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Randy Dishmon, Portfolio Manager of Oppenheimer Global Value Fund, applies a distinct approach to value investing and identifying undervalued companies.
He values companies by looking at core, fundamental company realities like: operating cash flow, balance sheet strength, strategic assets, private market value and break-up value.
The approach combines a thematic framework to idea generation with fundamental company analysis. Dishmon looks for businesses with durable characteristics and structural tailwinds that can outperform over the long term.
Entry points are sought where a large gap exists between the current market price and a conservative estimate of intrinsic value. Oppenheimer Global Value Fund can serve as a core equity portfolio allocation for investors seeking capital appreciation.
"I don't buy markets. I'm looking for the best 50 to 60 ideas I can find wherever they are in the world."
—Randy Dishmon
Q: How do you define value?
A: Essentially, all great investments begin with buying something for less than it's worth. For anyone looking for a formula for great value investing, that's as close as you're ever going to get. Value is not a matter of simply plugging certain quantitative factors into a prescribed formula or fitting into a style box. It's not that easy. The concept of intrinsic value as developed and formalized by Graham & Dodd has always been a flexible one. In fact, in their book, Security Analysis, published in 1934, they make no mention of an exact definition or formula for determining value. They simply advocate buying good companies with favorable prospects priced with a large margin of safety. That makes as much sense now as it did then.
Q: How does your approach to value differ from modern convention?
A: I believe it does in several ways. First, the modern perspective has been that price to earnings (P/E), price to book (P/B), and price to sales in some combination is the appropriate way to define what is cheap versus what is not. This is flawed, in my view. P/E and P/B, in particular, are downstream of an array of accounting decisions. As a result, they can be manipulated or shaped in ways that can serve the incentives of the people preparing the statements, not necessarily an outside investor. It's why I prefer to anchor concepts of value in numbers that better reflect business reality. Operating cash flow is a much better starting point. It is largely free of accounting distortions and is hard to manipulate. I start my valuation process there.
Second, there has been an evolution of sorts in the last 20 years or so, where more and more businesses operate with relatively modest amounts of physical capital, but loads of intellectual capital. This has meant that some traditional valuation tools like price to book can present a distorted valuation picture. Media and some types of technology companies are probably the most obvious examples of where this occurs. It's not unusual to see opportunities in these kinds of companies where the cash flow or price-to-earnings ratios are modest, but price-to-book ratio is pretty high.
If you apply a valuation test to determine if the company is cheap, the P/B ratio gets distorted by the capital light nature of the business model. It looks like it is not "value," but in truth it really is. Relying on rigid, quantitative definitions of value can cause you to miss good, cheap companies.
Third, when I examine the investment merits of a company and value it, I do so as if I were going to take it over, manage it and harvest excess cash out of it. It is a more strategic way to consider investments, more common to control investing or perhaps private equity than mutual fund investing. However, it grounds the process in the operating reality and price of the business at hand, not the day-to-day noise and commotion of Wall Street. As a result, over time, I believe we are more apt to pay the right price for our ideas.
Finally, as Einstein once said, "Not everything that counts can be counted, and not everything that can be counted counts." I always keep this in mind. There are things which drive or create value like management instinct or creativity that are hard to measure, but can matter a lot. Peter Lynch once warned of the perils of relying too much on just numbers. A judgment about what something might be worth is more than just math. Businesses are living and breathing things in a sense. They can change, and that can markedly affect value, but may not appear in simple ratios.
Q: Do you ever think of value in a relative sense?
A: Short answer, no. Value is an absolute, not a relative, concept. Either a company is cheap or it isn't. There is no bottom third of this category or bottom third of that sector or industry to define cheap. Relative anything doesn't protect you from loss. In fact, it can lead you to a value trap. By accounting metrics, a stock might look cheap, but what if the company operates in an industry that will be rendered obsolete in the near future? Do you still think that company is a good value opportunity? What if the industry in which it operates has razor thin margins? What if that company's management has a track record of poor capital allocation decisions? Some businesses are just never worth owning.
Q: So what would you say to value investors who base decisions off style boxes?
A: Investor beware. I believe "value investing" is not formulaic and should not be bound by rigid style boxes. They went to great lengths to avoid prescribed, stringent standards and technical methods to ascribe value, and so do I. The most famous value investor perhaps ever, Warren Buffett, adheres to this philosophy too. If you plotted all of the publicly traded companies in Buffett's Berkshire Hathaway portfolio, the portfolio would not plot in the value style box. This is also true of a number of other famous value investors. My track record since inception is a product of keeping my own counsel on value—not letting others decide what it is or isn't.
Q: Do you have any mentors who shaped your perspective on investing?
A: Yes, I joined the firm in 2001, as an analyst with no formal investment experience. To that point I had spent my career working as an engineer and as a consultant. Yet, the head of the Global Equity team at the time, Bill Wilby, recognized something in me and hired me as an analyst on his global portfolio, then the largest strategy the team managed. I learned an enormous amount from Bill and the rest of the team about how to think broadly, and holistically, about the really big structural shifts taking place in the world. From there we drilled down to businesses which were advantaged and were attractively priced. That remains the basis of what I do today as a portfolio manager.
Q: Why should an investor be interested in a global equity portfolio?
A: Thirty years ago businesses aligned geographically for appropriate reasons—doing business overseas was more expensive, complicated and burdensome from a legal and regulatory standpoint. That just isn't true today and hasn't been true for some time. Businesses today operate in real time regardless of the time zone. You've got to be structured that way to be effective and competitive. When you analyze businesses for a living, seeing global as the appropriate starting point for an equity investment is just a given. It's the way the world actually works. Carving up a portfolio into geographic sleeves based on a corporate domicile simply isn't business or economic reality, and hasn't been for some time. Global is the right starting footprint and it makes sense to me that one would build from there.
Randall (Randy) Dishmon serves as portfolio manager of Oppenheimer Global Value Fund. His previous positions at OppenheimerFunds included serving as co-manager of Oppenheimer Global Opportunities Fund and Senior Research Analyst for Oppenheimer Global Fund. Prior to joining OppenheimerFunds, Randy served for two years as a management consultant with Booz Allen & Hamilton. He also served for four years as a manager with UtiliCorp United and for seven years as a Vice President/Division Chief with KCI Technologies. Randy holds a B.S. in engineering from North Carolina State University, an M.S. in engineering from The Johns Hopkins University and an M.B.A. from the University of Michigan.
- 1. Special Risks: Foreign investments may be volatile and involve additional expenses and special risks, including currency fluctuations, foreign taxes, regulatory and geopolitical risks. Emerging and developing market investments may be especially volatile. Eurozone investments may be subject to volatility and liquidity issues. Value investing involves the risk that undervalued securities may not appreciate as anticipated. Mid-sized company stock is typically more volatile than that of larger company stock. It may take a substantial period of time to realize a gain on an investment in a mid-sized company, if any gain is realized at all. Diversification does not guarantee profit or protect against loss.
- A. Daily net asset value and dollar change of the fund is as of the previous business day's closing. Fund net asset values are updated at approximately 7:00pm ET daily. ↩
Foreign investments may be volatile and involve additional expenses and special risks, including currency fluctuations, foreign taxes and geopolitical risks. Emerging and developing market investments may be especially volatile. Due to the recent global economic crisis that caused financial difficulties for many European Union countries, Eurozone investments may be subject to volatility and liquidity issues. Value investing involves the risk that undervalued securities may not appreciate as anticipated. Small and mid-sized company stock is typically more volatile than that of larger, more established businesses, as these stocks tend to be more sensitive to changes in earnings expectations. It may take a substantial period of time to realize a gain on an investment in a small or mid-sized company, if any gain is realized at all. Diversification does not guarantee profit or protect against loss.


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Rc.No.641,Dt.06.08.2016 - 70th year of Independence - 09.08.2016 to 23.08.2016 Freedom Fortnight - Instructions
Rc.No.641/Text Books-1/2016 Date:06-08-2016
Sub:- SE – 70th year of Independence on 15.08.2016 decided that the period from 09.08.2016 to 23.08.2016 should be declared as Azadi 70 – Yaad Karo Kurbani (Freedom Fortnight) – Reg.
Read: 1. Mail received from the PS to Prl.Secretary to Govt.(SE), A.P., Secretariat.
2. Govt.Memo No.319192/General/A1/2016, dt.04.08.2016.
&& && &&
The attention of the all the District Educational Officers in the State are invited to the references read above and informed that the Government in their Memo No. 319192/General/A1/2016, dt.04.08.2016 have requested to issue instructions to all schools including Private and Aided Schools to carry out as many activities and each School as possible, while ensuring that each Primary/Upper Primary / Elementary /Secondary Schools takes up at least one activity and each Higher Secondary School takes up at least two activities. In addition, the mass singing of the National Anthem at 11.00 AM on Tuesday, the 23rd August, 2016 should apply to all School Children and they are also like to cover the events of Freedom Movement of 1857 and the Independence Struggle, in celebrations. Further they are informed to celebrate the activities at school level from 9th to 23rd August 2016. Copy of suggested activities is herewith enclosed.
Click below link to download activities
Click below link to download activities

subset: commoncrawl


text:
Title: Grant, John Thomas
URL: http://www.johnthomasgrant.com
Description: My fans say it best: "John Thomas Grant does something magic to make each grave stone look unique and special. I wonder if the person under looks at his final place on earth and says someone does remember me. The photos do honor the deceased in a special memorial."
Date Submitted: 02/09/09
Listed / Last Time Edited: 02/10/09
Main Category: > Photographers by Names > G
Second Category (if any): G
Linkedin (if any): http://www.johnthomasgrant.com
Number of visitors we sent to this photo site: 514 time(s).


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MySQL team attends and speaks at the MOSC 2014 on September 24-25, 2014 in Kuala Lumpur, Malaysia. We are having a MySQL booth and above that our local colleague Ricky Setyawan has secured one 45 minutes talk scheduled for Wed, Sep 24 @2:15-3:00pm on the MySQL Web Reference Architecture.
We will also run two hours workshop on MySQL Fabric scheduled for Thursday, Sep 25 @2:30-4:30pm. If you are around do not forget to come to our booth and/or visit our MySQL session & workshop!


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Live on BTSport 1: Sun 15.00: Arsenal are 7/2 (Skybet) to beat Chelsea by one goal in the Community Shield.
It's almost ten years to the day since Chelsea last faced Arsenal in the Community Shield, a Didier Drogba double giving the Blues a 2-1 success that day, however, the Stamford Bridge outfit haven't fared too well in the annual curtain raiser since then, a penalty shootout triumph against Manchester United in 2009 their only victory in five attempts.
Nevertheless, Jose Mourinho's men make the short journey to Wembley on this occasion as slight favourites, BetVictor chalking the Blues up at 6/4 to edge out the Gunners in normal time and bet365 quoting Arsene Wenger's charges at 19/10.
Inevitably, there'll be money, at 12/5 via Stan James, for the pair to require penalties to decide a winner, betway mark 6/1 against a 1-1 scoreline and bet365 can expect interest in the generous 7/2 they quote about the two sides playing out a score draw across the 90 minutes.
In bet365's handicaps, Arsenal receive a goal start at 4/7 and that's worth considering for punters seeking a safe-looking option but anyone that recalls the Gunners' 3-0 hammering of Manchester City in last term's Community Shield clash might understandably be keen to back them without any artificial assistance.
Paddy Power's 10/1 for them to nick it 2-1 catches the eye for example, it's an enticing 7/2 courtesy of Skybet for the North Londoners to record a victory by a one-goal margin and William Hill rate Arsenal at 6/1 to come out on top despite going in on level terms at the interval.
In terms of goals, five of the last six renewals have produced three or more so bet365's 19/20 for this game to generate more than 2.5 isn't without appeal and Stan James price the Gunners at 11/10 to fire the first of those. More accurately, that opener is 7/1 (Winner.com) to be struck by Theo Walcott and it's 7/10 at BetVictor for both teams to find the net.
Recommended Bets:
Over 2.5 goals – 19/20 (bet365)
Arsenal to beat Chelsea by one – 7/2 (Skybet)
Compare all Community Shield odds and bet at the best price.


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In the News
Original journalism from the Center's OpenSecrets Blog
Ahead of Super Tuesday, outside spending — some of it dark — props up incumbents
February 29, 2016 | Super PACs and dark money groups have spent more than $1.9 million to boost the campaigns of congressional incumbents with primaries tomorrow — Super Tuesday, for folks just in from another planet. And even as voters prepare to go to the polls, the donors of some of that money remain undisclosed. Races in the Heart of Dixie and…
Democratic Lawmakers Lead the Way in Personal Contributions
September 5, 2014 | Of the many methods that members of Congress can use to help out their colleagues, their party or some other political cause, digging into their own pockets may not seem the most appealing — not when they can establish joint fundraising committees, contribute from their campaign committees, or create leadership PACs to share the wealth.…
Business Cash Rules in Alabama
November 6, 2013 | Business brought its money and muscle to bear, just as promised after the government shutdown, in the special primary election in Alabama. It worked.
Feel free to distribute or cite this material, but please credit the Center for Responsive Politics. For permission to reprint for commercial uses, such as textbooks, contact the Center.


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Our Pretties
I am a very outgoing, joyful, affectionate, optimist and dedicated woman. I don't have fear to any challenge. I am very passionate about the things I like. My goal is find a good man to share my life with, also I really like to do my best in every field of my life. I want to find my soul mate. I wish my family to be fine and I want my children get their goals and be happy.
I love outdoors activities, I like to go for a walk to the country side, I like nature and to breath the pure air or just watch a nice sunset... I like going to the cinema, theater, relaxing, listen to music. It is good to go out to eat with the family or friends, also to go for a coffee and have a nice chat with a friend. I like traveling. I like to know about new cultures and enjoy the beautiful landscapes around the world.
Need partner: 25 - 40 years old
The man of my life has to be positive, joyful, honest, sensitive, very affectionate, kind, very passionate. I am looking for a man who will be a real Man and will be ready to start a long term relationship. I want to find responsible man who will take our relationships seriously with the good and bad things, because life has not only pink color.


text: Logan Capital Management, Inc. associated Registered Representatives offer securities through National Securities Corporation, a registered broker dealer, Member FINRA / SIPC. Investment Advisory Services is offered through Logan Capital Management, Inc. which is independently owned and operated from National Securities Corporation. Check the background of this Firm and /or investment professional on FINRA's Broker Check.


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RCI High Top Driving Shoes, Blue, 8.0
Click image to enlarge
Please note the following about this product:
- This item is sold as a pair.
- This product is discontinued.
Reviews (9)
What's in the Box
This is garage sale priced because it has been discontinued.
No Warranty, No Returns on Garage Sale Items
These high top driving shoes offer the same features as shoes costing twice as much! Soft, flexible design is lined with Nomex III and has a high grade split leather upper and double hook and loop closure straps. The exclusive one-piece molded sole features no-slip traction design for precision heel-to-toe action. Also has a no-slip heel cap for added wear! Available in Black, Red, or Blue. Size 7-13, and in half sizes too!
SFI 3.3/5 Certified
Important: Race driver and pit shoes come in Men's sizes. For women, subtract 2 from your shoe size and order that in Men's. Example: Women's size 7, order Men's size 5.
The number at the end of the part number indicates the shoe size.
Example: -10 = size 10; -85 = size 8-1/2, etc.
ShoeSizeConversionChart (GIF)
SFI Specifications (GIF)
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Thought Bubbles
I can't believe the money my company is paying out this month for new comers!! My pay is great...but your pay could be DOUBLE what I get when you get started!! WOW!!!
June 6, 2012 at 10:26 AM
Whoot whoot...so I have been promoted again with my work at home business, I love being a stay at home Mommy and wife and a Senior Regional Sales Director with AmeriPlan!!!
April 28, 2012 at 6:58 PM
WHOOT WHOOT....THIS GIRL IS EXCITED...I just got my first promotion with my work at home business!!! :) So happy I found a LEGIT company that allows me to make the $$ I need to make in order to stay at home wth my boys!!
March 26, 2012 at 11:26 AM
extremecheer Awesome job March 26, 2012 at 11:30 AM
davisfamofjust4 Thank you :) March 26, 2012 at 11:33 AM
working from home, gotta love it! I play with my kids, and I can nap with my kids HA!! lol
March 12, 2012 at 9:06 PM
mrsrains What do you do? March 12, 2012 at 9:29 PM
davisfamofjust4 I just sent you a private message mrsrains :) March 12, 2012 at 9:36 PM
so my 19mth old got into a new box of hungry jack instant potatoes the other day...this is what I got to pick up...
March 6, 2012 at 1:16 PM
asianmyss That's a mess the dog cant eat =( March 6, 2012 at 1:25 PM
davisfamofjust4 tell me about it lol March 6, 2012 at 2:18 PM
So, I wanted to work all weekend if I could and get some serious networking done but the hubby said NO WORKING on Sunday...so yesterday was family day...I know I know I need to more family days that's the point of working at home LOL ;-)
March 5, 2012 at 6:29 PM
1-7 of 7 Thought Bubbles


text:
Visit the
LLM Criminal Justice and Criminal Law
page on the University of Leeds website for more details!
Criminal Law is always what I have wanted to focus on in my career as a Barrister. Since I first decided to go into the profession, I have wanted to study Criminal Law because I believe it offers the widest variety of interesting and challenging legal work – something which my studies and work experience have repeatedly confirmed. When deciding to study for a Masters Degree, I jumped at the chance to focus on Criminal Law and further develop my interest in this area.I love studying on my course and have found the work challenging but stimulating at the same time. My tutors have always been really supportive of my work and always strive to offer support or feedback when it is needed. I especially enjoy the Criminal Law module, as it is great to cover the new developments in the Law that have taken place in the few years since I last studied the subject. Being a Postgraduate, I am also encouraged to undertake a lot of my own research and I am very much looking forward to completing my dissertation on a topic that is of great interest to me.The learning facilities in the School of Law are first class! The new Liberty Building is a fantastic environment in which to study Law and get your degree and the facilities in the building are second-to-none. That said, even before we moved into the new building, the facilities provided by the were top notch. As a qualified Barrister, I became heavily involved with mooting and ended up judging many of the moots and a mock trial for the undergraduate students – it has been great to pass on the things I have learned to others, in order to help them on their way towards their future careers.I have had an amazing time studying in the School of Law and at the University of Leeds in general and would encourage everyone who is thinking about applying to definitely apply! Thanks to all the lecturers and support staff at Leeds who have made my time here so enjoyable and successful.
The School of Law is offering two scholarships of £2,000 for high-quality students studying postgraduate taught programmes in the School in 2015/16. The Professional Graduate Scholarship is not available to those registering via a School or University agreement.These scholarships will be awarded on the basis of academic merit.
The School of Law is offering six Liberty Scholarships of £3,000 to international students of high academic quality starting a postgraduate taught programme in 2015.These scholarships will be awarded on the basis of academic performance in your undergraduate degree; the final decision on the award of a Liberty Scholarship will be that of the appointed award panel. The Scholarships have been created to aid those students from countries and/or regions where lack of funding is the biggest barrier to obtaining higher education overseas. The Liberty Scholarship is not available to those registering via a School or University agreement.
University of Leeds
Find A Masters.
Copyright 2005-2017
All rights reserved.


text:
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Bayesian Statistics: Indian Buffet Process
- Lucas Patterson
- 2 years ago
- Views:
1 Bayesian Statistics: Indian Buffet Process Ilker Yildirim Department of Brain and Cognitive Sciences University of Rochester Rochester, NY August 2012 Reference: Most of the material in this note is taken from: Griffiths, T. L. & Ghahramani, Z. (2005). Infinite latent feature models and the Indian buffet process. Gatsby Unit Technical Report GCNU-TR Introduction A common goal of unsupervised learning is to discover the latent variables responsible for generating the observed properties of a set of objects. For example, factor analysis attempts to find a set of latent variables (or factors) that explain the correlations among the observed variables. A problem with factor analysis, however, is that the user has to specify the number of latent variables when using this technique. Should one use 5, 10, or 15 latent variables (or some other number)? There are at least two ways one can address this question. One way is by performing model selection. Another way is to use a Bayesian nonparametric method. In general, Bayesian nonparametric methods grow the number of parameters as the size and complexity of the data set grow. An important example of a Bayesian nonparametric method is the Indian Buffet Process. (Another important example is the Dirichlet Process Mixture Model; see the Computational Cognition Cheat Sheet on Dirichlet Processes.) An Indian buffet process (IBP) is a stochastic process that provides a probability distribution over equivalence classes of binary matrices of bounded rows and potentially infinite columns. Adoption of the IBP as a prior distribution in Bayesian modeling has led to successful Bayesian nonparametric models of human cognition including models of latent feature learning (Austerweil & Griffiths, 2009), causal induction (Wood, Griffiths, & Ghahramani, 2006), similarity judgements (Navarro & Griffiths, 2008), and the acquisition of multisensory representations (Yildirim & Jacobs, 2012). Two aspects of the Indian buffet process that it shares with other Bayesian nonparametric methods underlie its successful application in modeling human cognition. First, it defines a probability distribution over very rich, combinatoric structures. Indeed, depending on the goal of the modeler, one can interpret binary matrices as feature ownership tables, adjacency matrices representing graphs, or other complex, structured representations. Second, under IBP, binary matrices can grow or shrink with more data, effectively letting models adapt to the complexity of the observations. For example, a binary matrix is often thought of as a feature ownership matrix in which there is a row for each object, and a column for each possible feature. An entry of 1 at element (i, k) of the matrix means that object i posseses feature k. Otherwise this entry is 0. Importantly, the user does not need to specify the number of columns (that is, the number of features). Instead, the number of 1
2 columns can grow with the size and complexity of the data set. That is, a priori, IBP due to its stochastic process foundations has support over feature ownership matrices with any number of columns. Upon observing data, a posteriori, IBP concentrates its mass over a subset of binary matrices with finitely many columns via probabilistic inference (assuming the use of a finite data set). Because IBP lends itself to Bayesian inference, the posterior IBP will maintain the variability regarding the exact number of features arising from the observations, thereby solving (or at least alleviating) the difficult problems of model selection and model comparison. As stated above, IBP does not make assumptions about the exact number of latent features underlying a finite set of observed objects, although it does make other assumptions about these units (Griffiths & Ghahramani, 2005, 2006). It assumes that the latent features are binary. Thus, an object either does or does not possess a feature. It also assumes that latent features are statistically independent, meaning that knowledge that an object possesses one feature does not provide information about whether it possesses other features. Lastly, it assumes that the latent features are a finite subset of an unbounded or infinite set of features. More formally, the probability of a binary matrix Z under IBP can be written as the following: α K K p(z) = 2 N 1 h=1 K h! exp{ αh (N m k )!(m k 1)! N} (1) N! k=1 where N is the number of objects, K is the number of multisensory features, K h is the number of features with history h (the history of a feature is the matrix column for that feature interpreted as a binary number), H N is the N th harmonic number, m k is the number of objects with feature k, and α is a variable influencing the number of features (a derivation of this equation can be found in Griffiths & Ghahramani, 2005). We denote Z IBP(α), meaning that Z is distributed according to the IBP with parameter α. Below, we provide intuition for α, the only parameter of the process. 2. Constructing the Indian Buffet Process There are three well studied constructions for the Indian buffet process constructions based on an implicit representation, a finite representation, and an explicit stick-breaking representation. Here we mainly study the implicit representation before we briefly introduce the other two constructions. An implicit representation: In the field of Bayesian nonparametric models (and the study of stochastic processes, in general), implicit representations are a way of constructing models which exploit de Finetti s Theorem. If a sequence of observations, X 1,..., X n, are exchangeable (i.e., its probability distribution is invariant to permutations of the variables in the sequence), then by de Finetti s theorem there is a stochastic element (also known as the mixing distribution) that underlies these observations. For such cases, one can choose to work only with the observations, X i s, (e.g., in defining conditional distributions) and thereby address the underlying stochastic process implicitly. A well know example of such a representation is the Chinese Restaurant Process which implies the Dirichlet Process as 2
3 Figure 1: Simulations of the Indian buffet process with different α values. The binary matrices depict samples from the IBP with α = 1 resulting in a total of 3 dishes sampled (Left), with α = 3 resulting in 12 dishes sampled (Middle), and with α = 5 resulting in 18 dishes sampled (Right). In all simulations, the number of customers (i.e., the number of rows) was fixed to 15. White pixels are 1 and black pixels are 0. its mixing distribution (Aldous, 1985; also see the Computational Cognition Cheat Sheet on Dirichlet Processes.). Griffiths and Ghahramani (2005, 2006) introduced the following culinary metaphor that results in an IBP while keeping the mixing distribution implicit. In this metaphor, customers (observations) sequentially arrive at an Indian buffet (hence the name) with an apparently infinite number of dishes (features). The first customer arrives and samples the first Poisson(α) dishes, with α > 0 being the only parameter of the process. The i th customer samples one of the already sampled dished with probability proportional to the popularity of that dish prior to her arrival (that is, proportional to n i,k where n i i,k is the number of previous customers who sampled dish k). When she is done sampling dishes previously sampled, customer i further samples Poisson( α ) number of new dishes. This process continues until all N customers i visit the buffet. We can represent the outcome of this process in a binary matrix Z where the rows of the matrix are customers (observations) and the columns are dishes (features) (z i,k is 1 if observation i possesses feature k). The probability distribution over binary matrices induced by this process is indeed as expressed in Equation 1. To get a better intuition for the parameter α, we simulated samples from IBP with three different α values. As illustrated in Figure 1, the smaller the α, the smaller the number of features with i z i,k > 0. In other words, for equal number of observations, the parameter α influences how likely it is that multiple observations will share the same features. Based on this property of the process, α is called the concentration parameter (similar to the α parameter in Dirichlet Processes). Thibaux and Jordan (2007) showed that Beta processes are the underlying mixing distribution for IBP. (Similar to the relationship between the Chinese Restaurant Process and the Dirichlet Processes.) We do not provide details of this derivation here. However, we note that the availability of the underlying mixing distribution is advantageous in at least two ways: (1) one can devise new constructions (e.g., stick-breaking constructions) of the 3
4 same stochastic process which can lead to new and more efficient inference techniques; and (2) it can lead to derivations of more sophisticated models from the same family, such as hierarchical extensions of IBP. Finally, another way of constructing Bayesian nonparametric methods is by first defining a finite latent feature model, and then take the limit of this model as the number of latent features goes to infinity (see Griffiths & Ghahramani, 2005, 2006). Conditional distributions for Inference: We need to derive the prior conditional distributions to perform Gibbs sampling for the IBP. In doing so, we exploit the exchangeability of IBP. For non-singleton features (i.e., features possessed by at least one other observation), we imagine that the i th observation is the last observation, allowing us to write the conditional distribution in the following way: P (z ik = 1 z i,k ) = n i,k N where z i,k is the feature assignments for column k except for observation i, and n i,k is the number of observations that possesses feature k excluding observation i. 3. Infinite Linear-Gaussian Model Now that we have a prior over binary matrices, we put it in action by outlining a model of unsupervised latent feature learning. Here we consider a simple linear-gaussian model (Griffiths & Ghahramani, 2005, 2006). Model: An important goal of the model is to find a set of latent features, denoted Z, explaining a set of observations, denoted X. Let Z be a binary feature ownership matrix, where z i,k = 1 indicates that object i possesses feature k. Let X be real-valued observations (e.g., X i,j is the value of feature j for object i). The problem of inferring Z from X can be solved via Bayes rule: p(x Z) p(z) p(z X) = (3) Z p(x Z ) p(z ) where p(z) is the prior probability of the feature ownership matrix, and p(x Z) is the likelihood of the observed objects, given the features. We assign IBP as a prior over binary feature ownership matrices, P (Z), which is described above. We now describe the likelihood function. The likelihood function is based on a linear-gaussian model. Let z i be the feature values for object i, and let x i be the observed values for object i. Then x i is drawn from a Gaussian distribution whose mean is a linear function of the features, z i W, and whose covariance matrix equals σx 2 I, where W is a weight matrix (the weight matrix itself is drawn from zeromean Gaussian distribution with covariance σw 2 I). Given these assumptions, the likelihood for a feature matrix is: p(x Z, W, σ 2 X) = 1 1 exp{ (2πσX 2 )ND/2 2σ 2 X (2) tr((x ZW ) T (X ZW ))} (4) where D is the dimensionality of X, and tr( ) denotes the trace operator. A graphical model representation of the model can be found in Figure 2. 4
5 Figure 2: A graphical model for the infinite linear Gaussian model. Inference: Exact inference in the model is computationally intractable and, thus, approximate inference must be performed using Markov chain Monte Carlo (MCMC) sampling methods (Gelman et al., 1995; Gilks, Richardson, & Spiegelhalter, 1996). We describe the MCMC sampling algorithm of Griffiths and Ghahramani (2005). A Matlab implementation of this sampling algorithm can be found on the Computational Cognition Cheat Sheet website. This inference algorithm is a combination of Gibbs and Metropolis-Hastings (MH) steps. We take Gibbs steps when sampling the cells in the feature ownership matrix. For all i with n i,k > 0 (non-singleton features), the conditional distribution can be computed using Equation 4 (the likelihood) and Equation 2 (the prior). To sample the number of new features for observation i, we compute a truncated distribution for a limited number of proposals (e.g., letting the number of new features range from 0 up to 6) using Equation 4 (the likelihood) and the prior over new features, Poisson( α ). Then we sample the number N of new features for observation i from this truncated distribution (after normalizing it). We take Gibbs steps when sampling α. The hyper-prior over the α parameter is a vague Gamma distribution, α Gamma(1, 1). The resulting posterior conditional for α is still a Gamma distribution, α Z G(1 + K +, 1 + N i=1 H i) (Görur, Jaekel, & Rasmussen, 2006). We take MH steps when sampling σ X. Proposals are generated by perturbing the current value by ɛ Uniform( 0.05, 0.05). We compute the acceptance function by computing the likelihood (Equation 4) twice, once with the current value (the denominator of the acceptance function) and once with the proposed value (the nominator of the acceptance function). Simulations: We applied the model to a synthetic data set of 100 images, denoted X. Each image x i was a real-valued vector of length 6 6 = 36. Each image was a superposition of a subset of four base images. These base images corresponded to the rows of the weight matrix W. For each row of the binary feature matrix, z i, each entry was set to 1 with probability 0.5 and set to 0 otherwise. Then we generated each x i by adding white noise with variance σ 2 x = 0.5 to the linear combination of the weight matrix based on the binary feature matrix, z i W. Figure 3 illustrates this process: the four base images (top row), binary feature vectors for a subsample, and the resulting images from the data set (bottom row). 5
6 Figure 3: (Top row) Four basis images underlying the data set. These binary images of length 6 6 = 36 constitute each of the four rows of the weight matrix. (Bottom row) Binary vectors of length 4 at the titles are four rows from the feature matrix, Z. Present features are denoted 1. Corresponding images from the dataset are depicted. Each image is a linear combination of the present features and white noise Figure 4: (Left) The posterior distribution of the number of features based on the samples of the MCMC chain. (Right) The expected posterior weight matrix computed in the following way: E[W Z, X] = (Z T Z + σ2 X σ 2 A I) 1 Z T X. In our Gibbs sampler, we initialized α = 1, and initialized Z to a random draw from IBP(α). We ran our simulation for 1000 steps. We discarded the first 200 samples as burnin. We thinned the remaining 800 samples by retaining only every 10 th sample. Our results are based on this remaining 80 samples. (We ran many other chains initialized differently. Results reported were typical across all simulations.) Figure 4 illustrates the results. The left panel in Figure 4 illustrates the distribution of the number of latent features discovered by the model. Clearly, the model captured that there were 4 latent features underlying the observations. The four images on the right panel in Figure 4 illustrate the weights for the four most frequent features across the chain. Notice how remarkably close the latent features discovered by the model are to the weights used to generate the data in the first place (top row of Figure 3). Aldous, D. (1985). Exchangeability and related topics. In Saint-Flour, XIII 1983 (pp ). Berlin: Springer. École d été de probabilités de 6
7 Austerweil, J. L. & Griffiths, T. L. (2009). Analyzing human feature learning as nonparametric Bayesian inference. In D. Koller, Y. Bengio, D. Schuurmans, & L. Bottou (Eds.), Advances in Neural Information Processing Systems 21. Cambridge, MA: MIT Press. Gelman, A., Carlin, J. B., Stern. H. S., & Rubin, D. B. (1995). Bayesian Data Analysis. London: Chapman and Hall. Gilks, W. R., Richardson, S., & Spiegelhalter, D. J. (1996). Markov Chain Monte Carlo in Practice. London: Chapman and Hall. Görur, D., Jaekel, F., & Rasmussen, C. E. (2006). A choice model with infinitely many features. Proceedings of the International Conference on Machine Learning. Griffiths, T. L. & Ghahramani, Z. (2005). Infinite latent feature models and the Indian buffet process. Gatsby Unit Technical Report GCNU-TR Griffiths, T. L. & Ghahramani, Z. (2006). Infinite latent feature models and the Indian buffet process. In B. Schölkopf, J. Platt, & T. Hofmann (Eds.), Advances in Neural Information Processing Systems 18. Cambridge, MA: MIT Press. Navarro, D. J. & Griffiths, T. L. (2008). Latent features in similarity judgments: A nonparametric Bayesian approach. Neural Computation, 20, Thibaux, R. & Jordan, M. I. (2007). Hierarchical beta processes and the Indian buffet process. Proceedings of the Tenth Conference on Artificial Intelligence and Statistics (AISTATS). Wood, F., Griffiths, T. L., & Ghahramani, Z. (2006). A non-parametric Bayesian method for inferring hidden causes. Proceedings of the 2006 conference on Uncertainty in Artificial Intelligence. Yildirim, I. & Jacobs, R. A. (2012). A rational analysis of the acquisition of multisensory representations. Cognitive Science, 36,
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TEMPLE — Joanna Flores Staton decided to run for the open position of Bell County district clerk in the Republican Party's March 14 primary.
Staton, who has served as the District court's coordinator for the past 25 years, will make her announcement official Monday afternoon.
Her decision to delay her announcement until Monday means she is filing on the last day of the eligibility period and entering a crowded primary field.
When Staton makes her announcement at 3 p.m. in the Commissioners Courtroom in the Bell County Historic Courthouse, 101 E. Central Ave., in Belton, she will be joining local attorney Susan Parker and current chief deputy of the district clerk's office, Jeannie Guthrie, in the race.
Parker and Guthrie, like the majority of Republican candidates, made their official announcements at a Nov. 12 filing event. The decision to file early gave them nearly a monthlong head start in fundraising and campaigning.
Staton said she put off her announcement until the last day because she wasn't sure it was the right time.
"People talked to me and convinced me," Staton said. "I realized that this is the perfect opportunity for me."
When asked about her qualifications for the position of district clerk, Staton said that, as court coordinator, she has come to know the courthouse and the attorneys and that she "enjoys the work."
Declining to give more details, Staton said she will elaborate more on her candidacy Monday.
Nancy Boston, Bell County Republican Party chairwoman, said Staton's is the only outstanding announcement she is aware of, but she is accepting papers from interested candidates.
"The filing deadline is Monday at 6 p.m.," Boston said. "I'll be in the party headquarters in Belton from 3 to 6 p.m. Monday if anyone still wants to file."
Bell County Democrats did not respond to requests for comment by press time.


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We spent one night here at the end of our travels in India. It is absolutely fine for the price and is quite grand, the rooms are fine and the service is good. Swimming pool is nice and the staff are attentive. The buffet for dinner was varied and tasty.
- Official Description (provided by the hotel):
- Hotel The Royal Plaza is one of the best luxury boutique hotels in delhi. Superbly located in the heart of city downtown- Connaught Place. The Hotel is minutes away from International Trade Fair Grounds, President House , India Gate, Parliament House. The Hotel is very close to New Delhi Railway Station.Its prime location in the heart of city has made it a commercial and shopping hub for both domestic and international travellers.With three restaurants , bar and night club The Royal Plaza provides excellent dining to suit any palate , in an elegant and inviting ambience.Royal Plaza also has an extensive Health Club and Spa -offering wellness menu with signature treatments and therapies to choose from and a temperature controlled & a eco friendly swimming pool ... more less
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Pack Pride takes a look at some of the highs and lows, jewels and sleepers of the class of 2007. During a year of transition, new head coach Tom O'Brien managed to hold together much of the class assembled before him and added a few of his own priorities to this year's recruiting class.
Biggest recruiting battle won... OL Desmond Roberts...The Pack knew from the start that they'd have a battle on their hands to land Roberts. He earned an early offer from South Carolina which was followed quickly by scholarship pledges from UNC and NC State. In the Pack's favor from the beginning was Robert's familiarity with the Wolfpack and his hopes of majoring in Engineering. He camped with NC State three years in a row and had become quite fond of former OL coach Mike Barry. When Barry left for the NFL it opened the door somewhat for other schools. UNC and Virginia Tech became the Pack's biggest threats over last summer but an unofficial visit from Roberts and his mother all but solidified him for the Pack and he made his commitment to State official on August 8th.
That would become just the first chapter in the effort to land Roberts in Raleigh, however. When NC State fired head coach Chuck Amato in November, Robert's commitment was thrown into question. He never officially de-committed and much of the credit for that was due to early connections made by new head coach Tom O'Brien.
State hosted Roberts on an official visit in early January and probably hoped to solidify his commitment so that he would cancel any future trips. However, he stayed true to his word with the coaches at Virginia Tech and Penn State and made official visits with both.
The Hokies, in particular, put on the full court press and probably had the best shot of any school to change Robert's mind. They landed his final visit but after a couple of days of mulling his future, Roberts decided to stick with his original commitment. On January 30th, he solidified his pledge to the Pack.
One that got away...QB Matt Simms...From Don Bosco Prep in Ramsey, NJ, Simms appeared to have recruiting behind him when he committed to Louisville last August. He had quite a bit of familiarity with Boston College from camping at BC for two summer but, interestingly, didn't list the Eagles as one of his top schools upon committing to Louisville.
Everything stayed status quo for Simms until Louisville head coach Bobby Petrino bolted for the NFL in January- thrusting the US Army All-American's future into question.
Because of his knowledge of Simms through BC's camp, newly hired Wolfpack head coach Tom O'Brien threw his hat into the ring and landed an official visit with Simms in late January.
Simms and O'Brien were shown together on national TV and all indications were the talented QB had a great visit in Raleigh. Just days before he would make his final decision, most insiders felt the Pack had emerged as the team to beat.
However, Simms pulled a mild shocker when he re-committed to Louisville during a phone call with new head coach Steve Kragthorpe.
Curiosity factor...LB Audie Cole...At 6-5, 215 pounds, Cole certainly doesn't seem to fit the mold of your average linebacker. In fact, when making a quick scan of the Boston College roster, the vast majority of Eagles' 'backers are 6-2 and shorter. So obviously, head coach Tom O'Brien and TE coach Jim Bridge saw some particular attributes that led them to project this high school star quarterback onto to the defensive side of the ball.
One reason may have been Cole's speed. He has been timed under 4-7 seconds in the 40-yard dash and was known to be a much more effective runner than passer while leading his Monroe (MI) squad.
Cole also spent time working at safety as a senior and actually earned all-league honors for his work on defense. Obviously, the ability to play in coverage shows that Cole has the talents to work in space.
Perhaps the factor most in his favor to succeed at linebacker is his reputation for being a tough, hard-nosed player that was known for being a load to tackle. He's also a wrestler which should serve him well when going head to head against some of the nation's best running backs in the ACC.
Jewel of the class...TE George Bryan...He may not have earned lofty recruiting rankings but Bryan, from New Hanover High School in Wilmington, NC was a major get for the Wolfpack early last year. Word from State's camp was that Bryan was one of the top five in-state players on their board. He also earned offers from every school that received his film.
When watching Bryan flexed out on offense at receiver, you quickly forget this is a player weighing in at 260 pounds. He runs fluidly and has very good flexibility given his size. Bryan has tremendous hands and does a great job of catching the ball in traffic.
At the Shrine Bowl held last December, Bryan didn't get a chance to catch any passes but he proved to be a formidable and impressive blocker. He more than held his own when going up against some of South Carolina's best defensive linemen.
While some have projected Bryan as an offensive tackle, he will begin his career as a tight end at NC State and given the Pack's depth concerns, could factor onto the depth chart quite early in his career.
Bryan chose NC State over scholarship offers from UNC, South Carolina, Clemson and East Carolina.
(Past winners- Andre Brown, TA McLendon, Mario Williams, DeMario Pressley)
Sleeper of the class...RB Curtis Underwood...Locally, Curtis Underwood was known as an all-world running back that could single-handedly take over a game. On a national level, Underwood barely scraped out a two-star ranking from Scout.com. While Underwood was barely a blip on the recruiting radar outside of New York, that probably sat just fine with Wolfpack head coach Tom O'Brien.
Underwood had an official visit planned with Boston College before O'Brien made the transition to NC State and the Pack's new head coach wasted no time in getting western New York's top player to Raleigh.
Within hours after completing his official visit to NC State, Underwood had pulled the trigger on a commitment to the Pack.
With rising junior running backs Toney Baker and Andre Brown on the depth chart, there will be little pressure on Underwood which should give him ample time to mature and grow into the Wolfpack system. But make no mistake, this is a talented player.
At 6-0, 210 pounds, Underwood has been timed as low as 4.44-seconds in the 40-yard dash. He rushed for better than 2,000 yards as a senior displaying an impressive combination of power, speed and shiftiness. Underwood has deceptive speed that causes opposing defenders to take bad angles. He has tremendous leg drive and strives to gain every available yard.
Perhaps the most promising aspect of Underwood's arrival in Raleigh is the fact that there will be no need to rush him into the running back mix. Barring any unforeseen injuries, offensive coordinator Dana Bible and running back's coach Jason Swepson should be able to ease their newest back into the Wolfpack system.
(Past winners- Manny Lawson, Jamesly Jean, Jeremy Gray, Matt Kushner)
Recruiter of the year...Head coach Tom O'Brien...With only about three full weeks to get out on the road and meet with recruits and an incomplete staff with which to work, O'Brien's results were stellar given the circumstances.
He focused on solidifying the previous commitments and managed to secure them all minus Linwan Euwell and Jonathan Hannah.
Rather than target uncommited prospects he was unfamiliar with, O'Brien chose, instead, to go after players he had recruited while at Boston College. Of the 10 uncommitted players that ultimately made official visits to NC State during the month of January, O'Brien landed eight of them- missing only on QB Matt Simms (Louisville) and OL Arthur Ray (Michigan State).
O'Brien's ability to bridge the gap between the old staff and the arrival of his new crew of assistants proved critical in allowing State to put together a respectable signing day class last Wednesday.
(Past winners- entire Pack staff, Joe Pate, Curt Cignetti, Doc Holliday)


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There is a popular regime known as The Miracle Morning which encourages individuals to establish a morning routine that would result in a more productive day. When I had first read about it a year ago, I loved the concept and even decided to take it for a spin by starting my morning off with the the recommended S.A.V.E.R.S (silence, affirmations, visualization, exercise, read, scribe) Although I'm a firm believer in a morning routine, I had found it difficult incorporating steps that I didn't feel would have an impact on the remainder of my day. And, I have to admit, I felt a bit silly reciting how great my day was going to be or how awesome I'm going to be at work – lol! But that's just me. I realized I was more comfortable with a routine that consisted of steps I designed which fell in line with my plan for mindful living as well as my personal and professional schedule.
Although morning-time is the launch site for my day's journey, I knew I wouldn't be able to cram in what I aspire to accomplish before leaving for the office at 7:30 a.m. So rather than follow an established 'miracle morning', I reflected upon what I needed to have a Meaningful Day.


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Colles' Fracture
A Colle's fracture is a break in the distal part of the radius bone. The radius is one of the bones of the forearm. The distal end of the bone is considered part of the wrist. Distal radius fractures are categorized by type:
- Open fracture—a broken bone that breaks through the skin
- Comminuted fracture—a bone that breaks into more than two pieces
- Intra-articular fracture—a broken bone within a joint
- Extra-articular fracture—a broken bone that does not involve the joint
|Intra-articular Colle's Fracture
|Copyright © Nucleus Medical Media, Inc.
This sheet focuses on fracture of the distal radius. Fractures of other wrist bones can be found on a separate sheet.
A distal radius fracture can be caused by:
- A fall on an outstretched hand
- A direct blow to the wrist
Risk Factors
Factors that can increase your risk of breaking your radius bone include:
- Severe trauma:
- Osteoporosis
- Poor nutrition
Conditions that increase the risk of falling include:
- Snow
- Ice
- Loss of agility or muscle strength
- Certain sports
- Increased age
- Postmenopause
- Decreased muscle mass
Symptoms may include:
- Arm or wrist pain
- Bruising
- Swelling
- Tenderness
- Severe pain with movement
- Trouble moving your wrist or arm
- Wrist appears out of line
You will be asked about your symptoms and medical history. A physical exam will be done.
Images will usually be taken of your wrist or arm. This can be done with an x-ray .
After you are diagnosed, you may be referred to a specialist. An orthopedist focuses on bones.
It takes 6-10 weeks for a fracture of the radius at the wrist to heal. The type of treatment you receive depends on where your bone is broken and how serious the break is.
Some fractures require a reduction. This means the doctor realigns the bones before healing begins. Reductions can be done by the doctor putting your bone fragments into position by moving your arm or through surgery.
Your doctor may choose to treat the fracture using a cast. Your cast may be removed after a few weeks and replaced if it loosens. Most casts are removed at about six weeks.
In other cases, a splint or a soft bandage may be used instead of a cast. Talk with your doctor about the best plan for you.
Your doctor may prescribe a pain medication or suggest an over-the-counter pain reliever.
A distal radius fracture sometimes requires surgery. The surgeon first realigns the bones during an operation. Then, any of the following may be used to hold the bones together as they heal:
- A plate and screws
- Pins
- An external device that holds the inside pins together
You may be given a splint to wear after surgery to keep your arm from moving too much.
Physical Therapy
You may be referred to a physical therapist. Exercises will help you regain range of motion and strength.
To help reduce your chance of fracturing your radius bone:
- Consider wearing a wrist guard when you play sports that put you at risk, such as in-line skating.
- Keep your muscles strong to prevent falls.
- Michael Woods, MD
- Reviewed: 09/2016
- Updated: 09/23/2014
Please note, not all procedures included in this resource library are available at Henry Ford Allegiance Health or performed by Henry Ford Allegiance Health physicians.
All EBSCO Publishing proprietary, consumer health and medical information found on this site is accredited by URAC. URAC's Health Web Site Accreditation Program requires compliance with 53 rigorous standards of quality and accountability, verified by independent audits. To send comments or feedback to our Editorial Team regarding the content please email us at email@example.com.
This content is reviewed regularly and is updated when new and relevant evidence is made available. This information is neither intended nor implied to be a substitute for professional medical advice. Always seek the advice of your physician or other qualified health provider prior to starting any new treatment or with questions regarding a medical condition.
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Popular Now
Popular Now
Popular Now
Popular Now
01803 865913
+44 1803 865913
By: Michael Zeilik(Author)
64 pages, illustrations
This student supplement to Astronomy: The Evolving Universe provides thirty two hands-on activities for students of astronomy. These are highly focused on central concepts in astronomy, and each activity is linked to a section of the main text. The activities are designed to take 30 or 40 minutes of class time, and most require no special materials or extra resources. Fully class tested, these activities form a key part of the innovative teaching strategies developed by the author.
"This book is easy to read and is a good introduction to popular astronomy."
- Astronomy Now
Foreword for the student
1. Angular size and distance (cosmic distances)
2. Angular speed and motion (heavenly motions)
3. Major motions of the planets (heavenly motions)
4. Retrograde motion of Mars (heavenly motions)
5. Sunrise points (heavenly motions)
6. Solar system models (scientific models)
7. Kepler's third law (heavenly motions)
8. Pluto and Charon (heavenly motions)
9. The Doppler shift
10. Weight
11. Newton's Gravitation
12. Continuous spectra (light & spectra)
13. Stellar temperatures, colors and spectra (light & spectra)
14. Stellar parallax
15. Classifying stars by the H-R diagram (light & spectra)
16. Stellar evolution (scientific models)
17. Cepheid variable stars (cosmic distances)
18. The sun's distance from the galactic center (cosmic distances)
19. Rotation curve of a spiral galaxy (heavenly motions)
20. Hubble's law (cosmic distances)
21. Cosmic background radiation (light & spectra)
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WASHINGTON -- Roger Clemens' wife took the stand in her husband's perjury trial late Thursday afternoon, but the bulk of her testimony will take place Friday morning.
Clemens is charged with lying to Congress in 2008 when he said he never took performance-enhancing drugs. His former strength coach, Brian McNamee, said he injected Clemens with steroids in 1998, 2000 and 2001 and HGH in 2000.
Clemens' wife, Debbie, is expected to testify that she received an HGH injection from McNamee in 2000. Debbie Clemens took the stand at the end of the day Thursday, but didn't get through much of her testimony. She only gave general background information about her family and relationship with Clemens.
The defense expects to rest its case Friday.
Prior to Debbie Clemens taking the stand, Clemens' lawyers continued to attack the credibility of his chief accuser Thursday.
The defense is trying to portray McNamee as an untrustworthy man who's changed his story about injecting the pitcher with performance-enhancing drugs multiple times.
McNamee's estranged wife testified for the defense, contradicting much of McNamee's testimony regarding why/when he stored medical waste.
Later Thursday, the defense called two DLA Piper lawyers, colleagues of Senator George Mitchell when he was working on the Mitchell Report in 2007.
Bret Ingerman read aloud from a DLA Piper memo dated July 13, 2007. The memo summarized information from a group interrogation of McNamee four days before. Ingerman said McNamee spoke to him, Mitchell, two partners at DLA Piper, McNamee's lawyer and FBI investigators.
McNamee told them he injected Clemens four to six times in 2000 "after explaining to Clemens the good, bad and ugly" of HGH, according to the memo.
McNamee said he kept the PEDs at his house, according to the notes, which contradicts McNamee's testimony in this trial. He told the jury that Clemens kept the PEDs at his place.
McNamee also said that he believed Clemens' trust in him went down after McNamee was investigated in relation to a sexual assault case in Florida in October 2001.
Earlier in the trial, McNamee complained that he had issues with the way Clemens compensated him for his work. According to the DLA Piper memo, McNamee claimed he was always ahead financially with Clemens. He also said Clemens never gave money to Mr. McNamee specifically to buy PEDs.
Another DLA Piper attorney, Ellen Ginsberg, testified about a follow-up conversation with McNamee in October 2007. Ginsberg said McNamee told Mitchell in October 2007 that he injected Clemens four times during the 1998 season.
Ginsberg also said that during the conversation, McNamee said Clemens' trust in him did not go down after the sexual assault incident, contradicting his July comments. McNamee was corrected.
Clemens is charged with lying to Congress in 2008 when he said he never took performance-enhancing drugs. McNamee said he injected Clemens with steroids in 1998, 2000 and 2001 and HGH in 2000.
Daily Pitch is a baseball fan's destination for breaking news, emerging trends and enlightening banter. With a veteran group of reporters positioned in three time zones, we provide a balanced, comprehensive glimpse at our national pastime, with a nod to both the passion and complexities that make the sport irresistible to many. More about our reporters


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What is JotForm?
JotForm is a free online form builder which helps you create online forms without writing a single line of code. No sign-up required.
At JotForm, we want to make sure that you're getting the online form builder help that you need. Our friendly customer support team is available 24/7.
We believe that if one user has a question, there could be more users who may have the same question. This is why many of our support forum threads are public and available to be searched and viewed. If you'd like help immediately, feel free to search for a similar question, or submit your question or concern.
How do I line up my product options horizontally on mobile views?Asked by BostonGalleryWrap on October 07, 2016 at 04:28 PM
Hi Support Peeps
They line up horizontally on the desktop version of my form but not on the mobile version.
This makes the form unattractive and very long because the variants are stacked on top of one another.
I have "Make Form Responsive" checked in the Designer but that doesn't help.
Many people will be ordering from their mobile phones so it's important to me that they have a good visual experience.
Also, it would be nice if I could center the products on the desktop version. Seems I only have control over the label.
Any help you can give me is appreciated.
I've included a link to my form.
Brian Smith
Boston Gallery Wrap
JotForm Support
Please inject the following code in your form: https://www.jotform.com/help/117-How-to-Inject-Custom-CSS-Codes
@media only screen and (max-width: 480px) {
.form-sub-label-container {
margin: 0px !important;
width: 105px !important;
.form-product-item {
width: 100% !important;
Let us know if you need more help, we will be glad to assist you.


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Shiro Ozaki
BiographyNishio, Aichi Prefecture, Japan
Shiro Ozaki was born on February 5, 1898 in Nishio, Aichi Prefecture, Japan. He was a writer and actor, known for Jinsei gekijo (1983), Fusetsu 20 nen (1951) and Jinsei gekijo: hisha kaku (1963). He died on February 19, 1964 in Japan. Read more... <


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Price: $
The phrase "Rochester institution" totally applies to LDR Char Pit, a favorite spot for many hungry locals since 1945 and one that's justifiably renowned for its steak sandwich. You can also chow down on house-ground burgers, Zweigle's hot dogs, plates, hot and cold sandwiches, and fish fry on Fridays. Breakfast, however, is served all day, every day.
Payment Type: cash only


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GoT Wine Reds Case
Your GoT Wine Reds Case includes two bottles each of
Black Fox Cellars Cabernet Sauvignon
Complex Cabernet Sauvignon is the most popular red wine. Black Fox's take on this iconic red boasts flavors of raspberry and cherry, with hints of cassis and cedar, and it won the Silver Medal in the San Francisco Chronicle Wine Competition 2016. Each sip dances on your tongue with vibrant tannins, light mouth feel, and a finish that doesn't linger too long. Its full-bodied flavor pairs wonderfully with umami, savory, high-fat foods. In other words, keep Black Fox Cab on hand to class up a mushroom cheeseburger or grilled steak.
Geja's Big Bold Red
As the name says, this feisty wine is big on bold, ripe flavor. Geja's Big Bold Red is fresh and forward, with prominent, aggressive tannins and balanced acidity. If you haven't already tried this multiple award-winner, there's no better time than now. This is one wine you can enjoy every day of the week. Silver Medal (87 points), Critics Challenge Wine Competition; Bronze, West Coast Wine Competition.
Granite Ridge Pinotage
Since the 1920s, vintners have been honing Pinotage, a genetic hybrid of Pinot Noir and Hermitage (or Cinsault) grapes that yields a truly unique light red wine. South Africa's Winery of Good Hope has perfected the hybrid, with a Pinotage that brings out the aspects of both grapes. In addition to the notes of cherry from the Pinot Noir, and the spiciness from the Hermitage, you'll enjoy a nice juicy palate with balance, length, and a bit of spice, especially if you drink it slightly chilled.
Treehaven Lane Petite Sirah
Petite Sirah is a spicy, medium-bodied red that is beloved for its beautiful, deep color. Treehaven's take on this fan-favorite offers aromas of raspberry and strawberry, leading to powerful flavors of crushed red berry fruit and plum jam. This rare grape is of French origin, but is now mainly grown in California, and takes up less than 10,000 planted acres around the world. A great combination for grilled meats, cold cuts, and strong cheeses, Treehaven Petite Sirah is a wine that is sure to get people talking at your next dinner party.
River's End Reserve Merlot
This wonderful red is the versatile bottle you want on your shelf to go with almost anything you cook, especially grilled fowl, braised red meats, and rich tomato sauces. Note the ripe berry flavors and aromas, and the nice touch of oak.
Maison Gourmand Vin Rouge
For most wine lovers, being able to drink great French wine on a daily basis is beyond our grasp. We present a solution: Vin Rouge, the captivating and delightful French table wine. You get the character of French terroir for a fraction of the price. Maison Gourmand Vin Rouge has soft flavors of black cherry and raspberry that mingle brilliantly a savory note of leather. It made us smile. We hope it does the same for you.