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Anonymous asked:

So what's the premise of the Original Sin story arch and is it worth the read?


PLOT: Nick Fury is more of a badass than previously though

That’s it

oh and apparently.. we’re like supposed to hate him or something.

I don’t know.

It’s like

So .. to protect earth he’s been killing bad dudes for like 50 years or something.

And the avengers don’t like that because killing is badong

and Avengers never ever ever ever ever EVER kill (that’s sarcasm)

Fury was a prevention

Avengers are a cure


so yeah

i don’t know if they were trying to make people dislike fury or whatever but it’s not worked.

At all.

He’s got one issue left and well.. let’s see how they fuck him over so he can be replaced by marcus johnson

and yeah

it’s worth reading because the art is wizard and you get to see Nick Fury thrash the avengers


Neuroscience and big data: How to find simplicity in the brain

Scientists can now monitor and record the activity of hundreds of neurons concurrently in the brain, and ongoing technology developments promise to increase this number manyfold. However, simply recording the neural activity does not automatically lead to a clearer understanding of how the brain works.

In a new review paper published in Nature Neuroscience, Carnegie Mellon University’s Byron M. Yu and Columbia University’s John P. Cunningham describe the scientific motivations for studying the activity of many neurons together, along with a class of machine learning algorithms — dimensionality reduction — for interpreting the activity.

In recent years, dimensionality reduction has provided insight into how the brain distinguishes between different odors, makes decisions in the face of uncertainty and is able to think about moving a limb without actually moving. Yu and Cunningham contend that using dimensionality reduction as a standard analytical method will make it easier to compare activity patterns in healthy and abnormal brains, ultimately leading to improved treatments and interventions for brain injuries and disorders.

"One of the central tenets of neuroscience is that large numbers of neurons work together to give rise to brain function. However, most standard analytical methods are appropriate for analyzing only one or two neurons at a time. To understand how large numbers of neurons interact, advanced statistical methods, such as dimensionality reduction, are needed to interpret these large-scale neural recordings," said Yu, an assistant professor of electrical and computer engineering and biomedical engineering at CMU and a faculty member in the Center for the Neural Basis of Cognition (CNBC).

The idea behind dimensionality reduction is to summarize the activity of a large number of neurons using a smaller number of latent (or hidden) variables. Dimensionality reduction methods are particularly useful to uncover inner workings of the brain, such as when we ruminate or solve a mental math problem, where all the action is going on inside the brain and not in the outside world. These latent variables can be used to trace out the path of ones thoughts.

"One of the major goals of science is to explain complex phenomena in simple terms. Traditionally, neuroscientists have sought to find simplicity with individual neurons. However, it is becoming increasingly recognized that neurons show varied features in their activity patterns that are difficult to explain by examining one neuron at a time. Dimensionality reduction provides us with a way to embrace single-neuron heterogeneity and seek simple explanations in terms of how neurons interact with each other," said Cunningham, assistant professor of statistics at Columbia.

Although dimensionality reduction is relatively new to neuroscience compared to existing analytical methods, it has already shown great promise. With Big Data getting ever bigger thanks to the continued development of neural recording technologies and the federal BRAIN Initiative, the use of dimensionality reduction and related methods will likely become increasingly essential.

I love reading these neuroscience posts! They always sound terrifying at the title, but tend to sound much simpler at the last paragraph (when you read the whole text, lazy bones!)


When cells apoptose, they appear to collapse, forming small blebs and vesicles called apoptotic bodies. Here, an apoptotic HeLa cell (center) sits among its healthy and dividing counterparts, revealing a striking collection of blebs on its surface. Although HeLa cells are the workhorse of many in vitro cell biological experiments, they are far from normal. They are propagated from a cervical tumor and contain an aberrant genome with multiple copies of several human chromosomes, some of which also carry papilloma viral genes.

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