Abstract: We give a systematic study of Higgs masses in a non-minimal model of supersymmetry with renormalization group improvement for extended values of the parameters like tanβ , MC (the mass of charged Higgs) and Q (the squark mass scale), in the context of LHC experiments. Several new and interesting results are obtained.
Keywords: Higgs Mass, Non-Minimal Model of Supersymmetry, Renormalization Group, LHC Experiment
Introduction: Supersymmetry is a very important tool for studying physics beyond standard model . It is being vigorously pursued for detecting supersymmetric particles in nature. The supersymmetric particles include the supersymmetric partners of ordinary particles and supersymmetric Higgs bosons. The minimal supersymmetric standard model (MSSM) , for example, contain two CP-even neutral Higgs bosons, a CP-odd neutral Higgs boson and two charged Higgs bosons. The relaxation of any of the assumptions of MSSM leads to non-minimal model (NMSSM). Ellis et al  gave non-minimal model by inclusion of a single Higgs field whose vacuum expectation value determined the mixing of the two Higgs doublet of the minimal supersymmetric standard model. These authors studied the spectrum and couplings of Higgs bosons in this extended model and compared them with those in the minimal model. In their extensive work , Ellis et al analyzed the possible production mechanisms and phenomenological signatures of the different Higgs bosons at the TeV-scale.
Keep reading: http://bit.ly/1Ltro24
By Janine Anderson | October 12, 2015 11:03 am
This image shows the functional connections in the brain that tend to be most discriminating of individuals. (Credit: Emily Finn)
Each person is unique. You can identify people by their DNA, fingerprints, personal preferences and behavior. But new research out of Yale University has shown we have another unique identifier: How our brains work.
“We all have this intuition that people are unique. We all have our own strengths and weaknesses, our quirks and personalities, what we’re good at and how we handle things,” says study co-first author Emily Finn, a pHD student in neuroscience at Yale. “It’s very easy to observe that from the outside … but it’s been pretty hard to find correlates in brain activities.”
And yet, it is the brain that makes all those differences possible. Knowing this, Finn and co-first author Xilin Shen, an associate research scientist at Yale, used functional magnetic resonance imaging (fMRI) scans to see if our brains each have a unique “fingerprint” that could distinguish one person from another.
To get a glimpse at the way specific parts of the brain function in real time, scientists use fMRIs to repeatedly scan a person’s brain while they complete a specific task. The noninvasive technique measures the amount of blood flowing to certain parts of the brain — more blood indicates more activity. Most fMRI studies average brain function over a study population, which has let scientists learn what parts of the brain work under certain circumstances. The convention among scientists, Finn said, was that it is hard to get meaningful information out of a single person’s fMRI scan.
Finn and Shen wanted to challenge conventional thinking.
They scanned the brains of 126 participants in the Human Connectome Project while they performed several different tasks. They mapped the connections in the prefrontal cortex and parietal lobes — recently evolved parts of the brain involved in complex functions like attention and language — to develop connectivity profiles of each person. They found that each person’s bran activity profile was indeed unique.
“The same brain doing two different things always looks more similar than two different brains doing the same thing,” says Finn. “It’s something that maybe seems intuitive outside the field but it’s something no one had been able to show.”
Their study was published Monday in Nature Neuroscience.
Beyond proving each person’s connection profile was unique and distinguishable from another person’s, Finn and Shen also looked to see if it was possible to use profile data to accurately predict someone’s performance on a test. To measure performance, they first developed a predictive model; they then — 126 times — removed one subject’s profile and put the remaining 125 through their model to see if it could accurately predict the person’s performance on a test that measured reasoning and the ability to see patterns.
Because they had the subjects’ actual test results, they could see how well the model stacked up, and found it was able to predict performance in a statistically significant way.
“It was more accurate than chance,” says Finn. “It certainly wasn’t perfect.”
A Bigger Role for fMRI
Finn says the predictive portion of the study was “more a proof of principle” that brain profiles could be linked to cognitive behavior.
“If we can predict that,” says Finn, “maybe we can predict something we can’t just give a test for, like the risk for mental illness or who would respond best to some kind of drug.”
That’s what led her and others on the team to do this work, she said.
“You as a scientist like to think the things you’re discovering about the brain will help people someday,” says Finn.
She wanted to see if there was a way to make fMRI scans useful from a clinical standpoint, where doctors could someday tell from the scan whether a person might be at higher risk for developing a mental illness, and to then implement a support plan that could improve their outcome. Currently, fMRI scans are really only used in research settings, Finn said, because it is harder to get usable information out of the scans. Instead, structural MRIs, which take static photos of the brain, are used regularly to diagnose problems in the brain, like tumors or strokes.
“I think doing this type of work and pushing the boundaries of what we can get out of one person’s scan is the first step down the road to make this brain scanning technology have real-world applicability,” says Finn.
Full story source:http://bit.ly/1WYZij3
ISSN Print: 2376-8045
ISSN Online: 2376-8053
Phosphorus was first discovered by people looking for riches in urine, explains a video by the American Chemical Society’s Reactions series. Seventeenth century alchemists thought urine, with its golden color, might help them turn other substances into gold. When they boiled off the liquid, they got a white glow-in-the-dark substance: phosphorus. The element is a key component of organic molecules and of modern products such as matches and fertilizers.
(Video credit: American Chemical Society/Reactions)
Story source: bit.ly/1LDhexJ
Jamshid Aghazadeh Mohandesi was graduated from Sharif University of Technology, Tehran, Iran in B.S. in Metallurgical Engineering. For M.Sc. and PhD he moved to England and he was graduated at University of Manchester in Material Science and Engineering. At the moment he is a professor at AUT.
Davoud Haghshenas Fatmehsari was graduated from AUT, Tehran, Iran in B.S. in Materials Engineering–Extractive Metallurgy. For M.Sc. he moved to Sharif University of Technology, Tehran, Iran and for PhD he came back to AUT and was graduated at Materials Engineering – Extraction of Metals. At the moment he is an assistant professor at AUT.
– Exploring a novel route for the synthesis of a stable suspension containing graphene sheets in aqueous solution.
– Characterization of the produced graphene sheets.
– Developing the Graphene/Poly Vinyl Alcohol nanocomposites.
– Evaluation of the mechanical properties of the nanocomposites.
| Please see updates and a correction below |
A tropical depression that formed Sunday in the Atlantic has strengthened into a tropical storm that could bring a lot of rain to parts of the U.S. East Coast later this week — possibly on top of a big rainfall event that’s already cranking up for the northern Appalachians and New England over the next several days.
Click on the image above and say hi to Tropical Storm Joaquin.
The forecast for Joaquin is highly uncertain at the moment, thanks to difficulties the weather models are having in dealing with the evolution of other weather disturbances that will likely affect the storm. This is especially true of a trough that’s forecast to develop over the Southeastern United States, according to this morning’s forecast discussion from the National Hurricane Center.
While a large portion of the East Coast is within the forecast cone for tropical storm force winds, the highest probability right now is between 20 and 30 percent, as this graphic shows:
The probabilities of sustained (1-minute average) surface wind speeds equal to or exceeding 39 miles per hour — tropical storm force— for Tropical Storm Joaquin. This wind speed probability map is based in part on forecasts of the track, intensity, and wind radii from the National Hurricane Center. (Source: NHC)
That could change over the next few days — in either direction. Joaquin could strengthen and make landfall, possibly even as a hurricane, or it could turn out to sea and never hit land.
| Update 9/30/15: Here is the latest from the forecast discussion page of the National Hurricane Center:
Joaquin is expected to become a hurricane within 24 hours, with additional intensification likely thereafter.
But Joaquin’s future track is still very highly uncertain. Some model runs take it completely out to sea. Others show the storm making landfall on the East Coast. The NHC’s current official forecast “lies between these possibilities.”
I think at this point we should take it all with a grain of salt. |
Whatever turn Joaquin takes, the U.S Eastern Seaboard already is in for heavy precipitation — independent of the storm. And Joaquin could later add insult to injury.
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