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SANTA CRUZ -- Sol Katzman and Stew Perlman are spending a sunny Saturday morning on Scott Creek Beach leaning over a rotting sea lion carcass.
The body has lost its moisture and begun to flatten into the sand.
The two men manage not to grimace as they measure the pungent heap from nose to tail and tie green twine around the rear flipper to show it's been counted.
Katzman, 60, and Perlman, 64, are "citizen scientists," part of a volunteer project that collects information about beach-cast marine mammals, birds and turtles along 40 miles of Monterey Bay coastline, from Davenport to Carmel.
The BeachCOMBERS project, which turned 15 this year, has explained mysterious die-offs, exposed harmful fishing practices and traced oil spills back to surprising culprits.
The project's goal is to determine how much animal mortality is normal on various beaches, enabling year-to-year comparisons. Project Manager Hannah Nevins, a seabird biologist with Moss Landing Marine Laboratories, said marine mammals and birds reflect the health of the whole environment they live in.
Their population numbers mirror those of the species they eat, including forage fish such as anchovies and sardines, which are hard to count or monitor directly.
Scott Benson, now a marine ecologist with the National Marine Fisheries Service, co-founded the program and managed it from 1997 to 2001. He said his goal was to get hard numbers and consistent data, which he thought were lacking in other volunteer survey programs.
Katzman works in bioinformatics and has no formal education in marine biology. But like all 73 of his fellow volunteers, he has gone through 20 hours of training to identify and document what washes ashore. He and Perlman, a high school English teacher before his retirement, walk the same stretch of beach the first week of each month.
November's survey of Davenport and Scott Creek beaches turned up only the sea lion and two seabirds. "If we come out here someday and there's a lot of stuff, we'll know something happened," Katzman said.
BeachCOMBERS, the latter part of the title which stands for Coastal Ocean Mammal and Bird Education and Research Surveys, has documented many of these "somethings."
In August 1997, volunteers arrived at Marina State Beach to discover 400 dead common murres -- penguin-like diving birds found all along the Pacific coast. Karin Forney of Moss Landing was among the volunteers who documented the event. "There were stretches of the beach where I wasn't even standing up," she said. "I was just crawling from one carcass to the next."
Birds APPEARed healthy
Forney, now a research biologist with the National Oceanic and Atmospheric Administration, found it especially troubling that the murres didn't show obvious signs of illness. "These were plump, otherwise healthy looking birds," she said, "aside from the fact that they were dead."
Scientists suspected the cause was a fishing operation that had recently been established just offshore. The fisheries were using gillnetting, which hangs like a curtain down to the sea floor. Nevins said this method is especially dangerous because the nets are invisible to birds and mammals, which swim into them and become entangled.
The fisheries were legal. The nets were placed deeper than 30 fathoms (180 feet), as the law required. But BeachCOMBERS' grim discovery prompted the National Marine Fisheries Service to investigate. It found that 5,000 murres and more than 100 porpoises were being killed in the nets each year. Volunteers "raised the red flag," Forney said, documenting a local event that would have gone unnoticed. The minimum depth for California's gillnet fisheries was ultimately changed to 60 fathoms or 360 feet, effectively eliminating them from the bay.
The citizen scientists also record and collect samples of tar balls -- goops of petroleum that wash ashore from sea floor seepage, runoff from pollutants on land, or a spill from a boat or ship. Knowing what levels are normal helps scientists assess the damage in the event of a major spill.
In 2002, some of these oil samples became clues in a long-standing marine mystery. The 1980s and '90s saw occasional spikes in the number of oiled birds and mammals washed ashore, but researchers didn't know the source of the oil.
Tracing the oil
Scientists at Moss Landing Marine Laboratories "fingerprinted" BeachCOMBERS oil samples, comparing their chemistry to samples they had collected over the decades. The culprit behind the oil spikes turned out to be the S.S. Luckenbach. The cargo ship sank off San Francisco Bay in 1953 and has been sitting on the ocean floor with a belly full of oil ever since. When large enough waves rocked the hull, the old ship would release oil to the surface.
The findings prompted a $22.7 million cleanup effort that has removed most of the oil. Occasionally, though, the ghost of Luckenbach still rises and sends ashore oily seabirds.
BeachCOMBERS volunteers have documented everything from a murre baby boom to a spike in stillborn sea lion pups. They linked an influx of frostbitten pelicans to a northward expansion of the species' range -- good news for the once-endangered pelicans, despite the ghastly carcasses on the shore.
They traced mysterious foam in seabird feathers to a bloom of algae and shared their data with other researchers when the substance reappeared off the coast of Washington and Oregon.
Widening the database
The BeachCOMBERS forensic database is ever expanding, but those involved in the project believe it has an important role outside of the hard science. Volunteers become stewards of their assigned beaches, Nevins said, and they often explain their work to passersby. "The public definitely observes us, and they want to know what we're doing," said Sharon McGuire, 62, an Aptos resident and volunteer since 2003.
While the volunteers are as enthusiastic as ever, money is getting is growing tighter. The project needs funding for equipment, data entry, volunteer training and insurance. Nevins said federal budget cuts have forced the Monterey Bay National Marine Sanctuary to scale back its contributions, and she's struggling to find support.
A year of walks
The project's value isn't lost on the volunteers, who must commit to at least a year of monthly walks -- rain or shine -- to help build up the database. "This isn't just some feel good little project," said former manager Benson, who continues to volunteer on beach walks.
After finishing their recent Saturday survey, Katzman and Perlman stood watching the surf for an extra half hour, grateful for an unseasonably warm day and an excuse to be near the water.
"It's just something I enjoy doing," Katzman said, "and hopefully the data will mean something."


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Tired of Looking Tired? How to Handle Puffy Eyes
Natasha Turner, ND | Posted 01.08.2013 | Canada Living
Read More: Skin Health, Vitamin B12, Iron, Vitamin K, Sleep, Dark Circles, Puffy Eyes, Puffy Undereyes, Undereye Concealer, Morning Eyes, Why Do I Get Puffy Eyes, Dark Undereye Cure, Dark Undereye Circles, Undereye Circles, How to Fix Dark Undereyes, Video, Canada Living News
If you find that you are spending more and more money for the perfect under-eye concealer, or treatments to combat puffiness in your face, you should look at the root causes. In my practice I have found that the culprit behind those dark circles and puffy eyes can range from thyroid problems to food allergies. Here are some solutions to the five most common causes.

subset: commoncrawl


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Reading United win, advance to second round of U.S. Open Cup
Reading United win, advance to second round of U.S. Open Cup
Two early second half goals lift United over FC Lehigh Valley United Sonic
In a showdown between Pennsylvania's two elite amateur soccer teams, Reading United A.C. defeated the 2012 NPSL Champions FC Lehigh Valley United Sonic by a 2-0 score line to advance to the second round of the 100th Lamar Hunt U.S. Open Cup. In a tight match between two evenly matched sides, Reading used a two-goal outburst shortly after halftime to secure the club's second win in U.S. Open Cup history. With the win, Reading will face fellow Philadelphia Union affiliate the Harrisburg City Islanders next Tuesday.
The first half of the match saw Reading hold a decided advantage in the possession. Much like Saturday's 8-0 demolition of the Westchester Flames, United came out aggressively, playing large portions of the match in FC Lehigh Valley United's half of the field. Sonic countered by staying well organized, thwarting wave after wave of pressure.
Reading's first real opportunity of the match came in the 19th minute when midfielder Manolo Sanchez struck a ball from the right wing that hammered off the crossbar and was eventually cleared by the NPSL Champions.
Whether it was the excitement of a cup tie or excellent marking, several Reading players saw there shots sail hopelessly over the goal. United outshot their opponents seven to three in the first half, but only forced Sonic keeper Charlie Sales to make one save.
FC Lehigh Valley United had a golden opportunity to catch Reading on a counter in the 37th minute.
Following a Reading corner kick, Sonic cleared and launched a counterattack that saw them have a three on one advantage. Great hustle by United defender Jimmy Ockford and midfielder Keegan Rosenberry broke up the play and ended Sonic's opportunity.
With the half winding down, Larry Ndjock fired a shot that rattled the post. In the ensuing scramble to clear the ball, the Reading bench shouted for handball, but referee Eric Weisbrod allowed the final seconds of play to tick off before whistling for halftime.
The second half began with United again exerting pressure in Sonic's half. The aggressive tactics worked and in the 50th minute when Reading United found the breakthrough goal.
Ndjock began a run down the right side of the field, with Philadelphia Union academy graduate Darius
Madison tracking the run in the center channel. Njdock beat his mark and found Madison alone in the Sonic penalty area. With the keeper at his mercy, Madison coolly stroked the ball into the back of the net to hand United a well-deserved 1-0 lead.
With the advantage, Reading continued to press forward. Right back Wes Charpie earned a throw in following an aggressive run down the right flank. Charpie picked out captain Steve Neumann on the throw in, who took the ball down the end line as he drove toward goal. From a nearly impossible angle, Neumann looked up and saw the keeper off his line and fired a shot that nestled just inside the side netting to double United's advantage. "I just saw the goalie off a little bit, the guys were asking me if it was a shot or a cross," said Neumann. "I'll take it to my grave that it was a shot," the Georgetown midfielder said with a smile.
With the insurance goal, United went looking for a third goal to kill off the match. Creating more opportunities to score, Reading forced Sales into several acrobatic saves to keep the match at 2-0.
As the scoreboard clock showed ten minutes remaining, Sonic desperately went searching for a goal. It was end-to-end stuff in the closing moments as each team attacked and then counterattacked. United keeper John McCarthy did well to save a stinging long-range effort from Sonic forward Joe Sales.
The late surge by FC Lehigh Valley United came up empty as McCarthy, who made four saves on the evening, and his defense earned their second consecutive clean sheet to start the 2013 season.
After the match, Head Coach Brendan Burke reflected on the hard fought win. "Couldn't be more pleased with the way the players listened and how they responded," Burke shared. "I'm going to enjoy coaching this team this summer," the head coach said with a grin from ear to ear.
With the 2-0 victory, Reading will host fellow Union affiliate and USL-Pro side Harrisburg City Islanders in the Second Round of the 100th U.S. Open Cup next Tuesday at Exeter's Don Thomas Stadium. This will mark the second time the clubs have met in the Cup, with Harrisburg scoring twice in the final five minutes to come from behind and beat Reading 2-1 in 2011.
Reading United return to Premier Development League action this Sunday when they host the New Jersey LUSO Rangers at Don Thomas Stadium. Kickoff for that match is scheduled for 6:00pm. Tickets are available at
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Were more interested in what kind of football player he is than anything else, said Reese, who drafted a character risk in corner Jayron Hosley a year ago. Well investigate it and well see how it goes.
If Te'o I still available by the time they get to pick 19 I think he'll be a Giant and I don't disagree because we need a linebackers badly!!


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Latest update: Aberdeen prepares itself for Simplot exit
ABERDEEN, Idaho - It's similar to that love story, where you see the impending break-up looking not-so-pretty, but this time it's the story of one company and a city who needs it most. Spoiler: economic development experts are saying this ending isn't looking as devastating as most suspected.
On Friday the Caldwell plant laid-off 262 employees to make way for the building of the new facility which will be located in the same town.
However, fear of the small town of Aberdeen turning into a ghost town that swept throughout the city when the company announced it would be closing the Aberdeen plant's doors by this Spring, might not be as prevalent of an issue as once believed to be.
Aberdeen Mayor Morgan Anderson is concerned about the 111 workers and 25 families this would impact, causing many, if not all of them to skip town in order to find employment elsewhere.
That's when Anderson called upon regional economic development specialists to help salvage the city, with its mere population of just under 2,000 people.
Anderson has been working with Kristen Jensen from the Great Rift Business Development Organization, Roger Chase from the Bingham Economic Development Corporation, and the Simplot company, among others.
Jensen said, in actuality, we probably will not see the mass exodus everyone has been fearing since the closure announcement nearly two years ago.
In fact, she feels positive about the outcome of this situation since Simplot is indicating it's doing its part to help out.
"I know they're not going to leave us behind," Jensen said. "I know they are going to be there to help us move forward into the future."
But, there's just one problem: Anderson and Jensen said the company is not allowing them to seek out prospective companies to move into the building until it officially closes its doors sometime between February first and the last week of April. Anderson suspects this is because Simplot wants to make sure the new Caldwell plant is up and running before it decides to nix the old Aberdeen plant for good.
Smart business move, yes. However, this is concerning to economic development specialists trying to prevent more than 100 employees from finding themselves without a job.
Anderson noted Simplot has never sold a single plant. They have either remained in business or have been demolished.
Jensen said Simplot has offered to pay for its employees' tuition if they decide to go back to school to gain training and expertise in another trade. The hope here, is to make sure these employees will be skilled in areas that could land them a job locally so they won't have to move out of Aberdeen.
"When the plant closes, they'll have other opportunities for employment and thus they can stay in the city of Aberdeen and that's our hope. We want to keep the employees in their homes, in their neighborhoods," Jensen said.
She also mentioned Simplot was only required to give its employees a 90-day notice before laying-off workers. However, this two year advanced notice allowed many of them to search for jobs in the meantime.
Some Simplot employees at the Pocatello plant mentioned many of the Aberdeen workers are seeking employment at the Don Plant in Pocatello, which is not being impacted by the closure.
In March, Idaho Rural Partnership will be sending between 15 and 20 economic development experts from across the state into Aberdeen to hold a community review session. This is where they will assess the city to determine how they can bring in certain businesses under its current circumstances, that can thrive within the community.
"We are hoping to get a lot of good insight from that and then we can go out and try to locate some of these types of businesses and hopefully attract them and bring them in," Jensen stated.
She also said she has been working with one unnamed company who is looking to locate itself between American Falls and Aberdeen.
Nevertheless, both Jensen and Anderson said too many manufacturing companies as well as consumers across the state (and even the nation) rely too heavily on produce grown in towns south of the Snake River such as Aberdeen and American Falls. Meaning, the cities aren't facing the threat of becoming a ghost town since there will always be potatoes flowing out into the rest of the state, onto the plates of many.
Even Simplot does not plan on ceasing its acquisition of produce local Aberdeen farmers supply them with, since the product is too good and they don't want to completely leave the city high and dry.
But at the end of the day, that key word there is still 'completely.'
Follow Kaitlin on Twitter: @KaitlinLoukides
See other articles on the left-hand side of this page under "related content" to gather more information on how Aberdeen has been facing the Simplot closure we have been covering.


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I see a few threads talking about books that we've read. Is it against the TOS to talk about books we've written?
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I see a few threads talking about books that we've read. Is it against the TOS to talk about books we've written?
--Depends what you have to say. Advertising is prohibited, but if you wanted to share some of the ideas in it I, for one, would be very interested. Welcome to BBF. Its a pleasure to have such a distinguished vistor.
A couple of weeks back your book was brought up this was my quick book review:
I finished The Book the other day and overall it was good. Nothing revolutionary but then again I wouldn't expect it to be. Basically what the book is is a in depth look at baseballs most commonly held strategic decisions and cliches. Things such as bunting, platooning, reliever usage, and so forth. Lots of charts and explanations of how they do things so one never really has to guess at how they came to their conclusions but at the same time one can easily skim a section if the material is too laborious for ones interest and not lose track of what they are saying.
One of the things I liked about the book is they mention game theory and go over it a little and how it relates to baseball. They do it in a way that I don't think most people do, and thats including stat-bashers and statheads. They don't just look at it in terms of success and failure but how it forces other teams to play you. For instance in terms of bunting if you never bunt in sac bunt situations then your opposing teams can alter their defense in a way that gives them an advantage. The corner infielders don't have to protect against the bunt, middle infielders can play deeper and play against a hit and so forth. So by not forcing the opposing team to respect the bunt you make it harder to get a hit in those situations. So there are times when one has to bite the bullet and sac bunt just to show people you will.
Now for what it isn't. This isn't an exciting book, it isn't a bill james book. Theres no stories no history no essay type sabremetric book like a Barra or Neyer book. This is more like a report prepared for a baseball manager then a fun summer read. This book isn't a book that ranks players, you won't be seeing people using quotes and passages from this book in these forums like they do with Bill James. This is simply a book that tries to explain what happens in a game when certain events occur and I believe that they do this very well.
Might I suggest you get ahold of Sean, the webmaster and owner of this site. (member webmaster.) On the Almanac part of the site, there is a book page, including a listing on one written by a Fever member.
Personally, I'd consider letting us know about your book a favor to the site and its members.
Thanks leece. I guess I'll just tackle whatever issues are brought forth.
Ub, that was a fair and honest review.
Nose, good idea.
From discussions about this sort of thing I believe it was decided that one is allowed to post a link and a short blurb to their site in their signature.
Anyway to kick off some talk about the book I'll throw you some questions.
In another thread a discussion came up about pitchers pitching to the score, with some believing this is a real effect. I tried to explain your books view, but personally I think I did a horrible job doing that, so if you could perhaps you could explain your books view here. What kind of effects you saw, were pitch counts different, pitch situations different, so on and so on.
Second question:
What kind of impact does a baserunner have in the game? Again on this site we have had debates in which some believe that good baserunning is not measurable. That the impact of basestealer is not captured in the stats, the pressure they put on the defense and so forth. Is it measurable and if so whats the impact? Was someone like Lou Brock "better" then his stats because the pressure he applied wasn't measured or was there anything to measure? What has PbP data shown you guys when players steal bases, when great basestealers are on and when they try to steal?
Hopefully that will get the ball rolling for you.
I'll second the second question. I'm particularly curious to what extent a player's ability to "take the extra base" has a significant impact on the outcome of the game.
To which I'll add a question about the relative value of a strong/accurate throwing arm. What "percentage" of an outfielder's defensive value does his throwing arm account for? Intuitively, one would think it's of less value than his range. Is this something discussed in your book?
Re: baserunning
Everything is measurable. It's a question of finding that sensitive needle. Basestealers not only put pressure on the defense... they put pressure on the offense. The effect is rather powerful, especially for those runners who don't like to sit and wait. They also open up the hole between 1b and 2b, and so a LH or an opposite-field hitting RH would be able to leverage that situation.
The overall value of taking the extra base is certainly real. A quick way to think about it is this way: the fast runner will advance about 0.20 bases more than an average runner, when a single or double is hit, and when he is on 1b or 2b. Each base is worth about 0.25 runs. The average runner will find himself on 1b or 2b about 40% of the time (including "duplicates"). A single or double is hit about 20% of the time. So, .20 x .25 x .40 x .20 = .004 runs per PA, or almost 3 runs for a full season. Add a bit more for GB movements, and we are talking about 5 runs. That's the overall extent. However, in any single PA, the effect can be enormous or non-existent.
For the throwing arm, you have a similar process, and you'll end up with roughly similar numbers. Of course if an OF is unduly tested, and he makes the most of it with his kills, he'll get more value than if the runners simply stayed put. (We don't talk about this in the book.)
Re: playing to the score, that was Andy's research, so I'd rather not comment on it without having the book by my side, so as to no misrepresent him.
First, congratulations on your book, it represents a tremendous amount of work and discusses for the first time some very interesting topics. It is by far the best book to come out this year including "Baseball Between the Numbers", "The Fielding Bible", and the THT and Baseball Prospectus Annuals.
But I do think that Gary Huckabay's article in the 2006 Baseball Prospectus in which he discusses statistical analysis with an unnamed GM to be the single most interesting read.
Even though I think that the discussions in your book are very informative and innovative I have trouble with the conclusions being based on the Run expectancy tables. I still feel that even though Run Expectancy Tables are useful for many things, they are not appropriate for evaluating strategic decisions. The strategies that you discuss in the book are always decided on very specific variables for each situation, a specific batter facing a specific batter at a specific point in a game with a specific score. Run expectancy tables are based on average values, an average batter facing an average pitcher in an average inning with an average score. Even though mention or try to control for some of the variables in most of the analysis in your book, the situations are too complex for you to be able to control all of the relavant variables. It would seem that a proper analysis would require a much more sophisticated game simulation program than you have at your disposal.
A specific question about intentional walks. Your analysis identifies the 1 out men on 2nd and 3d situation as one which is a good possibility for using the intentional walk. I am using a different data set than you, 2003-2005 PBP data instead of 2000-2004, but in those three years intentionally walking the batter in that situation cost teams 125 runs, by far the biggest run losing occurence of any Base Out situation. The next biggest loser was walking the batter with 2 outs and a man on 2nd which lost 23 runs. The use of the intentional walk in all other Base Out situations were either plusses for the defensive team or only insignificant losses. Is this just a data quirk or are managers overusing the intentional walk in the 2 situations that it would seem most likely to help them?
Thank you very much for the kind words!
I should correct your claim on the RE tables. We in fact insist that Win Expectancy (WE) tables, and not RE tables, should be the driving force (a message that is noted especially in the sac bunt chapter). It's also noted very specifically in my basestealing chapter, where the breakeven points change drastically based on the inning and score. The RE tables are valuable as a starting point, but by no means are they the ending point (so I agree with you there). And certainly, the batters on deck, the relief pitchers, etc, all play a part in this. Mick, Andy, and I each have our own "sophisticated" game program, but we only used it in the book where it would add to the content.
Andy wrote the IBB chapter, so, again, I'll have to have the book next to me. I'll reply to these questions tonight or tomorrow, and ask Andy to chip in his two cents.
I know that you use win expectancy tables and even though they are an improvement on run expectancy tables they are also based on average teams and therefore are not very helpful in evaluating strategy. For example, win expectancy tables start with the assumption that two teams have an almost equal chance of winning a game (slightly better than 50% if you are the home team and slightly worse if you are away). But that it almost never the case. For the 16 games that Pittsburgh played against SL last year the actual average chance that Pittsburgh had of winning each game was probably between .250 (the actual percentage they won against SL) and .355 (their chance of winning based on their overall league WP and SL's league winning percentage). Pittsburgh should use very different strategies to try and win games against SL than SL should use against Pittsburgh, but win expectancy tables would evaluate the strategies of each team in the same way if the game situations of score, out, inning, and men on base were the same. This type of analysis would lead to wrong conclusions.
You are right about that. A game starting with Pedro, RJ, Clemens would have a 70% chance of winning, so the strategies against them would be different than with a triple-A pitcher.
I don't think we did a good job of explaining that. I'll have to reread the portions where that would apply, and see how well we addressed it.
First off, I should correct you on the chance of Pittburgh beating St Louis. It has nothign to do with how they actually performed against each other. It's a small sample size. A .600 team facing a .400 team will win 70% of the time.
On to the larger issue: when we did our analysis, I think we made a decent effort of explaining the "average" issue. The intro to the 9 pages of WE tables discussed that you certainly need to go beyond average.
The IBB analysis assumed average for everything, except the batters on deck. You could come up with a larger matrix, that also included the quality of pitcher on the mound, and the pitcher you have at your disposal. In the SB chapter, I think I said that teams should run more often with a great pitcher on the mound, but I'm not sure. I've said it in other places for sure (not necessarily the book).
All this to say that there are tons of variables to consider, and the book gives you the path to do that. It's a huge step up from the current analysis being done, and we still need to do the next huge step to consider the park, the opponent, your teammates, the count, and inning, score, base, out. I don't think we left anyone with the impression that you should only consider the variables we did.
First off, I should correct you on the chance of Pittburgh beating St Louis. It has nothign to do with how they actually performed against each other. It's a small sample size. A .600 team facing a .400 team will win 70% of the time.
Pittsburgh played as a .440 team last year adjusted for their division and to a .500 opponent. St.Louis as a .586 team. A .440 team playing a .586 team has a .355 chance of winning. I would trust that number as an average but they did only win a quarter of their games against St. Louis so even though it is a relatively meaningless small sample I thought that it should be mentioned as a lower bound to the range.
Your .355 figure is pretty much what I get using the Odds Ratio method, if they were truly .440 and .586 teams. (They probably weren't.)
You are correct in mentioning the other number, and their true chances of winning was between .250 and .355, though much closer to .355.
Your .355 figure is pretty much what I get using the Odds Ratio method, if they were truly .440 and .586 teams. (They probably weren't.)
OOPS! I read the wrong column in my spreadsheet. How does .427 for Pittsburgh and .601 for SL sound to you? That would give Pittsburgh an average .326 chance of beating SL in the games last year.
For those interested, we have another excerpt of the book here:
Most likely the very last excerpt:
I just got my copy of THE BOOK...I'm specifically interested in custom and league linear weights based on the markov chain concept...hopefully there's enough information on how all of that is done that I can start to make some inferences into how to adapt the theory to the pre-PBP era.
I don't believe that information is in that book. You're probably better off looking at Tangotiger's site for that. I'm thinking his essay's on baseruns will probably show you how to do what tango is doing better then the book. AS for Markov chains, googling it is probably your best bet.
No...I already have a link on how markov chains work...that's not the problem. The problem is figuring out EXACTLY what input data I need to do specific things and then determining how to estimate state-to-state transition frequencies based on the frequency of annual statistics so that I can calculate BaseRuns for eras prior to 1957. I've read some of his writing on baseRuns already, but I don't believe he ever told us SPECIFICALLY how that can be done...if he has...I'll be happy to stand corrected (and informed. :) )
I'm away from my resources but I think (though I am not sure) that a book called curve ball (I think) might explain some of what needs to be inputted but again I'm not sure. I'm seem to recall coming across some info on how to do a markov chain for baseball but I can't seem to recall where. Best bet would be a series of e-mails with some of the professors who now and then get published for doing it, or of course with Tango.
All you would need are the state-to-state transition matrix. I will probably post those on our site to the benefit of whoever bought the book.
As well, you could figure them out youself. It's not that hard. For example, the state-to-state for the HR is a snap. Also fairly easy for triples and walks. Singles and doubles are a little harder, but I do have this on my site to help you out:
Strikeouts are straightforward. The outs are the hardest ones probably.
OK...so in order to do this kind of thing...you need to know:
How frequently (on average) each offensive event occurs in each base/out state. IOW, how often is a single hit with a runner at second and two outs...how often is a walk taken with the bases loaded and none out...how often does a batter K with a runner at third and one out? Etc for all base/out states.
How frequently does each event result in each specific state-to-state change (how often does a single...occuring with a man on first...result on that runner being on third and the batter advancing to second on the throw to third? Etc.
How frequently do runners score from each base given the out state.
I fail to see how it is possible to generate such things for years prior to PBP.
You need the first two. The third is implied by the second.
As for past years: the first one is fairly stable. If let's say 10% of PA are walks, but that from the PBP years, the walk happens in 8% of PA with a man on 1B, and 12% of PA with 1B open, and then you go to some older year where 8% of PA are walks.... well, you could make these numbers 6.4% and 9.6%. This would be a fair estimate.
As for the second one, again, you can keep the same state/transition rates. After you apply these rates, you will end up with a final runs per inning. If this figure is less than reality, then you can assume that your second matrix was too conservative, and therefore, you bump up the rates a bit, until you get the number to match to reality. It's really just a matter of tweaking a bit.
Got it?


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SANTA CRUZ -- Prosecutors portrayed a Felton man charged with murdering his girlfriend as remorseless and callous as they presented their closing arguments in his trial Thursday.
Prosecutor Jeff Rosell described Richard Chavez, 43, as an alcoholic with a violent temper and a history of domestic abuse.
"The most important thing we have learned about Mr. Chavez is that when he feels slighted, he's going to responded with disproportionate violence," Rosell told jurors. "He's going to punish the person and get them back."
That mentality fueled Chavez's behavior the night of Feb. 28, 2010, Rosell said.
"And he punished Deanna Dudley, and he got her back with a 2½-pound Maglite flashlight," he said.
Dudley, 37, died of head trauma after being struck in the head at the Rose Acres Lane home she and Chavez had recently moved to.
He hit her with the flashlight "not one, not two, not three but at least five times," Rosell said, his voice rising and his tone incredulous.
The blows split Dudley's skin down to the bone, cracked her skull and sent blood spraying across the walls of the closet emergency responders found her in, he told jurors.
Dudley wasn't perfect, Rosell said. She made lots of mistakes, but she tried, he said, referencing the testimony of her son, Stewart Newell, who emphasized how much his mother tried and that she cared about him and his sister.
Newell testified last week that his mother got into a number of fights with his sister, but maintained that his sister was the instigator and that his mother only hit back when she had to.
"It doesn't matter what they say about Deanna Dudley," Rosell said. "Stewart's mother didn't deserve to die like that. No one deserves to die like that."
Defense attorneys Mark Briscoe and Anthony Robinson, who will deliver their closing remarks Friday, don't dispute Chavez killed Dudley. They do, however, contest that her death constitutes first-degree murder. They say Dudley had a drinking problem and a violent streak, and that she came at Chavez with the flashlight first.
Jurors will be allowed to consider second-degree murder and manslaughter charges as well as first-degree murder when they deliberate. Under state law, first-degree murder is characterized as an unlawful killing with malice and premeditation.
Follow Sentinel reporter Jessica M. Pasko on Twitter at Twitter.com/jmpasko96


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On this episode of The Young and the Restless, Chloe deals with the news that Billy has married Victoria. She is wearing a cute blue sheer layered tank, looking comfortable yet stylish for the summer.
Chloe's top is similar to the Pins and Needles Dot Mesh Double Layer Tank available at Urban Outfitters for $38.00


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When the word "pancake" is in the name of your restaurant, people might jump to the conclusions that A.) you only serve breakfast, and B.) you only serve high-calorie offerings. In the case of Maxfield's Pancake House, neither is true.
Located in the One Mayfair Place strip mall at the corner of Mayfair Road and Center Street, Maxfield's is the second location for this casual breakfast and lunch eatery owned by Gus Zarmakoupis. (The other Maxfield's is in Fox Point.)
Manager Alisha Baackes said Maxfield's caters to the food lover in all of us: "We offer a comfortable, welcoming and happy atmosphere, and everything is made fresh. Any breakfast item or sandwich you can think of, we can customize it for you. We are really flexible and our food is priced very fair."
And if variety is the spice of your life, Maxfield's is the spot for you. Breakfast is served all day, and you'll find virtually any favorite breakfast item you can think of, including a huge selection of pancakes, French toast, crepes, waffles, omelets or traditional egg dishes. The corned beef hash ($7.49) is a crowd favorite that is made from scratch.
After 11 a.m, you'll find lunch options from salads and light sandwiches to some of the more popular items such as the gyro sandwich ($8.29) or the hamburger (half-pound $6.99 or 1/3-pound $6.49). The soups are made fresh daily and the variety of sandwiches is sure to please anyone.
For those worried about their waistline, you can find diet-friendly choices for breakfast or lunch, including fresh fruit, fresh vegetables and other lower-calorie items.
"If you haven't visited Maxfield's, I think you'll be impressed by the freshness of the food, Baackes said. "Everything is cooked from scratch and fresh ingredients are delivered daily. Plus, we are literally open 365 days a year. Most restaurants can't say that!"
The Basics
NAME: Maxfield's Pancake House
ADDRESS:2727 North Mayfair Road, Wauwatosa
FARE: breakfast and lunch food - American
HOURS: 6 a.m. to 4 p.m. daily
PRICE RANGE: $3.49 to $12.99 (approximate)
RESERVATIONS:yes, for six or more
HANDICAP ACCESS: yes
GLUTEN-FREE OPTIONS: in development
"Grab a Bite" is an informal look at the food scene in the Wauwatosa, Brookfield and Elm Grove area by freelance writer Karen Waldkirch. Whether you're looking for a place for a date night or a casual spot for lunch, Waldkirch will be out and about scouting eateries for you. If you have a suggestion for a column, e-mail her at firstname.lastname@example.com.
- Red Dot aims to duplicate East Side success in Wauwatosa
- There's No Place Like Hom Woodfired Grill
- Mo's Irish Pub: A lively Irish American neighborhood eatery
- Sluggo's Sports Pub & Grill: Back in business on Burleigh
- Tall Guy and a Grill: Taking backyard BBQ to new heights
- Cocina DeLeon: Old-world gourmet Mexican you make at home
- Burke's Irish Castle carries on a local legacy
- Albanese's Roadhouse serves up generations of Italian blessings
- BelAir Cantina: A breezy, Cali-Mex casual eatery
- Sherbrooke offers a bit of Canada in Tosa, eh
- Colonel Hart's: A true neighborhood hangout
- Ted's: It's Cheers without the beers
- Penelope's: A labor of love in heart of Elm Grove
- Drink in a bit of island life at Jimmy's Island Grill
- North Avenue Grill Same name, new owner
- Highlands Café: Tosa natives expand restaurant
- Café Hollander: Upscale and Belgian-themed
- Jose's Blue Sombrero: Tableside fun with a Mexican flair
- Balistreri's secret is in the staff and the recipes
- Slim McGinn's West a touch of Irish hospitality in Brookfield


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Stands for. The Whole Entire World Is F**ked. Used in any moments of extreme frustration. Esp. but not always with regards things that aren't working like broken down machines or programs.
I have been trying to fix this bug for 12 hours now and there just is no damn solution at all I'm pulling my hair out!!Arrgh TWEWIF!!!!
by Pffff April 19, 2010


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It is time to breathe. Yes. It's December. Let's let that sink in for a minute. Holiday shopping is completely stressful with families trying to out-purchase each other, and hit the Black Friday deals and Cyber Monday deals and the continued deals throughout the month. When my oldest daughter was born almost seven years ago, my husband and I decided that we were going to start making gifts at Christmas. Now that both our kids are older (three and seven) they both get to make gifts as well. Last year I shared what the handmade gifts my family has made in previously, so now I am going to share what we made this year if you are still looking for inspiration. Continue Reading "Handmade Gift Ideas From the Post Family" »
All posts tagged 'Guinness'
Handmade Gift Ideas From the Post Family
- 12.12.12


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Cut another Margus Hunt video last night very impressive I need to find more games of him
The other guys i really don't know much about outside of Geathers, who i think could've turned himself into a 1st rd player with a big yr next season.. Graduated or not, there basically interning for one more yr, trying to earn big bucks.. At least some of em..
Mike Davis WR Texas just declared today as well.. Draft board told em 3rd rd.. At least he came out and flat out said, he declared because of finances... I like when there honest..
Everyone knows how high i am on MLB's Ogletree and Minter, and i all ready posted this fantastic Article on Minter in the "KEVIN MINTER" thread, but felt it needed to be shared on the draft thread as well.. THis guys the real deal! The respect he gets from his teammates, almost all early rd picks, is amazing! Also, he was voted TEAM MVP by his teammates, and not for defense, but entire team! THis guys no freaking joke! I love how ERIC REID realized during the FLA game that MINTER was "In a zone!" and brought it up in the huddle..lol Minter is also a fantastic individual off the field and u have not to worry about him getting into trouble.. I love this guy as a prospect!
softly, LSU's Kevin Minter has made his presence felt in a big way
LSU middle linebacker Kevin Minter has been a quiet but dominant presence in the middle of the Tigers' defense this season with 111 tackles and 13.5 tackles for loss. (Photo by Michael DeMocker, NOLA.com | Times-Picayune) By Randy Rosetta, NOLA.com | The Times-Picayune The Times-Picayune
on December 29, 2012 at 7:15 PM, updated December 29, 2012 at 9:40 PM Print
ATLANTA -- It was a sweltering day on the field in a hostile environment at Ben Hill Griffin Stadium back in early October, with LSU and Florida locked up in an intense defensive struggle. All of a sudden it hit safety Eric Reid as the defense huddled up for the next snap.
As linebacker Kevin Minter's spectacular day was unfolding -- as always quietly and without a lot of fanfare -- his teammates took notice.
"We were standing there, trying to catch our breath, and Eric looked over and said 'Kevin, do you know you've made every play?'" defensive end Barkevious Mingo said, trying to imitate Reid's respectfully incredulous tone when he realized what Minter was doing.
"Kevin was in a zone -- flying around and making plays. Making every play."
LSU middle linebacker Kevin Minter: 'I had to work hard and compete for everything I got, and that's made me appreciate it that much more.'
Chris Granger, NOLA.com | Times-Picayune
Well, maybe not every play, although it seemed that way. Minter was undoubtedly spectacular that day in The Swamp with 17 solo tackles and 3 assists. That turned out to be the signature game of what has been a special season for the fourth-year LSU junior.
That season winds down Monday not far from Minter's hometown in Suwanee, Ga., when he and No. 9-ranked LSU (10-2) square off with 14th-ranked Clemson (10-2) in the 2012 Chick-fil-A Bowl at the Georgia Dome.
And in his typical unassuming fashion, Minter is wide-eyed at the idea of stepping back on the field where some of his biggest games have unfolded.
"I played in the state championship game here and lost," Minter said. "I've also played here against North Carolina (the first start of his career in 2010) and in the SEC Championship Game. I've got a lot of history here. I've always played fairly well here. I love the Georgia Dome."
That's about as close as the 6-foot-2, 245-pound Minter comes to brashness.
On those 20 tackles he was in on against Florida, not once did Minter get up off the pile of humanity yapping or talking trash. Instead, every play he's a part of ends with him trotting back to the huddle or to his spot in the middle of the Tigers' defense.
Flip that around, and you won't see -- or hear -- Minter imploring teammates with passionate speeches or arm-waving demonstrations.
The most his LSU teammates usually get, Mingo said, is Minter firmly and quietly urging "Let's go!"
Barkevious Mingo
LSUSports.net "I tease him sometimes because that's all we get from him," Mingo said. "I tell him, 'That's it, man?' But that's a lot of emotion from Kevin."
No argument from Minter. He concedes that working up a verbal lather is not part of his repertoire.
"It kind of came with my personality," he said. "I've never been that kind of guy. I've always been somebody who leads by example. I was a lot more assertive this year as far as getting guys lined up and telling them where they need to be because it's kind of what this job demands. But I've never felt like I needed to yell or scream to make my point."
Nor has he had to rely on vocal theatrics to be an effective defensive quarterback a season after the Tigers' linebacker corps struggled most of the season.
Minter was a part-time starter in 2011, splitting time with Karnell Hatcher, as defensive coordinator John Chavis deployed a 4-2-5 scheme almost exclusively to accentuate the talents of Tyrann Mathieu as a ball-hawking playmaker.
When Mathieu was dismissed from the team prior to the season, on top of the losses of defensive backs Mo Claiborne, Brandon Taylor and Ron Brooks to the NFL, there was a gaping hole on the defense for somebody who could consistently supply a game-changing presence.
LSU middle linebacker Kevin Minter played a key role in the Tigers' ability to slow down Texas A&M quarterback Johnny Manziel with a team-high 12 tackles.
Chris Granger, NOLA.com | Times-Picayune
While Minter isn't the same kind of dynamo that Mathieu was, he has helped fill the void in different ways.
Chavis was more comfortable using three linebackers more often this season, with junior Lamin Barrow also emerging as a star on the weakside and several players taking on the task on the strongside when Tahj Jones was ruled academically ineligible.
Minter rewarded Chavis and the rest of the defense by delivering a huge season.
The performance at Florida was the centerpiece, but he also recorded three other games with 10 tackles or more and has 111 stops heading into the bowl game. Minter has notched 13½ tackles for loss - at least one in every game but two.
This wasn't an overnight metamorphosis for Minter. Without an ounce of hesitation, he describes himself as a system player and says he took his time to learn as he toiled behind Kelvin Sheppard in 2010 and shared time with Hatcher last season.
"I had to work hard and compete for everything I got, and that's made me appreciate it that much more," Minter said.
"I've always had the size, strength and talent to be a good linebacker. It was just a matter of getting the system down and gaining confidence in myself in the ability to move people around and tell them where they need to be."
There was an impetus to that confidence.
Chavis' pride and joy as a coach has always been stout linebacker play and when that unit came under criticism and scrutiny in 2011, LSU's defensive coordinator felt that sting as deeply as the players.
LSU defensive coordinator John Chavis
Associated Press So in the off-season, Chavis sat down with the player he knew could spearhead an immediate and necessary turnaround.
"Coach Chavis told me 'You've always had the potential and now it's time to start living up to that,' " Minter said. "That meant a lot to me - that he thought I was that kind of player. It motivated me to work a lot harder in the off-season and from the first game, it felt different out there. It felt easier, almost like I was back in high school."
The result of the heart-to-heart with Chavis was that Minter emerged not only as a team leader, but also as one of the best linebackers in the country.
"It was an opportunity, and certainly we needed for him to step up and be front and center," Chavis said. "Kevin is a real quiet guy, but I saw both sides, on and off the field, and I feel like I know him very, very well. He's the kind of leader that you want to have."
That applies off the field as well.
Minter graduated earlier this month and has never been affiliated with a sniff of trouble. In an age when players are closely watched, their social media habits are over-analyzed and news of arrests and suspensions have mushroomed, Minter relies more on politeness and letting his actions speak.
"He's the kind of guy who leads by example," said Barrow, one of Minter's closest friends. "He does everything right on and off the field, and that's naturally somebody you look up to. When he has to be vocal, he can be."
Added Reid, "He's a great example-setter for the young guys, somebody they can look up to and somebody they can count on if they have a question, they can go to him and he'll answer it and not embarrass them."
More than that, though, Minter has that hidden ability to do what coaches crave most in their best players: He makes those around him better.
Not with a bunch of bravado - remember, "Let's go!" is as much as he offers up - but instead with the personality that other players around him follow and emulate.
LSU linebacker Lamin Barrow: 'Feeding off (Minter's) energy has helped make me a better player this year.'
NOLA.com | Times-Picayune
"Feeding off his energy has helped make me a better player this year," Barrow said matter-of-factly. "We always dreamed of being out there together from the time we got here, and he just helps motivate me by showing me you can make your statement with the way you play."
At the team banquet a few weeks ago, Minter was voted by his teammates as the team Most Valuable Player.
Still seemingly stunned by that recognition, Minter paused and contemplated his answer when asked how significant that is to him.
When he finally did, he delivered what will eventually be a perfect and fitting epitaph to his LSU career.
"It tells me that my teammates see me as a guy who tries his best and does everything he can for his team," Minter said.
I was looking at RB's again the other day, thinking about who would be a nice part of a duo with David Wilson, and i am telling you, Kerwynn Williams of Utah st is a very underrated player.. He caught 40plus balls, had 2games of over 100recieving and 100rushing on the season, and was flat out dominant! Hes not a big guy like Andre Brown, as hes only 5ft 8in 190lbs, but hes quick, deadly in open field, and can flat out catch the rock.. Shoot, they split him out alot, and he looks like a slot reciever out there, and not a RB... I think he'd be a great change of pace back for David Wilson, and really give us a dyanmic backfield.. I like some bigger backs as well, but Kerwynn Williams has moved up my personal rankings for sure..
This kids got oodles of vision , balance, and speed.. Also, lower center of gravity and a solid 190lbs on his 5ft 8in frame, makes em not a easy tackle...
Last edited by nycsportzfan; 01-11-2013 at 08:31 AM.
I dont see it in Kerwynn Williams . as a UFA maybe
The other part of this that sucks is that if they switch to a 43 they absolutely will be in the market for another 43 DE. Remember, this is the team that drafts 1 pick ahead of us.
Last edited by BlueSanta; 01-11-2013 at 06:54 PM.


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The main thing to look at is the front of the frame, where the crane closes. This joint should be a very thin line without any gap. Then, if everything else looks O.K., shoot the thing. If your buillet hits where you want it to, and stuff doesn't fly out sideways from the barrel/cylinder gap, you're fine. When a gun shoots reliably and accurately, leave it alone.
Bob Wright


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Justin Newcombe explains how to to give your garden a cutting edge.
Good design is knowing where to draw the line.
I spent the best part of the nineties and first decade of the naughty's designing gardens pretty much non-stop. Besides all the to-ing and fro-ing between wish lists and budgets, the design could usually be broken down into a set of simple questions. The key one was "So, how do you like it, straight or curvy?" - which I admit, as I write it, seems more like a toe in the pool in an internet chat room rather than a serious question exploring the virtues of alternate aesthetic variations in the garden design process. But, importantly, the answer helped me pursue the most appropriate design line for a particular garden. The interesting part was how to express that line.
In a typical lawn, for example, I almost always started by drawing the lawn before I drew the garden, as the lawn is the dominant element. I also almost always tried to frame the lawn using a mowing strip. This is a hard surface which is flush with the lawn, giving the lawn mower unimpeded access to the edges of the lawn. It's also a great opportunity implement line.
The materials you use can change the way you see the garden.
Let's take a square lawn as an example. If we use old brick, side by side and point in between each one with mortar, we send a rather different message than if we use terrazzo (polished concrete) with a coloured glass inlay. Both materials have a kind of currency, both contribute to a design language and depending on the one you choose, the story in the garden will be different. A structure as simple as a mowing strip can set an atmosphere which echoes throughout the rest of the garden design.
Planting can add strong definition in conjunction with other elements such as mowing strips or paths but also function as an edge on its own. Hedging is a classic example. Box hedges in particular have been used for hundreds of years as an expression of line in a garden setting. There's a tendency when using hedges to just run them around the edges like a kind of plant wall. Fair enough, this kind of garden can be charming but it can also be unnecessarily obvious. A bit more interplay with other aspects of the garden can make for a lot more interest. By setting parts of the hedge back from the edges or shaping the hedge differently from the edges, then planting bulbs, annuals or colourful edibles in the resulting gaps, you successfully dissolve the monotony.
Large drifts of smaller plants and ground covers can also define garden edges. The most popular of these plants seems to be mondo grass (ophiopogon japonica). This is primarily because of its reliability and tough nature but annuals such as celosia, lobelia, marigolds and a myriad others are definitely worth the effort. For winter colour you can't go past cyclamen. Garden design, as I mentioned earlier, has a language of its own which has developed over hundreds of years and I think interesting garden design is about being clever with what you've got rather than reinventing the wheel. Or the straight line.


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Home › Forums › Gear Forums › Gear (General) › Question for Quilt Users
Dec 16, 2009 at 10:50 am #1252780
I have a quick question for all you quilt users out there. I have not been able to afford a good down quilt but my awesome family all chipped in to get me a heavily dicounted golite ultra 20. The only problem is its a short. I fit in okay but there is not a lot of extra room.
My question is has anyone had experience with a quilt that is just big enough? I want to keep it but I was wondering if anyone with more experience would expect problems(I'm not clastraphobic by the way).Dec 16, 2009 at 10:58 am #1554398
Chris WBPL Member
@simplespiritLocale: .
Unlike a bag a quilt should generally only come up to around your chin. It basically cinches around the neck and you depend on a separate hood worn by itself or as part of a jacket/parka.Dec 16, 2009 at 11:01 am #1554399
Jeff PatrickBPL Member
How short is it? So when you lay in it how far does it come up your body without having to stretch it?
You want it to come up to at least above your shoulders so that you can seal out drafts when its cold using the cinch cord. Even then you definitely need some head insulation.
You'll probably be fine if its just a little short, but most likely it will raise the temp of how low you can take it. You'll probably need to suppliment it with a jacket anyways so you might just want to do a beefier one if you decide to keep it.Dec 16, 2009 at 11:15 am #1554406
I can cinch it up over my shoulders and stretch my legs out. It might compress the down at the bottom at bit so I would bring an extra pair of socks. I tried it with a down ski jacket and there seems to be room for that without compressing the down. It seems to be almost exactly big enough bit with no extra wiggle room. Golite seems to be shutting down production because shorts are about all thats out there (for the sale price).Dec 16, 2009 at 11:39 am #1554422
Jeff PatrickBPL Member
seems like you should be ok. Worst scenario is it works, just not to as cold a temperature as you want it to.
And since it already doesn't go down to 20 thats not too big of an issue.Dec 16, 2009 at 11:46 am #1554427
Thanks for the input guys I think I'll keep it. Worst case scenerio I could probably get someone like Tim Marshall to add an extra baffle to the top or do it myself.Dec 16, 2009 at 4:39 pm #1554516
DougBPL Member
I think you'll be fine Luke. As others have said, you'll want to wear a jacket with it anyway if you're really going to try to go as low as 20 degrees. I've had various quilts down under 30 and still haven't used the cinch cord around the neck area (haven't even hooked it together). I find I usually only have to tuck it around me and it does fine.Dec 16, 2009 at 7:37 pm #1554594
Thanks Doug, I have used a quilt before (BPL UL60) but it was plenty roomy. I was hoping no one would tell me that a down quilt needs lots of extra room or it will compress from the inside etc. Since no one has a horror story about that, I won't worry. This is exciting because until now my choice was the UL60 or a 2 pound sleeping bag. One time in CO I did a crazy amount of layering to try and make that quilt work down to 35 degrees. With the Ultra I can drop a pound of bag and us a smaller and ligher pack.
Have a great Christmas.Dec 16, 2009 at 7:42 pm #1554595
DougBPL Member
Also remember, Luke, that if you're not sure, and you still have the BPL UL60, at 11 oz. or so you can always carry it as well and layer it over the Ultra 20, instead of carrying a lot of extra clothes to layer instead. I'll bet the two together would keep you toasty down to 20 degrees and then some!Dec 16, 2009 at 7:57 pm #1554601
Good idea Doug although I have a tendancy to squeeze the most possible out of my UL gear. I took the UL60 down into the 30s once although that was pushing things. I'll have to get out sometime soon and see how the Ultra works out.
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text:
Measure D supporters were glum as Superintendent Rob Kessler spoke to them Tuesday night shortly after 9 p.m., thanking them for their efforts. Absentee ballots and early returns showed the parcel school tax was receiving 58 percent support when it needed 66 percent to pass.
Read the full story here Web Link posted Wednesday, June 4, 2008, 12:21 PM
Town Square
Measure D fails; Supervisor Piepho gets another term
Original post made on Jun 4, 2008
Like this commentPosted by Lucy
a resident of Danville
on Jun 4, 2008 at 2:06 pm
Wow-- I wonder what all of the non-supporters of Mary have to say now????
Like this commentPosted by Claire
a resident of Alamo
on Jun 5, 2008 at 9:18 am
I wonder if Measure D might have a better chance in a general election. I can only assume that people voted against it because they must think the school district can somehow juggle its budget to provide everything without sustaining and increasing the parcel tax. I don't think anyone wants to cut these programs or minds terribly paying the tax - they must not trust that the district is budgeting its best. So how can the school community gain this trust?


text:
If your pet could talk, how would it change your relationship? What kind of adventures would you go on together? That's the concept of Nickelodeon's new cartoon, Sanjay and Craig. It's about imaginative 12-year-old Sanjay Patel and his best friend, Craig, a talking pet snake and a master of disguise. The show premieres Saturday May 25 at 10:30 a.m. Eastern Time on Nickelodeon. It was created by co-executive producers Jim Dirschberger, Jay Howell and Andreas Trolf. "There's something about your best friend," Trolf told TFK. "Together with him or her, anything is possible. You can't wait to get up in the morning to have an adventure."
Because Craig is a snake, he can shape and stretch into almost anything. He's also a master of disguise, so he can go wherever Sanjay goes. "Craig pushes you to have as rad of a time as possible," Trolf says. "He's a cool dude, but he's also this crazy reptile guy that is sometimes still a bit of a wild animal."
Upcoming episodes find the best friends in some hilarious situations: The duo wins 100 pet dogs in a competition; Sanjay tries to snake-rope walk on Craig to cross a stinky pool of water; Craig enters a beauty pageant disguised as their friend Megan; and the friends try to retrieve a hundred dollar bill that they find frozen in ice. That last scenario is based on something that actually happened to co-creator Dirschberger as a kid. "None of us has seen a butt transplant or gotten kicked out of comedy clubs for laughing too hard," Trolf told TFK. "But the majority of the adventures of Sanjay and Craig are inspired by real life."
Behind the Voices
Actor Maulik Pancholy, who voices Baljeet on Phineas and Ferb, is the voice of Sanjay. Comedian Chris Hardwick voices Craig. When recording for animation, actors often work alone in the recording booth, and their voices are mixed in with other characters later. But Pancholy and Hardwick have worked together in the recording booth for Sanjay and Craig. "There is this magic that happens when you get Maulik and Chris in the room together," Trolf says. "It seems like they've been friends forever. When they start riffing and improving lines, it's incredible. They are the perfect Sanjay and Craig."
Earlier this week, TFK spoke to Pancholy while he was working on the show at a recording studio in New York City. He says he appreciates getting to collaborate with Hardwick. "Chris has just boundless energy," he says. "When we work together, our energy escalates, and the things we are excited about become SUPER EXCITING. It's really fun."
Pancholy also told TFK that Sanjay reminds him of himself as a kid. "Sanjay's got this very awkward side, and I can relate to feeling like you're not the coolest kid around," he says. "And he's got this great imagination. Growing up in Indiana, my friends and I would go bike riding and every ride was an adventure, solving crimes!"
Catch Sanjay and Craig's adventures when the show airs Saturday mornings on Nickelodeon. For more with Pancholy, watch the video below.


text:
A strange new family of algorithms probes the boundary between easy and hard problems
Brian Hayes
Why are some computational problems so hard and others easy? This may sound like a childish, whining question, to be dismissed with a shrug or a wisecrack, but if you dress it up in the fancy jargon of computational complexity theory, it becomes quite a serious and grownup question: Is P equal to NP? An answer—accompanied by a proof—will get you a million bucks from the Clay Mathematics Institute.
I'll return in a moment to P and NP, but first an example, which offers a glimpse of the mystery lurking beneath the surface of hard and easy problems. Consider a mathematical graph, a collection of vertices (represented by dots) and edges (lines that connect the dots). Here's a nicely symmetrical example:
Is it possible to construct a path that traverses each edge exactly once and returns to the starting point? For any graph with a finite number of edges, we could answer such a question by brute force: Simply list all possible paths and check to see whether any of them meet the stated conditions. But there's a better way. In 1736 Leonhard Euler proved that the desired path (now called an Eulerian circuit) exists if and only if every vertex is the end point of an even number of edges. We can check whether a graph has this property without any laborious enumeration of pathways.
Now take the same graph and ask a slightly different question: Is there a circuit that passes through every vertex exactly once? This problem was posed in 1858 by William Rowan Hamilton, and the path is called a Hamiltonian circuit. Again we can get the answer by brute force. But in this case there is no trick like Euler's; no one knows any method that gives the correct answer for all graphs and does so substantially quicker than exhaustive search. Superficially, the two problems look almost identical, but Hamilton's version is far harder. Why? Is it because no shortcut solution exists, or have we not yet been clever enough to find one?
Most computer scientists and mathematicians believe that Hamilton's problem really is harder, and no shortcut algorithm will ever be found—but that's just a conjecture, supported by experience and intuition but not by proof. Contrarians argue that we've hardly begun to explore the space of all possible algorithms, and new problem-solving techniques could turn up at any time. Before 1736, the Eulerian-circuit problem also looked hard.
What prompts me to write on this theme is a new and wholly unexpected family of algorithms that provide efficient methods for several problems that previously had only brute-force solutions. The algorithms were invented by Leslie G. Valiant of Harvard University, with extensive further contributions by Jin-Yi Cai of the University of Wisconsin. Valiant named the methods "holographic algorithms," but he also refers to them as "accidental algorithms," emphasizing their capricious, rabbit-from-the-hat quality; they seem to pluck answers from a tangle of unlikely coincidences and cancellations. I am reminded of the famous Sidney Harris cartoon in which a long series of equations on a blackboard hinges on the notation "Then a miracle occurs."
For most of us, the boundary between fast and slow computations is clearly marked: A computation is slow if it's not finished when you come back from a coffee break. Computer science formalizes this definition in terms of polynomial-time and exponential-time algorithms.
Suppose you are running a computer program whose input is a list of n numbers. The program might be sorting the numbers, or finding their greatest common divisor, or generating permutations of them. No matter what the task, the running time of the program will likely depend in some way on n, the length of the list (or, more precisely, on the total number of bits needed to represent the numbers). Perhaps the time needed to process n items grows as n 2. Thus as n increases from 10 to 20 to 30, the running time rises from 100 to 400 to 900. Now consider a program whose running time is equal to 2 n . In this case, as the size of the input grows from 10 to 20 to 30, the running time leaps from a thousand to a million to a billion. You're going to be drinking a lot of coffee.
The function n 2 is an example of a polynomial; 2 n denotes an exponential. The distinction between these categories of functions marks the great divide of computational complexity theory. Roughly speaking, polynomial algorithms are fast and efficient; exponential algorithms are too slow to bother with. To speak a little less roughly: When n becomes large enough, any polynomial-time program is faster than any exponential-time program.
So much for the classification of algorithms. What about classifying the problems that the algorithms are supposed to solve? For any given problem, there might be many different algorithms, some faster than others. The custom is to rate a problem according to the worst-case performance of the best algorithm. The class known as P includes all problems that have at least one polynomial-time algorithm. The algorithm has to give the right answer and has to run in polynomial time on every instance of the problem.
Classifying problems for which we don't know a polynomial-time algorithm is where it gets tricky. In the first place, there are some problems that require exponential running time for reasons that aren't very interesting. Think about a program to generate all subsets of a set of n items; the computation is easy, but because there are 2 n subsets, just writing down the answer will take an exponential amount of time. To avoid such issues, complexity theory focuses on problems with short answers. Decision problems ask a yes-or-no question ("Does the graph have a Hamiltonian circuit?"). There are also counting problems ("How many Hamiltonian circuits does the graph have?"). Problems of these kinds might conceivably have a polynomial-time solution, and we know that some of them do. The big question is whether all of them do. If not, what distinguishes the easy problems from the hard ones?
The letters NP might well be translated "notorious problems," but the abbreviation actually stands for "nondeterministic polynomial." The term refers to a hypothetical computing machine that can solve problems through systematic guesswork. For the problems in NP, you may or may not be able to compute an answer in polynomial time, but if you happen to guess the answer, or if someone whispers it in your ear, then you can quickly verify its correctness. NP is the complexity class for conscientious cheaters—students who don't do their own homework but who at least check their cribbed answers before they turn them in.
Detecting a Hamiltonian circuit is one example of a problem in NP. Even though I don't know how to solve the problem efficiently for all graphs, if you show me a purported Hamiltonian circuit, I can readily check whether it passes through every vertex once:
(Note that this verification scheme works only when the answer to the decision problem is "yes." If you claim that a graph doesn't have a Hamiltonian circuit, the only way to prove it is to enumerate all possible paths.)
Within the class NP dwells the elite group of problems labeled NP-complete. They have an extraordinary property: If any one of these problems has a polynomial-time solution, then that method can be adapted to quickly solve all problems in NP (both the complete ones and the rest). In other words, such an algorithm would establish that P = NP. The two categories would merge.
The very concept of NP-completeness has a whiff of the miraculous about it. How can you possibly be sure that a solution to one problem will work for every other problem in NP as well? After all, you can't even know in advance what all those problems are. The answer is so curious and improbable that it's worth a brief digression.
The first proof of NP-completeness, published in 1971 by Stephen A. Cook of the University of Toronto, concerns a problem called satisfiability. You are given a formula in Boolean logic, constructed from a set of variables, each of which can take on the values true or false, and the logical connectives AND, OR and NOT. The decision problem asks: Is there a way of assigning true and false values to the variables that makes the entire formula true? With n variables there are 2 n possible assignments, so the brute-force approach is exponential and unappealing. But a lucky guess is easily verified, so the problem qualifies as a member of NP.
Cook's proof of NP-completeness is beautiful in its conception and a shambling Rube Goldberg contraption in its details. The key insight is that Boolean formulas can describe the circuits and operations of a computer. Cook showed how to write an intricate formula that encodes the entire operation of a computer executing a program to guess a solution and check its correctness. If and only if the Boolean formula has a satisfying assignment, the simulated computer program succeeds. Thus if you could determine in polynomial time whether or not any Boolean formula is satisfiable, you could also solve the encoded decision problem. The proof doesn't depend on the details of that problem, only on the fact that it has a polynomial-time checking procedure.
Thousands of problems are now known to be NP-complete. They form a vast fabric of interdependent computations. Either all of them are hard, or everything in NP is easy.
To understand the new holographic algorithms, we need one more ingredient from graph theory: the idea of a perfect matching.
Consider the double-feature festival. You want to show movies in pairs, with the proviso that any two films scheduled together should have a performer in common; also, no film can be screened more than once. These constraints lead to a graph where the vertices are film titles, and two titles are connected by an edge if the films share an actor. The task is to identify a set of edges linking each vertex to exactly one other vertex. The brute-force method of trying all possible matchings is exponential, but if you are given a candidate solution, you can efficiently verify its correctness:
Thus the perfect-matching problem lies in NP.
In the 1960s Jack Edmonds, now of the University of Waterloo, devised an efficient algorithm that finds a perfect matching if there is one. The Edmonds algorithm works in polynomial time, which means the decision problem for perfect matching is in P. (Indeed, Edmonds's 1965 paper includes the first published discussion of the distinction between polynomial and exponential algorithms.)
Another success story among matching methods applies only to planar graphs—those that can be drawn without crossed edges. On a planar graph you can efficiently solve not only the decision problem for perfect matching but also the counting problem—that is, you can learn how many different subsets of edges yield a perfect matching. In general, counting problems seem more difficult than decision problems, since the solution conveys more information. The main complexity class for counting problems is called #P (pronounced "sharp P"); it includes NP as a subset, so #P problems must be at least as hard as NP.
The problem of counting planar perfect matchings has its roots in physics and chemistry, where the original question was: If diatomic molecules are adsorbed on a surface, forming a single layer, how many ways can they be arranged? Another version asks how many ways dominos (2-by-1 rectangles) can be placed on a chessboard without gaps or overlaps. The answers exhibit clear signs of exponential growth; when you arrange dominos on square boards of size 2, 4, 6 and 8, the number of distinct tilings is 2, 36, 6,728 and 12,988,816. Given this rapid proliferation, it seems quite remarkable that a polynomial-time algorithm can count the configurations. The ingenious method was developed in the early 1960s by Pieter W. Kasteleyn and, independently, Michael E. Fisher and H. N. V. Temperley. It has come to be known as the FKT algorithm.
The mathematics behind the FKT algorithm takes some explaining. In outline, the idea is to encode the structure of an n-vertex graph in an n-by-n matrix; then the number of perfect matchings is given by an easily computed property of the matrix. The illustration (above right) shows how the graph is represented in matrix form.
The computation performed on the matrix is essentially the evaluation of a determinant. By definition, a determinant is a sum of n! terms, where each term is a product of n elements chosen from the matrix. The symbol n! denotes the factorial of n, or in other words n×(n–1)×...×3×2×1. The trouble is, n! is not a polynomial function of n; it qualifies as an exponential. Thus, under the rules of complexity theory, the whole scheme is really no better than the brute-force enumeration of all perfect matchings. But this is where the rabbit comes out of the hat. There are alternative algorithms for computing determinants that do achieve polynomial performance; the best-known example is the technique called Gaussian elimination. With these methods, all but a polynomial number of terms in that giant summation magically cancel out. We never have to compute them, or even look at them.
(The answer sought in the perfect-matching problem is actually not the determinant but a related quantity called the Pfaffian. However, the Pfaffian is equal to the square root of the determinant, and so the computational procedure is essentially the same.)
The existence of a shortcut for evaluating determinants and Pfaffians is like a loophole in the tax code—a windfall for those who can take advantage of it, but you can only get away with such special privileges if you meet very stringent conditions.
Closely related to the determinant is another quantity associated with matrices called the permanent. It's another sum of n! products, but even simpler. For the determinant, a complicated rule assigns positive and negative signs to the various terms of the summation. For the permanent, there's no need to bother keeping track of the signs; they're all positive. But the alternation of signs is necessary for the cancellations that allow fast computation of determinants. As a result, the polynomial loophole doesn't work for permanents. In 1979 Valiant showed that the calculation of permanents is #P-complete. (It was in this work that the class #P was first defined.)
At a higher level, too, the conspiracy of circumstances that allows perfect matchings to be counted in polynomial time seems rather delicate and sensitive to details. The algorithm works only for planar graphs; attempts to extend it to larger families of graphs have failed. Even for planar graphs, it works only for perfect matchings; counting the total number of matchings is a #P-complete task.
The engine that drives the FKT algorithm is the linear-algebra shortcut for evaluating determinants (or Pfaffians) in polynomial time. This prime mover is harnessed to solve a counting problem in another area of mathematics, namely graph theory. Such translations, or "reductions," from one problem to another are standard fare in complexity theory. Holographic algorithms also rely on reductions, and indeed they ultimately translate problems into the language of determinants. But the nature of the reductions is novel.
A typical non-holographic reduction is a one-to-one mapping between problems in two domains. If you can reduce problem A to problem B, and then find a solution to an instance of B, you know that the corresponding instance of A also has a solution. Devising transformations that set up this one-to-one linkage between problems is a demanding art form. Holographic reductions exploit a broader class of transformations that don't necessarily link individual problem instances, but the reductions do preserve the number of solutions or the sum of the solutions. For certain counting problems, that's enough.
A problem with the cryptic name #PL-3-NAE-ICE supplies an example of the holographic process. The problem concerns a planar graph of maximum degree three; that is to say, no vertex has more than three edges. Each edge is to be assigned a direction, subject to the constraint that no vertex of degree two or three can have all of its edges directed either inward or outward. Graphs of this general kind have been studied as models of the structure of ice; the vertices represent molecules and the directed edges are chemical bonds. The decision version of the problem asks whether the edges can be assigned directions so that the not-all-equal constraint is obeyed everywhere. Here we are interested in the counting version, which asks how many ways the constraints can be satisfied.
The strategy is to build a new planar graph called a matchgrid, which encodes both the structure of the ice graph and the not-all-equal constraints that have to be satisfied at each vertex. Then we calculate a weighted sum of the perfect matchings in the matchgrid, using the efficient FKT algorithm. Although there may be no one-to-one mapping between individual matchings in the matchgrid and valid assignments of bond directions in the ice graph, the weighted sum of the perfect matchings is equal to the number of valid assignments.
The matchgrid is constructed from components called matchgates, which are planar graph fragments that act much like the logic gates of Boolean circuits. To understand how this computer built of graphs works, it helps to consider first an idealized and simplified version, in which we can manufacture matchgates to meet any specifications we please.
Given such an unlimited stock of gates, we can assemble a model of PL-3-NAE-ICE as follows. A degree-three vertex in the ice graph is represented by a "recognizer" matchgate with three inputs. The recognizer has a "signature" that implements the not-all-equal function: the gate is designed so that its contribution to the sum of the perfect matchings is 0 if the three inputs are 000 or 111, but the contribution is 1 for any of the other six possible input patterns (001, 010, 011, 100, 101, 110).
Each edge of the ice graph is represented in the matchgrid by a "generator" matchgate that has two outputs, corresponding to the two ends of the edge. To capture the idea that an edge has a direction—pointing toward one end and away from the other—the generator contributes 1 to the weighted sum when the outputs are either 01 or 10, but the contribution is 0 for outputs 00 and 11.
In this scheme, the concept of perfect matching becomes a computational mechanism. If a graph fragment, packaged up as a matchgate, allows a perfect matching, then the gate outputs a logical 1, or true. If no perfect matching is possible, the output is 0, or false. This is a novel and interesting way to build a computer, but there's a catch. Many of the needed matchgates cannot be implemented in the direct manner described above. In particular, the three-input not-all-equal gate cannot be implemented. The reason is easy to demonstrate. Perfect matching is all about parity; a graph cannot possibly have a perfect matching unless the number of vertices is even. The three-input not-all-equal gate is required to respond in the same way to the inputs 000 and 111. But these patterns have opposite parity; one is even and the other is odd.
The remedy for this impediment is yet more linear algebra. Although no simple matchgate can directly implement the three-input not-all-equal function, the desired behavior can be generated as a linear superposition of other functions. Finding an appropriate set of equations to create such superpositions is the most essential and also the most difficult aspect of applying the holographic method. It has mostly been a hit-or-miss proposition, requiring both inspiration and expert use of computer-algebra systems. Cai and Pinyan Lu of Tsinghua University have recently made progress on systematizing the search process.
So far about a dozen counting problems have been solved by the holographic method, none of them having any immediate practical use or consequences for the further development of complexity theory. Indeed, they are an odd lot—apart from the ice problem they are mostly specialized and restricted versions of satisfiability and matching. One particularly curious result gives a fast algorithm for counting a certain set of solutions modulo 7, but counting the same set modulo 2 is at least as hard as NP-complete.
Why are the methods called holographic algorithms? Valiant explains that their computational power comes from the mutual cancellation of many contributions to a sum, as in the optical interference pattern that creates a hologram. This sounds vaguely like the superposition principle in quantum computing, and that is not entirely a coincidence. Valiant's first publication on the topic, in 2002, was titled "Quantum circuits that can be simulated classically in polynomial time."
Do holographic algorithms reveal anything we didn't already know about the P = NP question? Lest there be any misunderstanding, one point bears emphasizing: Although some of the problems solved by holographic methods were not previously known to be in P, none of them were NP-complete or #P-complete. Thus, so far, the barrier between P and NP remains intact.
Suggesting that P might be equal to NP is deeply unfashionable. A few years ago William Gasarch of the University of Maryland took a poll on the question. Of 100 respondents, only nine stood on the side of P = NP, and Gasarch reported that some of them took the position "just to be contrary." The idea that all NP problems have easy solutions seems too good to be true, an exercise in wishful thinking; it would be miraculous if we lived in a universe where computing is so effortless. But the miracle argument cuts both ways: For NP to remain aloof from P, we have to believe that not even one out of all those thousands of NP-complete problems has an efficient solution.
Valiant suggests a comparison with the Goldbach conjecture, which holds that every even number greater than 2 is the sum of two primes. Nearly everyone believes it to be true, but in the absence of a proof, we don't know why it should be true. We can't rule out the possibility that exceptions exist but are so rare we haven't stumbled on one yet. Likewise with the P and NP question: A polynomial algorithm for just one NP-complete problem would forever alter the landscape.
The work on holographic algorithms doesn't have to be seen as some sort of wildcat drilling expedition, hoping to strike a P = NP gusher. It would be worthwhile just to have a finer survey of the boundaries between complexity classes, showing more clearly what can and can't be accomplished with polynomial resources. Valiant writes that "any proof of P ? NP will need to explain, and not only to imply, the unsolvability of our polynomial systems."
Finally, there's the challenge of understanding the algorithms themselves at a deeper level. To call them "accidental"—or "exotic," or "freak," which are other terms that turn up in the literature—suggests that they are sports of nature, like weird creatures found under a rock and put on exhibit. But one could also argue, on the contrary, that these algorithms are not at all accidental; they are highly engineered constructions. The elaborate systems of polynomials needed to create sets of matchgates are not something found in the primordial ooze of mathematics. Someone had to invent them.
© Brian Hayes
You can find this online at http://www.americanscientist.org/issues/num2/accidental-algorithms/2
© 2016 Sigma Xi, The Scientific Research Society