ScienceDaily (Nov. 1, 2012) ? Tendon injuries affect athletic horses at all levels. Researchers from the University of Connecticut are studying the use of stem cells in treating equine tendon injuries. Their findings were published Oct. 16 in the Journal of Animal Science Papers in Press.
Tendon injuries in horses tend to worsen over time as damage to the tendon creates lesions. Currently, horse owners treat tendon injuries by resting the horse and then carefully exercising the horse to control the growth of scar tissue in the tendon. Unfortunately, this treatment does not always work.
"These injuries result in lameness, which requires substantial recovery time and carry a high risk of re-injury," write authors S.A. Reed and E.R. Leahy.
Stem cells injections are already common veterinary medicine, and scientists are curious how to make stem cell treatments more effective. In this paper, the authors looked at the use of three types of stem cells: bone marrow-derived mesenchymal stem cells, adipose-derived stem cells and umbilical cord blood-derived stem cells.
These types of cells have the potential to strengthen a tendon after injury. Implants of bone marrow-derived mesenchymal stem cells (BMSC) can increase collagen production and organized collagen fibers in the tendon. Adipose-derived stem cells can express certain proteins important in healing.
However, stem cells are not a miracle cure. Implantation can be tricky, and stem cells do not always decrease recovery time. Some BMSC transplantations have also led to the growth of unwanted bone in the tendon.
Umbilical cord blood-derived stem cells (UCB) may have the most potential for healing horse injuries in the future. These cells may be better able to grow into new types of cells and repair tendon damage. So far there have been no studies of UCB use in actual horse tendon injuries. But in vitro studies show that UCB could be capable of tendon regeneration.
The authors recommend future studies into implantation techniques and the role of stem cells in different parts of the tendon. With this knowledge, horse owners, veterinarians and animal scientists can help keep equine athletes healthy.
Share this story on Facebook, Twitter, and Google:
Other social bookmarking and sharing tools:
Story Source:
The above story is reprinted from materials provided by American Society of Animal Science, via EurekAlert!, a service of AAAS.
Note: Materials may be edited for content and length. For further information, please contact the source cited above.
Journal Reference:
S. A. Reed, E. R. Leahy. Stem cell therapy in equine tendon injury. Journal of Animal Science, 2012; DOI: 10.2527/jas.2012-5736
Note: If no author is given, the source is cited instead.
Disclaimer: Views expressed in this article do not necessarily reflect those of ScienceDaily or its staff.
New York City Mayor Michael Bloomberg, center, gives a thumbs up after ringing in the opening bell at the New York Stock Exchange in New York, Wednesday, Oct. 31, 2012. Traffic is snarled, subways out of commission, streets flooded and power out in many parts of the city, but the New York Stock Exchange opened without hitch Wednesday after an historic two-day shutdown, courtesy of Superstrom Sandy. (AP Photo/Seth Wenig)
New York City Mayor Michael Bloomberg, center, gives a thumbs up after ringing in the opening bell at the New York Stock Exchange in New York, Wednesday, Oct. 31, 2012. Traffic is snarled, subways out of commission, streets flooded and power out in many parts of the city, but the New York Stock Exchange opened without hitch Wednesday after an historic two-day shutdown, courtesy of Superstrom Sandy. (AP Photo/Seth Wenig)
Traders work on the floor at the New York Stock Exchange in New York, Wednesday, Oct. 31, 2012.Traffic is snarled, subways out of commission, streets flooded and power out in many parts of the city, but the New York Stock Exchange opened without hitch Wednesday after an historic two-day shutdown, courtesy of Supertorm Sandy. (AP Photo/Seth Wenig)
Water gushes from a hose as it is pumped out of a basement in New York's financial district, Wednesday, Oct. 31, 2012. Much of lower Manhattan and the financial district are still without electrical power. The Federal Reserve Bank of New York is background center. (AP Photo/Mark Lennihan)
MUMBAI, India (AP) ? Asian stock markets were mixed Thursday, with investors buoyed by solid manufacturing data out of China but wary of weak global demand for electronics after Panasonic Corp. forecast a massive loss.
Two manufacturing surveys in China, released Thursday, showed improvement for the month of October, adding to signs that the world's second largest economy may be recovering from its worst slump since the 2008 global recession.
The state-sanctioned China Federation of Logistics and Purchasing's monthly purchasing managers index improved to 50.2 from September's 49.8 on a 100-point scale, indicating expansion. Separately, HSBC Corp. said its own PMI improved to an eight-month high of 49.5 from September's 47.9, though it still showed activity contracting.
That gave momentum to stocks in the region. China's Shanghai Composite index led gains, rising 1.8 percent, to 2,105.60. Hong Kong's Hang Seng index rose 0.6 percent, to 21,772.60. Stocks in Taiwan also gained.
Gains in Japan were tempered by Panasonic's warning Wednesday that it would post a $9.6 billion loss for the fiscal year through March, among the biggest in Japan's manufacturing history and far more than expected.
"People are worried you'll see further downgrades from Sony and Sharp," said Andrew Sullivan, principal sales trader at Piper Jaffray in Hong Kong. He said investors were also underwhelmed by the Bank of Japan's Tuesday stimulus announcement, a bond-buying program designed to boost growth and combat deflation.
"There's still concern after the Bank of Japan didn't do as much as the market had hoped for," he said. "Is the government really prepared to act decisively?"
Japan's Nikkei 225 index reversed early losses to gain 0.1 percent, to 8,934.94. Panasonic plunged over 19 percent. South Korea's Kospi was down 0.58 percent at 1,901.05. Indices in India, New Zealand, Thailand, Singapore and Indonesia retreated.
The New York Stock Exchange was closed Monday and Tuesday, and the city that is the world's financial center struggled to get back to work after a huge storm slammed into the U.S. East Coast. The trading floor reopened Wednesday but had to run on backup generators because of a power outage in lower Manhattan. Volumes were thin with many people still unable to get to work due to transportation disruptions and power outages.
By the end of the day, stocks had barely budged, with the Dow Jones industrial average and the S&P 500 each moving less than a tenth of percentage point.
Investors will be keeping an eye out for signs of the cost of the storm damage as well as a raft of U.S. economic news to be released over the next few days, culminating in a comprehensive jobs report for October at the end of the week.
Benchmark oil for December delivery rose 8 cents to $86.32 per barrel in electronic trading on the New York Mercantile Exchange. The contract rose 56 cents to finish at $86.24 per barrel in New York on Wednesday.
In currencies, the euro retreated slightly to $1.2959 from $1.2962 late Wednesday in New York. The dollar rose to 80.03 yen from 79.76 yen.
Here at Cabrillo, we often talk about the energy-saving benefits of installing a programmable thermostat. But with so many kinds of thermostats on the market, how are you supposed to figure out which one is right for you? Today we?re going to highlight some the most important programmable thermostat features that you should look for when you?re deciding on which model to choose.
How much customization are you looking for?
One of the most important things you should think about when you?re comparing the features of different programmable thermostats is how much customization you want. Here is a breakdown of the different types of models based on how many days you can differentiate settings for:
5-2 model. This type of programmable thermostat allows you to have one set of settings for weekdays and another for weekends. If your family?s schedule is consistent on most weekdays and weekends, this option could be perfect for you.
5-1-1 model. Along with a set of settings for weekdays, 5-1-1 models allow you to have separate settings for both Saturday and Sunday as well. If your family?s weekend schedule is a little more unpredictable, or if you consistently have different Saturday and Sunday schedules, this might be the right fit.
7-day model. 7-day programmable thermostats give you the most control over your home?s thermostat settings because they allow you to have separate settings for every day of the week. These are good for families with abnormal work or school schedules, but they are also useful during the summer when many families have different schedules from day-to-day.
Other programmable thermostat features
Along with different customization capabilities, here are a few other features you can look for in your new programmable thermostat:
Touch screens
Backlit displays
Reminders to change your air filter
Vacation features
Smart recovery capabilities (thermostat begins heat-up or cool-down process early in order to meet the next temperature setting in time)
If you have any questions about programmable thermostat features, or if you?d like a heating and cooling system serviced or installed in your home, your Bay Area plumbing, heating and cooling company.
Predicting what topics will trend on TwitterPublic release date: 1-Nov-2012 [ | E-mail | Share ]
Contact: Caroline McCall cmccall5@mit.edu Massachusetts Institute of Technology
A new algorithm predicts which Twitter topics will trend hours in advance and offers a new technique for analyzing data that fluctuate over time
CAMBRIDGE, Mass. -- Twitter's home page features a regularly updated list of topics that are "trending," meaning that tweets about them have suddenly exploded in volume. A position on the list is highly coveted as a source of free publicity, but the selection of topics is automatic, based on a proprietary algorithm that factors in both the number of tweets and recent increases in that number.
At the Interdisciplinary Workshop on Information and Decision in Social Networks at MIT in November, Associate Professor Devavrat Shah and his student, Stanislav Nikolov, will present a new algorithm that can, with 95 percent accuracy, predict which topics will trend an average of an hour and a half before Twitter's algorithm puts them on the list and sometimes as much as four or five hours before.
The algorithm could be of great interest to Twitter, which could charge a premium for ads linked to popular topics, but it also represents a new approach to statistical analysis that could, in theory, apply to any quantity that varies over time: the duration of a bus ride, ticket sales for films, maybe even stock prices.
Like all machine-learning algorithms, Shah and Nikolov's needs to be "trained": it combs through data in a sample set in this case, data about topics that previously did and did not trend and tries to find meaningful patterns. What distinguishes it is that it's nonparametric, meaning that it makes no assumptions about the shape of patterns.
Let the data decide
In the standard approach to machine learning, Shah explains, researchers would posit a "model" a general hypothesis about the shape of the pattern whose specifics need to be inferred. "You'd say, 'Series of trending things remain small for some time and then there is a step,'" says Shah, the Jamieson Career Development Associate Professor in the Department of Electrical Engineering and Computer Science. "This is a very simplistic model. Now, based on the data, you try to train for when the jump happens, and how much of a jump happens.
"The problem with this is, I don't know that things that trend have a step function," Shah explains. "There are a thousand things that could happen." So instead, he says, he and Nikolov "just let the data decide."
In particular, their algorithm compares changes over time in the number of tweets about each new topic to the changes over time of every sample in the training set. Samples whose statistics resemble those of the new topic are given more weight in predicting whether the new topic will trend or not. In effect, Shah explains, each sample "votes" on whether the new topic will trend, but some samples' votes count more than others'. The weighted votes are then combined, giving a probabilistic estimate of the likelihood that the new topic will trend.
In Shah and Nikolov's experiments, the training set consisted of data on 200 Twitter topics that did trend and 200 that didn't. In real time, they set their algorithm loose on live tweets, predicting trending with 95 percent accuracy and a 4 percent false-positive rate.
Shah predicts, however, that the system's accuracy will improve as the size of the training set increases. "The training sets are very small," he says, "but we still get strong results."
Keeping pace
Of course, the larger the training set, the greater the computational cost of executing Shah and Nikolov's algorithm. Indeed, Shah says, curbing computational complexity is the reason that machine-learning algorithms typically employ parametric models in the first place. "Our computation scales proportionately with the data," Shah says.
But on the Web, he adds, computational resources scale with the data, too: As Facebook or Google add customers, they also add servers. So his and Nikolov's algorithm is designed so that its execution can be split up among separate machines. "It is perfectly suited to the modern computational framework," Shah says.
In principle, Shah says, the new algorithm could be applied to any sequence of measurements performed at regular intervals. But the correlation between historical data and future events may not always be as clear cut as in the case of Twitter posts. Filtering out all the noise in the historical data might require such enormous training sets that the problem becomes computationally intractable even for a massively distributed program. But if the right subset of training data can be identified, Shah says, "It will work."
###
Written by Larry Hardesty, MIT News Office
[ | E-mail | Share ]
?
AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.
Predicting what topics will trend on TwitterPublic release date: 1-Nov-2012 [ | E-mail | Share ]
Contact: Caroline McCall cmccall5@mit.edu Massachusetts Institute of Technology
A new algorithm predicts which Twitter topics will trend hours in advance and offers a new technique for analyzing data that fluctuate over time
CAMBRIDGE, Mass. -- Twitter's home page features a regularly updated list of topics that are "trending," meaning that tweets about them have suddenly exploded in volume. A position on the list is highly coveted as a source of free publicity, but the selection of topics is automatic, based on a proprietary algorithm that factors in both the number of tweets and recent increases in that number.
At the Interdisciplinary Workshop on Information and Decision in Social Networks at MIT in November, Associate Professor Devavrat Shah and his student, Stanislav Nikolov, will present a new algorithm that can, with 95 percent accuracy, predict which topics will trend an average of an hour and a half before Twitter's algorithm puts them on the list and sometimes as much as four or five hours before.
The algorithm could be of great interest to Twitter, which could charge a premium for ads linked to popular topics, but it also represents a new approach to statistical analysis that could, in theory, apply to any quantity that varies over time: the duration of a bus ride, ticket sales for films, maybe even stock prices.
Like all machine-learning algorithms, Shah and Nikolov's needs to be "trained": it combs through data in a sample set in this case, data about topics that previously did and did not trend and tries to find meaningful patterns. What distinguishes it is that it's nonparametric, meaning that it makes no assumptions about the shape of patterns.
Let the data decide
In the standard approach to machine learning, Shah explains, researchers would posit a "model" a general hypothesis about the shape of the pattern whose specifics need to be inferred. "You'd say, 'Series of trending things remain small for some time and then there is a step,'" says Shah, the Jamieson Career Development Associate Professor in the Department of Electrical Engineering and Computer Science. "This is a very simplistic model. Now, based on the data, you try to train for when the jump happens, and how much of a jump happens.
"The problem with this is, I don't know that things that trend have a step function," Shah explains. "There are a thousand things that could happen." So instead, he says, he and Nikolov "just let the data decide."
In particular, their algorithm compares changes over time in the number of tweets about each new topic to the changes over time of every sample in the training set. Samples whose statistics resemble those of the new topic are given more weight in predicting whether the new topic will trend or not. In effect, Shah explains, each sample "votes" on whether the new topic will trend, but some samples' votes count more than others'. The weighted votes are then combined, giving a probabilistic estimate of the likelihood that the new topic will trend.
In Shah and Nikolov's experiments, the training set consisted of data on 200 Twitter topics that did trend and 200 that didn't. In real time, they set their algorithm loose on live tweets, predicting trending with 95 percent accuracy and a 4 percent false-positive rate.
Shah predicts, however, that the system's accuracy will improve as the size of the training set increases. "The training sets are very small," he says, "but we still get strong results."
Keeping pace
Of course, the larger the training set, the greater the computational cost of executing Shah and Nikolov's algorithm. Indeed, Shah says, curbing computational complexity is the reason that machine-learning algorithms typically employ parametric models in the first place. "Our computation scales proportionately with the data," Shah says.
But on the Web, he adds, computational resources scale with the data, too: As Facebook or Google add customers, they also add servers. So his and Nikolov's algorithm is designed so that its execution can be split up among separate machines. "It is perfectly suited to the modern computational framework," Shah says.
In principle, Shah says, the new algorithm could be applied to any sequence of measurements performed at regular intervals. But the correlation between historical data and future events may not always be as clear cut as in the case of Twitter posts. Filtering out all the noise in the historical data might require such enormous training sets that the problem becomes computationally intractable even for a massively distributed program. But if the right subset of training data can be identified, Shah says, "It will work."
###
Written by Larry Hardesty, MIT News Office
[ | E-mail | Share ]
?
AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.
NEW YORK, Oct. 31, 2012 (Reuters) ? Wall Street firms and U.S. banks scrambled to raise cash on Wednesday, as U.S. financial markets resumed normal trading after a devastating storm pummeled the U.S. East Coast and closed major markets for two days.
Mayor Michael Bloomberg rings the opening bell at the New York Stock Exchange in New York, October 31, 2012. The exchange opened Wednesday following Hurricane Sandy. REUTERS/Dario Cantatore/NYSE Euronext/Handout
Major banks and investment houses rely on the money markets - a key cash source for financial markets - to finance trading positions and loans they make. Companies sell commercial paper and other short-term debt to money market funds and other investors to fund their inventories and payrolls.
The massive storm, Sandy, disrupted these markets, thinned trading and drove up borrowing costs on Monday and Tuesday, although analysts expect money market rates to return to normal levels by early next week.
"It showed a bit of stress that everyone was trying to fund themselves," said Mike Lin, director of U.S. funding with TD Securities in New York.
Some companies were heard withdrawing heavily from their accounts with money market funds last Thursday and Friday in preparation for possible market disruptions this week, analysts said, although the latest data available showed money fund assets had risen through Oct 24.
If banks were to struggle to obtain short-term funding, they could turn to the U.S. Federal Reserve, but there were no signs any banks needed to borrow emergency cash via the central bank's "discount window," analysts and traders said.
The Fed currently charges 0.75 percent at its discount window on loans to creditworthy banks.
A spokesman with the New York Fed, which oversees open market operations for the central bank, declined to comment.
MONTH-END COMPLICATION
But overnight borrowing costs in funding markets have since receded from levels seen on Monday and Tuesday, which were levels not seen since the height of the global credit crunch in late 2008.
"It was about the market being illiquid. People tried to close their books before the storm," Alex Roever, short-term interest rate strategist at J.P. Morgan Securities who is based in New York, said about the trading on Monday and Tuesday.
Investors charged a borrower 0.35 to 0.40 percent for an overnight loan in the repurchase agreement (repo) market on Wednesday. This was double what they charged last week, analysts and traders said.
However, this was sharply lower than the 1.25 percent heard quoted late on Monday before Sandy made landfall in the U.S. Northeast. The storm knocked out power for about 8 million people and flooded the New York subways.
Money market funds and other large investors also commanded slightly higher compensation to buy commercial paper (CP).
The trading volume of these short-term corporate IOUs was a quarter of their average daily volume, traders said.
"The challenge was on the investor side. They were trying to figure what their month-end outflows were," J.P. Morgan's Roever said.
Interest rates on commercial paper that matures in a week on average was quoted at 0.25 percent, fractionally higher than last Friday. CP activity was non-existent on Monday and Tuesday, according to market participants.
The timing of the interruption also complicated the jobs for money market traders who typically seek cash to settle trades and exit positions on the last trading day of the month.
Traders at banks and other institutions rushed to raise money Monday and Tuesday to insure their trades were funded at least through Wednesday, when they had expected the stock and bond markets to reopen.
"It's not as bad as it could have been, but people are still operating with skeletal staffs," TD's Lin said.
The staffing at banks and Wall Street firms should improve as the city's subway system resumes limited service on Thursday.
On Friday, the overnight repo rate ended at 0.20 percent.
In the $1.8 trillion tri-party repo market, a borrower obtains cash from investors by pledging Treasuries and other securities as collateral.
Longer-term repo rates were lower on expectations of trading returning to normal soon, analysts said.
"By next week, we should be back to normal ranges," said Dave Sylvester, head of money markets with Wells Capital Management in Minneapolis.
Well Capital operates a dozen money market funds with combined assets of $130 billion.
One-week repo rates, for example, was last quoted at 0.20-0.25 percent, while one-week commercial paper rates were quoted in a similar range.
(Additional reporting by Jonathan Spicer; Editing by Bernadette Baum, Bernard Orr)
Reviews are one of the most popular types of content on the web. In fact, they have literally changed the way people shop. But they have also changed the lives of content creators. Because of their popularity, reviews are something that content creators can target with confidence as a value-provider (provided the review actually provides value, of course).
There are a number of WordPress plugins out there that will help content creators deliver their reviews in a more attractive and engaging way. We?ve gone through all the best free ones we could find and whittled the list down to six plugins that we thought were the best.
Some of the plugins below take advantage of schema.org markup options. These markups allow search engines to read and then display things like ratings (stars, for example) in their results, as well as other information such a price (if applicable) and even the review?s author. We have indicated whether or not each plugin uses the schema.org markup options.
(Note: All of the plugins below are for reviews written by site authors, not visitors to a site.)
Featured Plugin - Open an Online Store with MarketPress
Out of all the WordPress ecommerce plugins available, this has got to be the winner - easy to configure, powerful functionality, multiple gateways and more. A simply brilliant plugin!
Find out more
?
1. Benday Reviews System
The Benday Reviews System plugin offers a very easy-to-use yet fairly sophisticated review solution that gathers reviews from your site into one sortable table.
First you will need to set up your categories on the settings page. After that, you will see a new simple box for your review under the Write/Edit Screen.
?
You will need to insert the plugin?s shortcode on a Page. This is where a summary of your reviews will appear in a table.
?
Once that?s done, all your reviews will appear on that page. They will then be sortable within the table by title, category, rating, and date posted.
?
If you click on an individual category (at the top), you will see reviews only in that category.
?
Clicking on the title will take you to the actual post.
This plugin is very nice, but its one noticeable drawback seems to be that it does NOT place your review score on the post itself. Of course you could do that manually, or you could use another plugin to record the score and place it on the post.
Although there aren?t settings to change the appearance of the table, if you know CSS, you can dig into the plugin?s CSS file to change things the way you like.
(This plugin does NOT use schema.org markup options.)
?
2. Author hReview
The Author hReview plugin places an attractive summary box of your review on your Post page with star ratings and other information. It also takes advantage of schema.org markup options. These markups allow search engines to read and then display things like ratings (stars, for example) in their results.
This plugin taps into schema.org by using product markup options or general review markup options (good for most anything ? restaurant reviews, movie reviews, etc.).
Here?s an example of a completed review for a DVD.
?
The settings on your Post page consist of the following options.
?
You can also control some basic options of the review boxes overall. Here?s a look at that settings page.
?
?
3. Author Product Review
As the name indicates, the Author Product Review plugin is?is primarily designed for reviewing products; however, you could use it for other purposes if you really wanted to as well (that said, you might find more flexibility in other plugins if not reviewing products).? This plugin takes advantage of schema.org markup options. These markups allow search engines to read and then display things like ratings (stars, for example) in their results.
Here?s an example of how a post you create with this plugin may appear in the search engines. This image has been taken from the plugin?s info page.
After activating the plugin, you will see a review box on the sidebar of your Write/Edit Screen.
When published, the plugin shows only the rating that you?ve given the product. It does not show the price or the name of the product; however, this information is included in the code of your page, and so it can be read and displayed by search engines. (See the search engine image above and notice the information included there.)
By default, your rating (with stars) is automatically inserted at the end of your post; however, you can place it anywhere in the post you like by simply inserting {rating}.
In this example, I?ve placed it at the very top.
?
4. Review Schema
Like the Author Product Review plugin above, the Review Schema plugin is made to take advantage of schema.org markup options. These markups allow search engines to read and then display things like ratings (stars, for example) in their results, as well as other information.
Here?s a look at how your results might appear in the search engines (as demonstrated by the plugin author).
?
The review box for this plugin appears in the sidebar of your Write/Edit Screen.
?
Again, like the Author Product Review plugin, the only information that is displayed on your Post page is the star ratings, and you can place those stars where you like by inserting a {rating}tag. The other information is included in your code and can be read by search engines, but it won?t be visible to readers.
?
?
5. Easy Review Builder
Although not quite as ?easy? as it might be, the Easy Review Builder plugin does provide a nice review platform that will allow you to add as many different elements to a review as you like, and it will also automatically calculate an overall rating for you based on the scores of the individual elements.
Here?s a look at an example of what it can do.
The reason why this plugin is not quite as easy as it might be is because all the information must be entered into shortcodes. The end result is impressive, but a more user-friendly system for entering information would help.
As a demonstration, here?s a look at the shortcode that created the example above.
?
But again, the result in the end is nice. In fact, you can even easily style the table to your liking in the settings. Here?s a look at how you might do that.
?
(This plugin does NOT use schema.org markup options.)
?
6. Review Ratings
The Review Ratings plugin is a simple plugin that lets you easily assign a rating to whatever you?d like with a shortcode. Here?s a look at it in action with a 4 out of 5 stars rating.
One of the nicer aspects of this plugin is that it lets you change the type of symbols to use for your ratings (stars, hearts, etc.), and it also lets you change the color. You can also determine the number of possible symbols for the highest rating via the settings page.
?
This plugin will also allow you include ?related? posts with a shortcode; however, there is not much subtlety in this. The related posts are chosen from any other posts on your site that happen to have ratings, regardless of their topic. The plugin author indicates that the relationship is based on similar ratings. As well, it seems the plugin sometimes chooses the very same post as a related post.
That said, if you?re just looking to insert a quick rating into your posts, this plugin may be what you?re looking for.
(This plugin does NOT use schema.org markup options.)
?
Featured Plugin - WordPress + Google Maps = Perfect
Simply insert google maps into posts, sidebars and pages - show directions, streetview, provide image overlays and do it all from a simple button and comprehensive widget.
Find out more
Related posts:
Great Review Site for Checking Out WordPress Plugins Don?t get caught by bad plugins, check out WP nuggets to filter Wordpress Plugins before installation...
Two New WordPress and BuddyPress Review Themes Available on Themeforest Want to build a review site using BuddyPress? Check out the details on two new theme options....
10 WordPress Themes for Creating a Review Site This week our showcase is all about WordPress review themes. These themes help you to create a great WordPress review...
Looking for WordPress Hosting? Check out WPShout?s Hosting Review Trying to find the perfect web host for WordPress? Check out WPShout's thorough review....
10 Plugins to Make WordPress Blazing Fast Check out these 10 great plugins for speeding up WordPress performance....
Dell Inc. is an American multinational computer technology corporation based in 1 Dell Way, Round Rock, Texas, United States, that develops, sells and supports computers and related products and services. Bearing the name of its founder, Michael Dell, the company is one of the largest technological corporations in the world, employing more than 103,300 people worldwide.[Dell is listed at number 44 in the Fortune 500 list. It is the third largest PC vendor in the world after HP and Lenovo.
View Website
Job Role:Tech Process Associate Job Location: Across India Education: BE(CS/IT/EC/EI)/BCA/MCA from 2012,2013 batch Experience: Freshers Salary: Rs. 180000LPA Last date to apply: 05 Nov,2012 Venue Date: To be informed Venue Location: To be informed
Desired Profile:
Candidates must be BE(CS/IT/EC/EI)/BCA/MCA from 2012,2013 batch
No backlogs
Should be open to work in night shifts in a 24?7 environment.
Should have excellent communication skills in English.
Interested and eligible candidates can register online on or before 05 Nov,2012. Only shortlisted candidates will get venue date and place information via email
For more details,click here
For registrations,click here
Note: ?Should be open to relocate to Chandigarh / Mohali in case of outstation candidates.( relocation assistance provided )
Related posts:
HCL Off campus for BE/MCA/Graduates of 2011 and 2012 batch @ Across India
Sasken Off campus for BSc/MSc/BCA/MCA graduates on 9 June @ Kerala
Innodata Isogen off campus for BE/BTech/MCA Freshers from 2011 & 2012 batch
EncryptSoft conducting campus drive for BE/MCA Freshers @ Bhopal
Genpact Off campus for Graduate Freshers on 30 Oct
Here at Cabrillo, we often talk about the energy-saving benefits of installing a programmable thermostat. But with so many kinds of thermostats on the market, how are you supposed to figure out which one is right for you? Today we?re going to highlight some the most important programmable thermostat features that you should look for when you?re deciding on which model to choose.![[ Back to EurekAlert! ]](https://lh3.googleusercontent.com/blogger_img_proxy/AEn0k_uif5xZWXwLF1ZHquXlK6kXZBpsSnoo8Jq42cRvOYEDdDAZtWTHCt2Fq7HyW6UXu5Ib_oogY2uNGAvKhHgpyQ0lEutf0mhXUAZO-mYdUiE=s0-d){kind=small}
Public release date: 1-Nov-2012
Share ] 
