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Senate Committee Approves FY 2010 Spending Bill Without Funding For Abstinence-Only Education
The Senate Appropriations Committee on Thursday approved its fiscal year 2010 spending bill (HR 3293) for health, education and labor programs, CQ Today reports. The bill does not include funding for abstinence-only sex education, instead providing $104.5 million for a comprehensive "Teen Pregnancy Prevention" program. The recently passed House version of the bill takes a similar approach, according to CQ Today.The committee voted 29-1 to approve the $730 billion bill, with abstinence-only advocate Sen. Sam Brownback (R-Kan.) being the sole opponent (Wolfe, CQ Today, 7/30).In related news, Sen. Arlen Specter (D-Pa.) in the FY 2010 spending bill did not request funding for abstinence-only sex education programs in his home state, despite routinely requesting such funds as a Republican, CQ Politics reports.When he was a Republican, Specter sponsored 22 earmarks totaling $550,000 for abstinence-only programs in the FY 2009 version of the bill. Specter"s aides said that he wanted to focus earmark requests on hospitals and universities in the FY 2010 version of the bill. However, the "likely" explanation for the absence of abstinence-only earmark requests is the senator"s 2009 switch to the Democratic Party, which often advocates for comprehensive sex education programs as a way to reduce teen pregnancy, CQ Politics reports (Clarke, CQ Politics, 7/29).
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Johns Hopkins School Of Medicine To Offer New Degree Program In Informatics
A new, intensive, one-year master"s degree program designed to prepare graduates for informatics leadership positions in clinical, public health and scientific settings will be offered beginning in September by the Johns Hopkins University School of Medicine. The Maryland Higher Education Commission (MHEC) approved the new program in June.
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Genes Play A Role In Glycemic Control In People With Type 1 Diabetes
Researchers have proven that glycemic control in type 1 diabetes is not fully dependent on the individual"s behavior, but is in part subject to genetic influence, according to a presentation here today at the American Diabetes Association"s 69th Scientific Sessions.
Diagnostics

Yawn Alert For Weary Drivers

We"ve all experienced it after long hours driving, the eyelids getting heavy, a deep yawn, neck muscles relaxing, the urge to sleep, the head nodding down... But, you"re hands are still on the wheel and you only just stopped yourself nodding off in time to avoid the oncoming traffic. But what if your car could keep an eye on you while you drive and nudge you when you starting yawning and warn you to pull over and take a break? That"s the aim of a new in-car yawn-detection system being developed by an international team in the US and India. Writing in the inaugural issue of the International Journal of Computational Vision and Robotics, Aurobinda Mishra of Vanderbilt University, in Nashville, TN, and colleagues Mihir Mohanty of ITER, in Orissa and Aurobinda Routray of IIT, West Bengal, India, describe a computer program that can tell when you are yawning and could prevent road traffic accidents. The US National Highway Traffic Safety Administration estimates that at least 100,000 road crashes are caused by driver fatigue each year. The new program is based around an in-car camera hooked up to image-processing software that captures a sequence of images of the driver"s face. It then analyses changes in the face and accurately identifies yawning as distinct from other facial movements such as smiling, talking, and singing. The yawn frequency is then correlated with fatigue behavior and could then be hooked up to a warning system to alert drivers to the need to take a break. The algorithm is effective at yawn detection regardless of image intensity and contrast, small head movements, viewing angle, spectacle wearing, and skin color. The researchers point out that for traffic safety, it is essential to recognize and understand the physical and mental stress leading to fatigue in drivers. Considerable research has been carried out to investigate and characterize biological signals, such as brain waves and heart activity. However, it would be costly and inconvenient for drivers to have to connect to an ECG machine every time they took a trip. A system that watches the driver and analyses their facial expressions would be so much simpler and less invasive. "A non-rigid motion estimation algorithm for yawn detection in human drivers" in International Journal of Computational Vision and Robotics, 2009, 1, 89-109 Mihir Mohanty Inderscience Publishers


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