1, 1999, to October 20, 2009. (I use these data because they happen to be publicly available and familiar to many readers, not to impart any kind of financial advice.) Professional investors care more about changes in prices than their level, specifically the log returns, the log of the price today divided by the price yesterday. For this time period of 2,529 trading days, there are 2,528 such values (see Figure 1). The "efficient market hypothesis" from financial theory says the returns can't be predicted from any public information, including their own past values. In fact, many financial models assume such series are sequences of independent, identically distributed (IID) Gaussian random variables. Fitting such a model yields the distribution function in the lower left graph of Figure 1.
An investor might want to know, for instance, how bad the returns could be. The lowest conceivable log return is negative infinity (with all the stocks in the index losing all value), but most investors worry less about an apocalyptic end of American capitalism than about large-but-still-typical losses—say, how bad are the smallest 1 percent of daily returns? Call this number q0.01; if we know it, we know that we will do better about 99 percent of the time, and we can see whether we can handle occasional losses of that magnitude. (There are about 250 trading days in a year, so we should expect two or three days at least that bad in a year.) From the fitted distribution, we can calculate that q0.01=–0.0326, or, undoing the logarithm, a 3.21 percent loss. How uncertain is this point estimate? The Gaussian assumption lets us calculate the asymptotic sampling distribution of q0.01, which turns out to be another Gaussian (see the lower right graph in Figure 1), implying a standard error of ±0.00104. The 95 percent confidence interval is (–0.0347, –0.0306): Either the real q0.01 is in that range, or our data set is one big fluke (at 1-in-20 odds), or the IID-Gaussian model is wrong.
From its origins in the 19th century through about the 1960s, statistics was split between developing general ideas about how to draw and evaluate statistical inferences, and working out the properties of inferential procedures in tractable special cases (like the one we just went through) or under asymptotic approximations. This yoked a very broad and abstract theory of inference to very narrow and concrete practical formulas, an uneasy combination often preserved in basic statistics classes.
The arrival of (comparatively) cheap and fast computers made it feasible for scientists and statisticians to record lots of data and to fit models to them. Sometimes the models were conventional ones, including the special-case assumptions, which often enough turned out to be detectably, and consequentially, wrong. At other times, scientists wanted more complicated or flexible models, some of which had been proposed long before but now moved from being theoretical curiosities to stuff that could run overnight. In principle, asymptotics might handle either kind of problem, but convergence to the limit could be unacceptably slow, especially for more complex models.
By the 1970s statistics faced the problem of quantifying the uncertainty of inferences without using either implausibly helpful assumptions or asymptotics; all of the solutions turned out to demand even more computation. Perhaps the most successful was a proposal by Stanford University statistician Bradley Efron, in a now-famous 1977 paper, to combine estimation with simulation. Over the last three decades, Efron's "bootstrap" has spread into all areas of statistics, sprouting endless elaborations; here I'll stick to its most basic forms.
Remember that the key to dealing with uncertainty in parameters is the sampling distribution of estimators. Knowing what distribution we'd get for our estimates on repeating the experiment would give us quantities, such as standard errors. Efron's insight was that we can simulate replication. After all, we have already fitted a model to the data, which is a guess at the mechanism that generated the data. Running that mechanism generates simulated data that, by hypothesis, have nearly the same distribution as the real data. Feeding the simulated data through our estimator gives us one draw from the sampling distribution; repeating this many times yields the sampling distribution as a whole. Because the method gives itself its own uncertainty, Efron called this "bootstrapping"; unlike Baron von Münchhausen's plan for getting himself out of a swamp by pulling himself out by his bootstraps, it works.
Let's see how this works with the stock-index returns. Figure 2 shows the overall process: Fit a model to data, use the model to calculate the parameter, then get the sampling distribution by generating new, synthetic data from the model and repeating the estimation on the simulation output. The first time I recalculate q0.01 from a simulation, I get -0.0323. Replicated 100,000 times, I get a standard error of 0.00104, and a 95 percent confidence interval of (–0.0347, –0.0306), matching the theoretical calculations to three significant digits. This close agreement shows that I simulated properly! But the point of the bootstrap is that it doesn't rely on the Gaussian assumption, just on our ability to simulate.
The bootstrap approximates the sampling distribution, with three sources of approximation error. First there's simulation error, using finitely many replications to stand for the full sampling distribution. Clever simulation design can shrink this, but brute force—just using enough replications—can also make it arbitrarily small. Second, there's statistical error: The sampling distribution of the bootstrap reestimates under our fitted model is not exactly the same as the sampling distribution of estimates under the true data-generating process. The sampling distribution changes with the parameters, and our initial fit is not completely accurate. But it often turns out that distribution of estimates around the truth is more nearly invariant than the distribution of estimates themselves, so subtracting the initial estimate from the bootstrapped values helps reduce the statistical error; there are many subtler tricks to the same end. The final source of error in bootstrapping is specification error: The data source doesn't exactly follow our model at all. Simulating the model then never quite matches the actual sampling distribution.
Here Efron had a second brilliant idea, which is to address specification error by replacing simulation from the model with resampling from the data. After all, our initial collection of data gives us a lot of information about the relative probabilities of different values, and in certain senses this "empirical distribution" is actually the least prejudiced estimate possible of the underlying distribution—anything else imposes biases or preconceptions, which are possibly accurate but also potentially misleading. We could estimate q0.01 directly from the empirical distribution, without the mediation of the Gaussian model. Efron's "nonparametric bootstrap" treats the original data set as a complete population and draws a new, simulated sample from it, picking each observation with equal probability (allowing repeated values) and then re-running the estimation (as shown in Figure 2).
This new method matters here because the Gaussian model is inaccurate; the true distribution is more sharply peaked around zero and has substantially more large-magnitude returns, in both directions, than the Gaussian (see the top graph in Figure 3). For the empirical distribution, q0.01=–0.0392. This may seem close to our previous point estimate of –0.0326, but it's well beyond the confidence interval, and under the Gaussian model we should see values that negative only 0.25 percent of the time, not 1 percent of the time. Doing 100,000 non-parametric replicates—that is, resampling from the data and reestimating q0.01 that many times—gives a very non-Gaussian sampling distribution (as shown in the right graph of Figure 3), yielding a standard error of 0.00364 and a 95 percent confidence interval of (–0.0477, –0.0346).
Although this is more accurate than the Gaussian model, it's still a really simple problem. Conceivably, some other nice distribution fits the returns better than the Gaussian, and it might even have analytical sampling formulas. The real strength of the bootstrap is that it lets us handle complicated models, and complicated questions, in exactly the same way as this simple case.
To continue with the financial example, a question of perennial interest is predicting the stock market. Figure 4 is a scatter plot of the log returns on successive days, the return for today being on the horizontal axis and that of tomorrow on the vertical. It's mostly just a big blob, because the market is hard to predict, but I have drawn two lines through it: a straight one in blue, and a curved one in black. These lines try to predict the average return tomorrow as functions of today's return; they're called regression lines or regression curves. The straight line is the linear function that minimizes the mean-squared prediction error, or the sum of the squares of the errors made in solving every single equation (called the least squares method). Its slope is negative (–0.0822), indicating that days with below-average returns tend to be followed by ones with above-average returns and vice versa, perhaps because people try to buy cheap after the market falls (pushing it up) and sell dear when it rises (pulling it down). Linear regressions with Gaussian fluctuations around the prediction function are probably the best-understood of all statistical models—their oldest forms go back two centuries now—but they're more venerable than accurate.
The black curve is a nonlinear estimate of the regression function, coming from a constrained optimization procedure called spline smoothing: Find the function that minimizes the prediction error, while capping the value of the average squared second derivative. As the constraint tightens, the optimal curve, the spline, straightens out, approaching the linear regression; as the constraint loosens, the spline wiggles to try to pass through each data point. (A spline was originally a flexible length of wood craftsmen used to draw smooth curves, fixing it to the points the curve had to go through and letting it flex to minimize elastic energy; stiffer splines yielded flatter curves, corresponding mathematically to tighter constraints.)
To actually get the spline, I need to pick the level of the constraint. Too small, and I get an erratic curve that memorizes the sample but won't generalize to new data; but too much smoothing erases real and useful patterns. I set the constraint through cross-validation: Remove one point from the data, fit multiple curves with multiple values of the constraint to the other points, and then see which curve best predicts the left-out point. Repeating this for each point in turn shows how much curvature the spline needs in order to generalize properly. In this case, we can see that we end up selecting a moderate amount of wiggliness; like the linear model, the spline predicts reversion in the returns but suggests that it's asymmetric—days of large negative returns being followed, on average, by bigger positive returns than the other way around. This might be because people are more apt to buy low than to sell high, but we should check that this is a real phenomenon before reading much into it.
There are three things we should note about spline smoothing. First, it's much more flexible than just fitting a straight line to the data; splines can approximate a huge range of functions to an arbitrary tolerance, so they can discover complicated nonlinear relationships, such as asymmetry, without guessing in advance what to look for. Second, there was no hope of using a smoothing spline on substantial data sets before fast computers, although now the estimation, including cross-validation, takes less than a second on a laptop. Third, the estimated spline depends on the data in two ways: Once we decide how much smoothing to do, it tries to match the data within the constraint; but we also use the data to decide how much smoothing to do. Any quantification of uncertainty here should reckon with both effects.
There are multiple ways to use bootstrapping to get uncertainty estimates for the spline, depending on what we're willing to assume about the system. Here I will be cautious and fall back on the safest and most straightforward procedure: Resample the points of the scatter plot (possibly getting multiple copies of the same point), and rerun the spline smoother on this new data set. Each replication will give a different amount of smoothing and ultimately a different curve. Figure 5 shows the individual curves from 800 bootstrap replicates, indicating the sampling distribution, together with 95 percent confidence limits for the curve as a whole. The overall negative slope and the asymmetry between positive and negative returns are still there, but we can also see that our estimated curve is much better pinned down for small-magnitude returns, where there are lots of data, than for large-magnitude returns, where there's little information and small perturbations can have more effect.
Bootstrapping has been ramified tremendously since Efron's original paper, and I have sketched only the crudest features. Nothing I've done here actually proves that it works, although I hope I've made that conclusion plausible. And indeed sometimes the bootstrap fails; it gives very poor answers, for instance, to questions about estimating the maximum (or minimum) of a distribution. Understanding the difference between that case and that of q0.01, for example, turns out to involve rather subtle math. Parameters are functions of the distribution generating the data, and estimates are functions of the data or of the empirical distribution. For the bootstrap to work, the empirical distribution has to converge rapidly on the true distribution, and the parameter must smoothly depend on the distribution, so that no outlier ends up unduly influencing the estimates. Making "influence" precise here turns out to mean taking derivatives in infinite-dimensional spaces of probability distribution functions, and the theory of the bootstrap is a delicate combination of functional analysis with probability theory. This sort of theory is essential to developing new bootstrap methods for new problems, such as ongoing work on resampling spatial data, or model-based bootstraps where the model grows in complexity with the data.
The bootstrap has earned its place in the statistician's toolkit because, of all the ways of handling uncertainty in complex models, it is at once the most straightforward and the most flexible. It will not lose that place so long as the era of big data and fast calculation endures.
You can find this online at http://www.americanscientist.org/issues/num2/2010/3/the-bootstrap/1
© 2016 Sigma Xi, The Scientific Research Society


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[quote user="JPizzack"]
[quote user="Morehead State"]Well thats just not my style. I'm still hurting from the Flipper Anderson game.[/quote]

im kinda kidding. it's very rare that I do any trash talking. sure here I do to you about the sox maybe lol....but i just dont do it really.
mostly because I have a temper and I fear things may get carried away over something ridiculous. Afterall....I did oncedamn nearincite ariot at woodstock over a bag of popcorn, so...i wouldnt put it past myself.

I'll talk a little smack (or not so little) to Yanks fans or Pats fans or Eagles fans I know, but not until time has passed to ease the pain.

subset: commoncrawl


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Thinking Rock allows you to collect your thoughts and process them into actions, projects, information or future possibilities. Actions can be done by you, delegated to someone else or scheduled for a particular date. Projects can be organised with ordered actions and sub-projects. You can review all of your actions, projects and other information quickly and easily to see what you need to do or to choose what you want to do at a particular time.
What's New
- Bug fix: week number in weekly calendar view
- Bug fix: timestamp time can be in 24 hours format. Settings under Miscellaneous/Calendar tab
- OS X 10.4 or later
- Java 1.5 or later


text:
Word Find Game
Downtown (Up to 5 of 5 Words)
- How to Play the Game
- To circle a word, click at one end of the hidden word and drag the mouse to the end of the word.
- If you see fewer than 5 words, try clicking the Rescramble button.
- Option
- If you can't find a word, select it in the list, then click "Find Words".
Phrases and words with hyphens are not included in this game.
Known Bug: The menu goes behind any Java applet.


text:
Stay connected with us to get the latest health and fitness news, innovative workouts, healthy recipes and wellness tips.
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Pistachio crust teams up with a savory mustard-dill sauce for an exceptional tuna dish. Choose "sushi grade" tuna steaks if you prefer a milder flavor. Make it a meal: Serve with brown rice and steamed broccolini.
Nutrition Profile:
Diabetes Appropriate
Healthy Weight
Heart Healthy
High Potassium
Low Calorie
Low Carb
Low Cholesterol
Low Sat Fat
Low Sodium
Serves 4
Prep Time 30 min
Total Time 30 min.
Step 1
Place shallot, bay leaf and wine in a small saucepan and bring to a boil. Reduce until the wine is almost evaporated, about 5 minutes. Remove from the heat, discard bay leaf and transfer to a small bowl. Add sour cream, lemon juice, 1 teaspoon dill, mustard and 1/4 teaspoon salt; stir to combine.
Step 2
Put breadcrumbs, pistachios, the remaining 1 teaspoon dill and 1/4 teaspoon salt in a blender or food processor. Process until finely ground. Transfer to a shallow bowl. Dredge both sides of the tuna in the pistachio mixture.
Step 3
Heat oil in a large nonstick skillet over medium heat. Add the tuna and cook until browned, adjusting the heat as necessary to prevent burning, 4 to 5 minutes per side for medium-rare. Serve with the lemon-dill sauce.
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text: Hi gang- I'm from the beautiful, rainy Northwest. I bought my first Colorado (2006 Ext Cab) in Jan 2009 and immediately loved it. A red light runner took it away from me last week and thankfully the airbags deployed saving my wife and I from any real harm. I had to get another one so we just picked up a 2008 Ext Cab 4x4 in Inferno Orange. These trucks are the best and I look forward to conversing with lots of other happy Colorado owners!


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So happy to find an alcohol-free version!
Verified Purchase
So happy to find an alcohol-free version!
Have been using Bach Rescue Remedy for years for my cats - but most of them don't take too well to the strong alcohol smell. So I am really happy to find this alcohol-free version here in iherb! But please take note, everybody - there's the exact same alcohol-free formula packaged for kids, THAT'S MUCH CHEAPER THAN THIS ONE FOR PETS! I bought one of this before I saw that other ... so I bought the other one too!
So happy to find an alcohol-free version!
Posted by Reviewer3000993 on Oct 08, 2013 | Verified Purchase
Have been using Bach Rescue Remedy for years for my cats - but most of them don't take too well to the strong alcohol smell. So I am really happy to find this alcohol-free version here in iherb! But please take note, everybody - there's the exact same alcohol-free formula packaged for kids, THAT'S MUCH CHEAPER THAN THIS ONE FOR PETS! I bought one of this before I saw that other ... so I bought the other one too!
Much Calmer Cat Thanks To Rescue Remedy
Posted by MGG-ThreeTwoFour on Jul 22, 2015 | Verified Purchase
One of my cats, a female Bombay/Bermese mix, has been stress grooming to the point of bald patches on her haunches, belly & elbows. It was difficult to get her to eat since mealtime was the most stressful activity for her, for some reason. After testing negative for everything including common allergies, it was determined that she was in the beginning stages of "kitty senility". (She is 12 years old.) My vet prescribed an anti-anxiety medication for her but when she didn't show any signs of improvement after a couple of weeks, I decided to try a more natural approach with the Rescue Remedy Pet product. In less than 48 hours I noticed a dramatic difference in her behavior. She was much calmer, less skiddish and was able to eat her meals without constantly looking over her shoulder for that "phantom predator". We can now also enter a room without her fleeing in a panic to run and hide under the bed. She is very high-strung so I had to give her a double dose of 8 drops in her food, twice per day for the first week or so. Now, after 1 month I've been able to reduce her dosage to 4 drops and her fur has almost completely grown back. I can't say enough good things about this product! It has brought back my sweet little girl who has returned to her loving, affectionate & confident self. I recommend. ** For new customers of iHerb, please also visit my page for more product reviews **
Left pets for one week.
Posted by Reviewer3034644 on Dec 09, 2009 | Verified Purchase
Since we have 6 cats and 1 dog, we tend to leave them home when we travel. A week is our outermost time away. Last time we left, I put the rescue remedy in their water. Since the Rescue Remedy helped me so much in taking care of my grandkids, I can only assume that my pets didn't panic. They seemed fine when we returned.
Work well with my cat
Posted by garyofca on Jan 11, 2014 | Verified Purchase
You would see the huge difference after using it. Please also visit my page for more reviews, especially for new customers to iHerb.
This product is fabulous.
Posted by Reviewer3038641 on Aug 23, 2010 | Verified Purchase
I have a 4.5 yr old Yorkie who was rescued from a substandard puppy mill. Not having been socialized as a puppy and used to only a small cage for most of his life he is terrified of new situations. I love to travel by car and he would be so terrified he would throw up every car trip even to the store. I got Rescue Remedy which was recomended by the fearful dog book the humane society required me to purchase and when I squirt it into his mouth (he doesn't like treats) he is calmer for our trips and sleeps most of the time. No more throwing up. I wholeheartedly recomend it!
Rescue Remedy
Posted by Reviewer1588471 on Apr 20, 2009 | Verified Purchase
Excellent for your pets when they are travelling with you and for other times when they are stressed
Great flower power...
Posted by Reviewer2648186 on Jun 04, 2010 | Verified Purchase
I bought this by mistake. I was in a hurry and wanted the one for ppl. I emailed the company and they said it was 100% the same product and therefore completely safe to use. The only difference is the perservatives - this one contains glycerin and water. If I use this alot I notice i get some soreness under my tounge so i dont use it that often. I'm sure it is an excellent product for animal as the original is for ppl. Im gonna use this on my new kitten when I get it home.
Bach Original Flower Essemces
Posted by Reviewer3331684 on Mar 24, 2011 | Verified Purchase
Great product. . .lives up to all expectations. Used only two drops for my Yorkie before grooming and 4 drops for my 54-pound "wild" puppy! Will always have on hand.
Use every day
Posted by CoolinArizona on Aug 12, 2011 | Verified Purchase
I rescued a year old puppy about 6 months ago and he was having issues with sleeping through the night because he was distressed being in a new place/bed. I started out giving him 4 drops every night with a little water and he loves it and laps it up and sleeps through the night as do I. If he's going to the Vet or something new that might upset him I just put a drop or 2 on my finger and it settles him down immediately. I always have a back up in the car for those scary trips
Posted by 5731085735222173366 on Nov 06, 2013 | Verified Purchase
My dog is struggling with anxiety and can sometimes have seizures where she is very stressed and will not calm down. 4 drops of Rescue Remedy in her mouth and it takes 1 minute before she lies down and relax. GREAT product!


text:
Discovering the Cowon X7 is like spotting a live dinosaur, roaming around Britain's green fields, battling for grazing room among the cows and sheep. It's a hard drive MP3 player in a market that has long been dominated by flash memory devices. The result is that this is one enormous beast - more a Brachiosaurus than an Iguanodon (to really stretch that metephor) - looking more like a PDA than a touchscreen smartphone or simple music player. It thankfully has a few tricks up its sleeve to justify this complete disregard for evolution.
The Cowon X7 seems huge next to almost all current portable devices. The 120GB internal hard drive makes sure it's not slim at 14.5mm, and the 4.3in screen is large even by today's giant touchscreen standards. The body stretches out beyond the screen too, with a generous bezel making the X7 significantly larger than the iPod Classic 160GB - the only big-name rival for this media player at present.
Yes, it's a biggie, but it doesn't feel that much heavier than the iPod Classic in-hand, even though at 212g it is aroun 50g more. What makes the Cowon X7 feel so grand, so oversized, is its width. At 78.6mm wide it'll fill even the largest mitt, and those with smaller hands will have trouble wrapping your digits comfortably around its body. Anyone thinking they're getting a svelte, ultra-pocketable media player with the X7 is clearly looking in the wrong place.
Build quality is great though, and the touchscreen removes the need for a set of design-diluting physical playback controls. There's a pair of volume controls on the left hand-side, a power button on the right and a menu button front and centre, but these are the only physical buttons on-show. On the Cowon X7's bottom are the 3.5mm headphone jack, power socket and a flap containing the connector port that doubles as a USB connection, video out and audio in - the last two requiring extra cables not included in the box.
A utilitarian workhorse, the Cowon X7's front also features a speaker, and there's a mic around the back, both of which are missing from the iPod Classic. The closer you look into the player, the more you see that its features start to justify its bulky body. It doesn't have the desirability of an iPod Touch. But it does have a few features that the Touch can't replace with its wealth of apps, and of course it has the advantage of it's all-too-rare huge storage.
NEW 4.3inch color TFT LCD COWON MP3 Player X7-120G-WH from JAPAN$491.97 View Item
1ft 30cm SHORT USB Data Sync & Charger Cable for COWON MP3 player X7 J3 S9$5.99 View Item
3ft 1m LONG USB Data Sync & Charger Cable BLACK for COWON MP3 Player X7 J3 S9$6.99 View Item
REALOOK Cowon X7 Screen Protector, Crystal Clear 2-PK$10.99 View Item
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text:
Modern and Luxurious Double Room
Size19 m²
Floor No.
- Family/child friendly
- Kitchen
- Balcony/terrace
- Towels
- Lockable room
Accommodation summary
|Widegate St, E17HP London, United Kingdom
|Property type
|Private room
|Property ID
|Acceptance rate
|Response time
|A few hours
|Calendar updated
|More than half a year ago
This room is located in a brand new intimate boutique accommodation designed to be the gateway to your London experience, whether it is for business, a discovery weekend, a mini break or a long stay. In the centre of the metropolis, it is situated next to bishopgate, one of the seven main gates in London. Situated in the financial heart of the city, next to fashionable Spitalfields market, near to West End shopping as well as easy access to international travel. So, whatever the reason for your stay, you are never far from all the attractions and facilities of this great city.
It has excellent transport links: Closest tube station - Liverpool Street- Access to Central / Hammersmith and City / Metropolitan and Circle Lines; National Rail / Stanstead Express 3 minutes walk to Moorgate and Northern Line; 10 minutes walk to District Line International Travel London City Airport 5 miles Heathrow 17 miles / Gatwick 25 miles Luton 28 miles Eurostar – St Pancras, 15 minutes direct by underground or taxi Eurostar will be available soon from the new Shoreditch station within walking distance.
It is also close to a number of famous landmarks which is perfect for guests wanting to explore the City of London. Famous landmarks include The Tower of London/Tate Modern/St. Pauls Cathedral The London Eye/West End Shopping Close to Brick Lane/Spitalfields Close to Moorfields world famous Eye hospital Close to Old Street - home to UK's Silicon Valley Close to creative district centred around brick lane and Famous Hoxton Square and Shoreditch.
House rulesNo smoking allowed.
|Check-in after
|Check-in before
|On arrangement
|Check-out before
|Cancellation Policy
Reviews for this host's other properties
Really cosy and comfortable room, I highly recommend the house, very friendly host.
Clean & comfortable room. Good location.
Nice quiet but central location. Excellent host.
We stayed for a week in this apartment in Brick Lane area just a short walk from Liverpool Street station. The neighbourhood is lively with a lot of restaurants. The apartment is nice and clean, and the reception very friendly.
There is a diningtable with chairs connected to the small kitchen, but we missed some comfortable chairs (there was only one in one of the bedrooms). Nevertheless if you walk around the city all day and just need a place to sleep, it is absolutely perfect.
Very comfortable clean room, no hassle, will be back.
Quiet apartment. Clean & comfortable room.
Great host. Clean & comfortable room. Quiet location.
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I love this product! I have multiple headphones - each for different purposes. This is great way to control the mess in my bag. It's also s great gift and very inexpensive - all co-workers getting one! Only one challenge - the rubber seems to pick up and show dirt/oil (from hands).4
I ordered the teal Quirky and it didn't look like the white one in the picture - but that is okay! I still really like what I got. I listen to headphones almost daily at my job, so it is great to grab my headphones out of my purse without pulling gum wrappers, keys, pens, etc with them. My only bummer about the product is the volume button on my headphones is placed ever so oddly that they don't wrap tightly/perfectly around the Quirky shape. However, for the price and organization now of my purse? I am happy!5


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David M. Williams
David M. Williams
David M. Williams, 92, of Minneapolis, passed away at home on Oct. 1, 2013. Dave lived life on his terms and rarely met a person he didn't like. He was a Greyhound bus driver for 43 years and often drove the Minneapolis to Bemidji and Duluth runs. He joined the Osman Shrine Clowns in 1982 and performed in the Shrine Circus for many years.
He is survived by his children, David, Dennis (Mim) and Darcie (Ed); sister, Marion (Art); brother, Roger (Suzanne); seven grandchildren and 10 great-grandchildren; nieces, nephews and many loving friends.
He was proceeded in death by his ex-wife, Virginia Bundy Williams.
Services were held Oct. 7 at University Lutheran Church of Hope.
Arrangements were with Washburn-McReavy Hillside, 19th Ave. N.E., Minneapolis.


text: When I was out checking on my hive today I scraped out some of the dead bees and noticed that a couple of them had mites on them. One had at least 4. I am sure it's too far into the winter (at least for my area) for me to do anything but I was wondering if any of you had any good advice on what to do. I am afraid I am just going to have to wait until spring before I can do any real intervention.


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Features Description - Web Project Template Files
This report is part of the Template Files for Web Projects bundle.
OverviewWeb Project Template Files: Agile Toolkit
Authors: Sonia Kay, Econsultancy and other expert contributors
Title: Feature Description
About this GuideFeature cards are the Agile equivalent of articulating detailed requirements. A feature (sometimes called a story) describes in plain English what the system has to do. It is written from the user perspective so for instance, a feature might be "The customer must be able to book a trip to any European city including travel and accommodation". Working on the "test first" principle, each feature card must also state how the feature will be tested for completion. Once a feature is written it is incorporated in the Features Tracking Matrix where it is prioritised and allocated to an iteration.
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Sophia Bush's pussy gets the oral treatmentThursday, April 29th, 2010
As a sex symbol, Sophia Bush needs to keep up with her title by letting herself get caught in slutty situations like in these pictures I'm about to show you. Aside from getting her pussy occupied by a cum-popping cock, she also likes just laying back and getting the oral tornado by her fuck buddy. She knows how, sometimes, getting your cunt teased by a wriggly tongue can be a lot more heavenly and ecstatic than getting pounded by a massive cock. And it's probably true, even from a guy's standpoint: chicks moan louder and squirt faster when you're toying with their pussies.
What's even better with Sophia Bush is that, once you've spent your strength and cum with her cum-sapping eagerness (the one weakness us guys wish we didn't have), you can just lie back and watch her lady friend continue pleasuring her by spreading her throbbing pussy and licking it deep and hardcore. You're probably already spent too, from ogling at Sophia Bush's dirty pussy licking pictures, but there's more past the link if you want a second round later on.


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December 7, 2005 -- Cary , North Carolina í¢â'¬" CDV Software Entertainment has announced that it will release í�"berSoldier, a WWII FPS for the PC, in March 2006. í�"berSoldier will challenge players to take on the role of a genetically modified super-soldier brought back from beyond the grave, as he seeks retribution against the enemies that surround him. Combining tactical supernatural powers, a veritable arsenal of historically based weaponry and rich mission diversity, í�"berSoldier will deliver a pulse-pounding and original FPS experience.
In development by Burut Creative Team ( Burut CT ), �berSoldier will require players to join resistance fighters in the struggle to defeat Nazi occupation forces in dozens of action-packed missions that require quick, on-your-feet thinking and tactical prowess. "�berSoldier 's high quality graphics, dynamic physics engine and realistic rag-doll effects will offer players an affordably-priced yet high-quality game experience," stated company spokesperson, Mario Kroll. "We believe that �berSoldier will provide a fun, fast-paced alternative to CDV's traditionally more cerebral game offering, thus complementing CDV's impressive 2006 line-up extremely well."


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Canada Has its Very Own Healing Lake
Adrian Brijbassi | Posted 02.16.2013 | Canada Travel
Read More: Therapeutic, Saskatchewan, Manitou Springs Hotel and Spa, Mineral Spa, Village Perk, vacay.ca, Healing, Travel, Manitou Beach, Dead Sea of Canada, Canada, Mineral Lake Healing, Manitou Beach Healing Lake, Healing Waters, Canada Travel News
When you drive up to Manitou Beach in Saskatchewan, you might wonder yourself what you are doing here and just how long you will spend. Not that it seems foreboding, dangerous or derelict. There just isn't much here and what is in place doesn't have visual appeal. Even the lake, the primary reason to visit, is murky and vacant. But residents insist there's magic in the waters of the lake


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HT4100 4.1, 4.5, 4.9 Discussion, The "4.9 liter turbocharger, stage 1" thread. in Cadillac Engine Discussion; Damn people! I have not forgotten about this project, but it has been placed on hold because of many other ...
Re: The "4.9 liter turbocharger, stage 1" thread.
Damn people!
I have not forgotten about this project, but it has been placed on hold because of many other things. In the last year, I have purchased a new home, I have been promoted at work, I have been trying to wrap up school, and have been dealing with other automotive related things not concerning this forum. I should also note that the transmission on the Seville took a nose dive to Hell and that has also been a factor in not completing this project; the tranny will be done with a nice LSD however!
Now for the good news...
Since I have become more settled in my house, I will be getting back to the project soon. I don't really want to put a time table on this because I have some home projects to do too, but I have all the pieces necessary to build this project. I'm not going to say what route I am taking either, but I will say this: everyone who gave me credible input in this thread will get credit where do! I want the final results to be a total surprise...I will give a small hint however: I do have a complete Allante intake setup, fuel injectors included...
Also, Tom, where the Hell are ya going dude??!! Hit me a PM and give me your new email before you leave if you'd like, I want to talk more about my ideas here!!!
All that said, please bear with me on this thing for a little while longer!
- 03-18-08 10:05 PM #212Cadillac Owners Member
- Automobile(s): 1994 Sedan DeVille
- Join Date
- Jan 2008
- Posts
- 6
Re: The "4.9 liter turbocharger, stage 1" thread.
Good luck! I have a 94 Sedan DeVille with the 4.9L. It's a great motor, and it's about time someone does something with it. It's a cadillac motor, I truly believe it can handle upgrades. Can't wait to see those 1/4 mile times when you're done! U should call it the 91 STS-V haha, sure beats a 4.4L.
Re: The "4.9 liter turbocharger, stage 1" thread.
I wouldn't push the boost too hard with stock pistons. Even the LT1's only can handle 6 psi before things start coming out in pieces....And they were meant to be abused....
I would look seriously into o-ringing the block or heads. A big limit is going to be the stock head gaskets, no performance once available. Even the 301 Turbo V8's got o-ringed gaskets..... and I blew 2 sets of them....But I beat the Mustang both times.....
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- 07-08-08 12:43 AM #214Cadillac Owners Member
- Join Date
- Apr 2005
- Posts
- 38
Re: The "4.9 liter turbocharger, stage 1" thread.
I really really really really REALLY wish that people would stop using words like "The ____ engine can only handle __ psi before it breaks." tuning is a HUGE part of whether or not something breaks and all turbos are NOT created equal. 6 psi on a GT12 is not the same 6 psi on a GT60. You need to think about VOLUME when you're describing or discussing turbos. That is why the flow maps are so important when you start turbocharging something that isn't normally turbocharged. Take one small T3 60 trim (largest of the Garrrett T3 before TO4B and TO4E) turbo on a 130-150 ci engine and you may see 300 hp on 18 psi at the point where the turbo is stretched thin and being overworked. Take that same engine and use a TO4B or TO4E and you may see 300 hp on 6-8psi with the turbo barely being used. Now that that same TO4B or E and put it on an engine twice the size and it's the same deal...you need engine to make boost and you need turbo to make power. A small engine isnt going to be too happy with a large turbo the same way a large engine with a small turbo is. Bottom line is that all turbos arent created equal and you CANNOT SAY that "___psi is the highest you can go on stock internals" unless you're describing WHICH TURBO AS WELL. Go back to my posts on the GM that he's thinking of using. The turbo itself maxes out at barely 440 cfm and is capable of running 20 psi but running that much boost on that small turbo will do one thing, create heat, and make it that much harder to tune. You really need to think of your HP GOAL before you think or buy your turbo.
As for what psi an engine fails at...they all fail at some point. I recently tuned a 1.6L B16 (Honda) engine that made 550+ hp on a GT35 turbo with stock internals. To some, the ignorant (still stuck on web forums being keyboard racers) are still stuck in the mindset of "The B16 can only handle 6 psi on stock internal and maybe 200 hp before the rods bend" well guess what...mine was on 26 psi. Tuning is key and knowing which turbo when you say things like ___psi.
Re: The "4.9 liter turbocharger, stage 1" thread.
I don't plan on being one of those guys that has something unpractical for use, so when I say that I want 400 HP on a built engine, then I am likely looking at 7-9 psi of boost on top of an engine that has a mild cam, port and polish, Allante intake and other gadgets (I pretty much have the aforementioned items I need there at that)...
That said, the project is still taking a bit of time. House is going through quite a few changes, but I have a new 4.9 liter ($65 from junkyard half-price day!) that I am working on with a few neat surprises in store, including my device for forced induction. The transmission is also done and will likely get a run this weekend to see what needs to be done there - upgraded 3.33 FDR with an LSD, beefier internals, shift improvements, and a Superchip for this transmission combo that I actually found in a junkyard! It is from a 1992 STS with the 3.33 FDR...
Updates soon, I promise!!!
Re: The "4.9 liter turbocharger, stage 1" thread.
Cool! Killer price on the 4.9!
The idea is NOT to explode the engine the first time boost is hit. So with cast pistons and a bottom end never intending to see boost, keeping it low below 10 psi is crucial.
Illumina, I might have an intercooler for you, PM me.... It is in flux, but possible....
- 07-10-08 12:37 AM #217Cadillac Owners Member
- Join Date
- Apr 2005
- Posts
- 38
Re: The "4.9 liter turbocharger, stage 1" thread.
Again, not necessarily. The pressure being put in isnt as important as the volume of air being put in at that given pressure. You need to specify which turbo and which volume (how much CFM at given psi) when you're discussing which psi. If you have a turbo that doesnt flow enough volume no matter what psi you're run it at, you don't have much to worry about when it comes to pistons melting, cracking or rods bending. I'll give you this example using the stock MX6 2.2L F2T engine and the stock RHB5 VJ11 turbocharger. The max CFM that this engine is capable of at redline (6,000 rpm) is 235 CFM and that is at 100% VE. The turbo itself is barely capable of 200-250CFM per the flow map. The stock boost on this turbo is 8.7 psi but even if you raise the boost to 20 psi (max) it still isnt enough flow to reduce the AFR from rich to lean. Even at 20 psi the AFR is still pig rich in the 11's. Bottom line, if your turbo is sized accordingly, you don't have nearly as much to worry about. The GM series that he is looking at is sized accordingly for this engine, psi, engine CID, RPM, and target power output. You cannot say ___ psi will ruin the engine when you don't which turbo. Generically saying ___ psi, or "Stay under ___ pis and you'll be okay" doesnt work if you don't mention volume at that specified PSI.
I will say this, most engines can handle at least half an atmosphere (6-8 psi) which is a good start regardless of which turbo it is. I will agree with you there, but the rest no. We're kind of on the same page.
EDIT: PS- I don't come here often, WTF is Casino cash? lol
Re: The "4.9 liter turbocharger, stage 1" thread.
I got you.... I have heard the LT1 can only take 6 psi, more than that they have real problems with the hypereutectic pistons breaking.
Re: The "4.9 liter turbocharger, stage 1" thread.
Just mentioning I am still kicking around, I pop in hear and look around every now and again.
My 4.9 is still running great, however I am now getting ready to install my 8th yes eighth transaxle. I managed to blow up the Centerforce Dual Friction clutch I had in the car as well. I have a new Clutchnet clutch that is suppose to be able to handle 450lbs of torque. I am building a custom one off 4spd standard transaxle for the car, with much better gearing for the 4.9's torque. It has a 3.32 gearset with a .73 overdrive 4th.
I do still have a turbo sitting here for the 4.9 but am not sure if I am ever going to get around to installing "it". I still plan a Turbo at some point however the turbo I have is way too big for the motor. It was almost a gag joke that I got it. Its from a Kenworth Tractor. Yes as in long haul tractor. So it should be good for uhm 20-30psi on a 6L+ V8. The inlet is so big, it looks like it could swallow a wooden 2x4 and spit it out the other side.
As for the Turbo 4.9 Fiero. It was modified a fair bit, however for the most part, the engine and fuel system was stock. Custom ECM, and such. I know he had A LOT of passes on that motor and nothing ever failed, it was actually built for his wife and she ran the hell out of that car.
I belive it was a high 12 second car IIRC. I would have to double check the records to make sure. I think there car was in the 3000lb range.
Re: The "4.9 liter turbocharger, stage 1" thread.
Ok, so I'm bored and need to talk turbos on a cadillac...
What are you planning on doing for engine management? I ask because it would be real straigtforward and easy to install a MegaSquirt, especially since these cars are non-OBD-II which makes sensor feedback to the ECU a moot point. I wish I had my 1990 Eldo near me, it's 1000 miles away in storage as I'd set it up for all to see...
Easiest way to do it is a remote mount turbo, I'd use a Holset HY35 or HX35, 40, etc... series (on the HX you'd have to hog out the turbine split scroll header) for test purposes since they're cheap as dirt (good used one off a couple year old truck usually runs $250 range, only run oil as a lubricant/coolant (no bearings)), in line oil pump ($150), oil lines ($50) some exhaust piping ($100), weld on some hangars(or bolt on if welder not available). Return would be cheaper aluminized steel pipe ($50), for couplers use heater 'stick' hose ($50) for large diesel rigs instead of Silicone because it's much cheaper and much more durable, t-bolt clamps ($50), a cheap ($85) ebay intercooler up front, $300 to build your own Meqasquirt w/a 3-bar MAP sensor, stimulator kit (to bench test that it's working prior to vehicle install), and LC-1 Wideband O2 ($100). You'd also need an external wastegate if you only wanted to run ~5-7lbs of boost which will set you back another $100.
I'm surprised no one has bothered doing this yet, it's so easy it's comical, the turbo system would take a day at most to plumb up and install, the MS would take a couple hours each night x a week for a novice to build, prolly a few sessions like that to install, and then a few more sessions like that to get it idle and then tune. I can't begin to believe no one has considered this, it could be done for about $1300, definatley under $1500...
Re: The "4.9 liter turbocharger, stage 1" thread.
I have just been busy with so many other things that I simply haven't had time to do this yet.
Please stay tuned as this whole thing will be a pleasant surprise!
Re: The "4.9 liter turbocharger, stage 1" thread.
There have been many a tuner if you visit www.fiero.nl boards, there was a turbo 4.5L using stock ECU with auto trans that was chip tuned by a fella in Canada, there are many others. Also, on pre-OBD vehicles the proms could be burned with a few different prom burners and freeware software...
- 01-02-09 01:19 AM #225Cadillac Owners Member
- Automobile(s): 94 Fleetwood / 83 El Dog.
- Join Date
- Jan 2009
- Age
- 29
- Posts
- 21
Re: The "4.9 liter turbocharger, stage 1" thread.
Dont forget your A/F Meter.
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Any woman who has more than one child can tell you how different each child is from birth. You are born with your personality intact. The Color Code is based on your natural, innate personality type. Of course, people may change over time, but your Core Color will always remain the same.
Sometimes it is difficult to choose from the four options given, but there is usually one that fits better than the rest, or at least one that you could see yourself as more so than the others. If you're still unsure, try asking someone who knows you well, such as a parent or sibling. They can give clarity on areas of your personality that you may not notice.


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Species Description: The Gunnison's prairie dog (Cynomys gunnisoni) is a yellowish buff color mixed with black above; slightly paler below with a short, white-tipped tail. It is approximately 12-14 inches in length, between 12-15 inches tall, weighing about 23–42 ounces. The Gunnison's prairie dog is one of five species of prairie dog, all of which are native to North America. The Gunnison's prairie dog is a keystone species of the sagebrush ecosystem. They create habitat, provide food, and help keep the soil and plant communities healthy. For example, their abandoned burrows are used by burrowing owls, weasels, snakes, badgers, and even foxes. The prairie dog is an important food source for coyote, weasels, foxes, hawks, eagles, and the endangered black footed ferret. In addition, their burrowing helps to aerate the soil, add organic matter, and help to increase water penetration.
Location: The Gunnison's prairie dog occurs in the four corners area of Arizona, New Mexico, Colorado, and Utah.
Recent Actions: Today, November 14, 2013, the Service announced the completion of a 12-month status review in response to a petition to list the Gunnison's prairie dog as a threatened or endangered species. The review has determined that protecting the Gunnison's prairie dog under the Endangered Species Act is not warranted at this time.
The Service has determined that populations of the Gunnison's prairie dog located in central and south-central Colorado and north-central New Mexico are warranted for protection under the Endangered Species Act. However, listing these populations at this time is precluded by pending actions for other species with higher listing priorities. The Service also determined that Gunnison's prairie dog populations in Arizona, Utah, and elsewhere in Colorado and New Mexico are not warranted for listing.
Service's 12-Month Finding
Service's 90-Day Finding


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Galtonia viridiflora
= Full Sun
(PPAF) = Propagation of this plant prohibited without a license.
2017 Catalog
Order the 2017 Catalog printed on genuine paper for $2.
Digging Dog Nursery
a retail and mail order plant nursery specializing in unusual and hard to find perennials, ornamental grasses, shrubs, trees, and vines.
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"We ordered a half-dozen Bergenia 'Bressingham White'.... Not only did they arrive in tip-top shape, but they also are thriving this spring."
~Ian in Illinois
view Digging Dog's comments with Dave's Garden (The Garden Watchdog)


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Much nicer then the stock rotator clamps. Some times its the little details that you do to your bike that makes its stand out.
ASV Rotator Clamp - Clutch
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This clamp is very nice looking! But i tightned it all the way and i tried to move it but it didnt. But i loosened it then it worked. I just hope the bolts wont vibrate off. This is still a awesome rotator clamp though! idk if u can but you may be able too see it in the pic.
levers break and the less they do the better 4 you...they look clean and work pretty dorn good...but you can still break levers with them but for the lil money u spend on them you'll save more $ in the long run...its worth it 4 sure
I am sure these clamps have saved my controls numerous times. Also they make adjustment easy and look really nice for a long time.
this ASV clamp is very good looking, cheap and saves your lever asembly from breaking. I would recommend getting this clamp in red and putting it on black handle bars.
put this and the clutch clamp on my bike, completed my ano red accents here and there on my bike. looks great, saves money!!
This clamp saved me money in the long run. It saved me from having to buy new levers every time I crashed, and it looks good too. Also, I like how it allows me to adjust my clutch height without tools. It's a time saver!
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We love the style and size of the Samsung Q330 and think it's a great notebook for travellers. Its performance is good and it has a useful set of features, but it also has two graphics adapters that provide similar performance to each other. We'd prefer it if there was a bigger performance gap between the adapters (or for the notebook to only use Intel HD graphics).
Samsung's Q330-JS03AU is an attractive, sub-2kg 13.3in laptop that's slim, well-featured and competitively priced. It's the perfect size for users who want a notebook that's easy to carry around but has a roomy design. The configuration of the notebook is a little puzzling though: it ships with NVIDIA Optimus graphics that don't make much of a dent in the performance. We'd like to see this model offered strictly with integrated Intel graphics because the extra speed offered by the extra NVIDIA chip is not worth bothering about and omitting it would bring the price down.
NVIDIA's Optimus technology automatically switches between the integrated Intel HD graphics adapter and the dedicated NVIDIA GeForce GT310M; there is no physical switch. This means the NVIDIA card kicks in when you run a game, and the Intel card remains at the helm when you type up a document. There is scope for modifying which card your applications use (you use the NVIDIA driver for this), but this doesn't always work in an obvious way.
During our battery test, during which we turn off power-saving schemes, enable Wi-Fi and turn up screen brightness then loop a video, the notebook lasted 2hr 51min when we let Optimus select which graphics card to use. When we forced it to use the NVIDIA card the notebook returned an identical result, but when we forced it to use the integrated Intel graphics it only lasted 2hr 42min.
This is a topsy-turvy result: the NVIDIA card should have given us the lower time. The moral here is, don't mess with Optimus: let it select the graphics card on its own and you'll get optimal battery performance. This is unlike what we experienced when we tested the MSI FX600, where we had to select the graphics card manually in order to get the longest possible battery life.
Either way, the inclusion of two graphics cards isn't really justificed given the negligible difference in battery life. Furthermore, the difference in 3D performance between the two graphics adapters is not dramatic enough for an extra graphics adapter to be of any real usefulness. In 3DMark06, the Intel HD card recorded a score of 1729, while the NVIDIA card recorded a score of 3667. This is similar to what we saw from MSI's CX420, which is a hybrid notebook that uses ATI graphics. These results tell us that the Q330 is not a gaming machine by any stretch of the imagination and you shouldn't be roped into buying it by thinking you'll be able to play many games on it just because it has an NVIDIA graphics adapter.
However, if you want to buy this notebook because it looks good, has a relatively small size and a thin profile, has a built-in optical drive, is comfortable to type on and costs less than $1200, then go right ahead. You'll get good CPU performance too.
The laptop ships with an Intel Core i3-350M CPU that runs at 2.26GHz and it has Hyper-Threading. Along with 4GB of DDR3 SDRAM and a 640GB, 5400rpm hard drive, the notebook offers a nice all-round configuration for productivity applications and the storage of media files. In our Blender 3D test, it recorded a time of 1min 5sec and in our iTunes MP3 encoding test it recorded 1min 8sec. The Blender time is exactly what we expected from a laptop running the Core i3-350M CPU, while the iTunes time was a little quicker than expected. For example, the Medion Akoya E7214, which runs the same CPU, recorded a time of 1min 10sec in the iTunes test.
You can also use the Samsung Q330 for more processor-intensive pursuits such as video encoding. In our video encoding test, in which we use AutoGordianKnot to turn a DVD file into a 1.5GB Xvid file, the laptop took a respectable 1hr 14min. This is 18min faster than the Medion and actually very competitive with the Core i5-based Acer Aspire 5741, which also runs at 2.26GHz and took 1hr 15min in the same task.
The Q330 has a silver, brushed finish on its palm rest and a dark, glossy lid; it looks rather nice and many people told us so. Its keyboard has chiclet-style keys and is reasonably comfortable to type on. The location of the touchpad isn't centred under the spacebar though; it's slightly to the right of it. While you type, your right palm can accidentally move the cursor. We also don't like the location of the SD card reader at the front: you can't easily access this slot when you use the notebook on your lap. Along the sides you get a built-in DVD burner, Gigabit Ethernet, HDMI, microphone and headphone ports, and three USB 2.0 ports.
The USB 2.0 ports support Samsung's ChargeableUSB feature, which means you can charge devices like MP3 players and mobile phones that have a USB connection — even when the laptop is in sleep mode or completely switched off. It's very convenient when travelling as it means you don't have to take chargers for all of your devices; just make sure you pack the appropriate USB cables. However, it doesn't work with Apple devices, so you'll only be able to charge your iPhone or iPod when the notebook is up and running.
We're not fans of the way the Optimus graphics switching technology has been implemented in the Samsung Q330, but we still think this is a great notebook to consider. In particular, we love the fact that it's a 13.3in laptop rather than a 15.6in model; it makes it much easier to carry to and from work or the classroom. The notebook's performance, even though it uses a Core i3 instead of a Core i5 CPU, is good enough to run taxing tasks in addition to everyday office applications. The only thing it's not good for is serious gaming.
Samsung's environmental policies are detailed on its Web site.
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As a piece of individual brilliance and athleticism, there have probably been better All Black forward tries than that scored by Peter Jones five minutes into the second spell of the fourth test against the Springboks at Eden Park in 1956.
There was Ian Kirkpatrick's extraordinary burst from inside his own half to score against the Lions in the second test at Lancaster Park in 1971, as just one example.
But not even Kirkpatrick's try has etched itself into New Zealand rugby folklore as much as Jones's, which was the only All Blacks' try in the 11-5 win over the Springboks.
This was because of the circumstances of that South African tour, which aroused a national fervour that has never been equalled.
Until 1956 the All Blacks had never won a series against the Springboks, and in 1956 many New Zealanders were still seething over the defeats in 1937 and 1949.
Over the 4-0 whitewash suffered by Fred Allen's side in South Africa in 1949 there was particular resentment at what was seen as biased refereeing. So there was a spirit of revenge in the air as the fourth test loomed, with the All Blacks having taken an edge in the series by winning an exciting third test 17-10 at Lancaster Park.
That was the game in which Don Clarke, the Waikato kicking colossus, had been introduced at fullback, and Kevin Skinner and Peter Jones had been recalled to the pack.
So everything depended on the fourth test result, and it drew a crowd of 61,240, still a New Zealand test record.
The All Blacks held a shaky 3-0 halftime lead, after Clarke had landed the second of two long-range penalty goal attempts.
But five minutes into the second spell Jones's try secured the victory. From a lineout near the Springboks' 10m mark the ball was spilled by the Springbok halfback "Popeye" Strydom, All Black hooker Ron Hemi toed it ahead for the fast following Jones to receive a favourable bounce.
He grasped the ball ahead of Springbok captain Basie Viviers and, with startling pace for a big man, raced into the clear, beating a would-be covering tackler to score near the posts. Clarke's conversion made it 8-0, and the way rugby was played then that lead was virtually unassailable.
Another Clarke penalty made it even safer at 11-0, with the Springboks' converted try coming too late to affect the result.
Seldom has an All Black win created so much jubilation and in the aftermath Jones became even more of a national icon. Unaware he was talking on national radio, Jones announced he was "absolutely buggered".
In those years saying "bugger," in polite company, was taboo. But even in those straitlaced times few New Zealanders took offence, such was the affection for Jones. The civil servants then running national radio were the only exceptions. For many years the Jones' tape was locked away with strict instructions it was never to be aired again.
Concession from Doc Craven
"We lie prostrate at your feet," South Africa's manager Danie Craven said at the post-match dinner.
"We have taken the count without a shadow of a doubt," said Craven, a thorn in the side of the All Blacks as a player almost 20 years earlier.
Analysing the tour he said his side made too many mistakes, the All Blacks played a ruthless tight brand of rugby far different to that in 1937.
"We have paid more for mistakes in this series than for years in the history of South African rugby.
'Your desire to beat us was more than just desire. That was evident from the preparations you made. The result was that this New Zealand team was much harder to beat," he said.
Great tries:
1987: John Kirwan vs France
1995: John Lomu vs England
1997: Christian Cullen v Australia
2000: Jonah Lomu v Australia
Tries against the All Blacks