How Long Is 1400 Seconds
How Long Is 1400 Seconds – Harvard brain researcher Dr. Jill Bolt Taylor found that it takes 90 seconds to recognize an emotion and let it go. You just have to pay attention to it
This pausing and naming of emotions reduces activity in the amygdala that triggers primal fight or flight and allows you to act without thinking.
How Long Is 1400 Seconds
“When a person reacts to something in the environment, a 90-second chemical process takes place in the body; After that, any remaining emotional state is only the person who chooses to be in that emotional state.
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It takes less than 90 seconds for this chemical to be completely eliminated from the body This means that for 90 seconds you can see the process happening, you can feel it happening, and then you can see it disappear.
After that, if you continue to feel fear, anger, etc., watch the thoughts you think will re-stimulate the circuitry so that you will have this physical response again and again. “
1️⃣ Identify an emotional response and a corresponding physical response Most emotions have a physical quality that goes with them Examples: tightness in the chest with anxiety, heat build-up with anger, or a sinking feeling in the stomach with fear
Embracing these physical sensations and allowing them to fully express themselves requires the body and nervous system to return to control.
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Speaking your thoughts, feelings and ideas out loud can be very beneficial If you’re in public and can’t speak, tell them in your head The more you notice it, the better you will become at feeling your body and its reactions, without accepting them
At our core, everyone wants to be seen, heard and validated, and so do our feelings Stopping for 90 seconds to really feel what you’re feeling, listening to what your body is telling you, and validating without judgment without naming the experience is deeply healing.
Be careful and consistent with this process Your nervous system and brain will rewire, stand by, fly away, distract, soften or repress your experience of acceptance and love.
Stephanie Rae is a Somatic Experiential and Discovery Practitioner In addition, she is a sex coach specializing in women’s sexuality and sexual trauma. If you use Python and Pandas for data analysis, you may want to use a loop for the first time. But even for small dataframes, using the default loop is time consuming and you will quickly realize that it can take a lot of time for large dataframes. When I first waited more than half an hour for the code to execute, I found the option that I want to share with you.
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A data frame with rows and columns is a pandas object If you use a loop, you will iterate over the entire object Python cannot take advantage of any built-in functions and is very slow. In our example, we have a dataframe with 65 columns and 1140 rows It contains football results for 2016 – 2019 seasons We want to create a new column that indicates whether a particular team has played a draw or not We can start like this:
Since we’ve got every match from the Premier League in our data frame, we need to check if the team of interest (Arsenal) played and if applicable, if they were a home team or an away team. As you can see, this loop was very slow and took 20.7 seconds to execute. Let’s see how we can be more efficient
Returns a series for each row, so it iterates over a data frame as a pair of indexes and the columns of interest as series. This makes it faster than the standard loop:
The code took 68 milliseconds to run, which is 321 times faster than the standard loop. However, many advise against using it as there are still stronger alternatives and.
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Data frame detypes can be changed which can cause many problems You can also use Dtype
. We won’t go into detail here because we want to focus on efficiency Here you will find the official documentation:
Not fast by itself, but has advantages when used in conjunction with DataFrames It depends on the content
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Now we can move on to a new topic We take advantage of vectorization to generate really fast code The point is to avoid loops at the Python level and use optimized C code like the example in  that uses memory more efficiently. We just need to change the function:
In this case we don’t even need a loop We just need to adjust the contents of the function Now we can pass the pandas array directly to our function which results in a huge speedup
In the previous example, we passed our function to the pandas array Adding the values gives us an array of numbers:
Numpy arrays are so fast because we get the benefit of reference locality Our code took 0.305 milliseconds to run and was 71803 times faster than the standard loop used in the beginning.
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If you use Python, Pandas and Numpy for data analysis, there will always be room to improve your code. We compared five different methods of adding a new column to a data frame based on some calculations We noticed a huge difference in speed:
If you like Medium and Tower Data Science and haven’t signed up yet, feel free to use my referral link to join the community. Scientists say that despite the best and most expensive research, a vaccine against SARS-CoV-2, the virus that causes COVID-19, is at least a year away. Scientists also say that the worst enemy of bacteria is the cheap soap in your sink
This is due to simple chemistry In soap suds, a mixture of molecules aggregates into bubble-like structures called micelles that trap viral material and other organic matter — grease, oil, dirt — and fall into the drain.
Thomas Gilbert is an associate professor of chemistry and chemical biology at Northeastern. Photo Courtesy: Thomas Gilbert
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The soaps we use contain a class of compounds called surfactants, which can neutralize bacteria on our skin, such as SARS-CoV-2 and other coronaviruses, pathogens with crown-like structures and an outer shell made of lipid molecules and proteins.
Surfactants essentially prize the coronavirus particles and encapsulate the viral molecules in micelles suspended in the foam, says Thomas Gilbert, associate professor of chemistry and chemical biology at Northeastern. “It washes away the inactivated viral material when you wash your hands.”
SARS-CoV-2 spreads through the air in the form of small particles that are released when an infected person breathes, sneezes, coughs or talks. They can enter your body through your eyes, mouth or nose Recent research has shown that the bacteria can survive for hours, even days, on surfaces made of plastic, metal and cardboard.
Because germs from these contaminated items touch your body and carry the virus, public health officials have pushed hand washing as the best way to protect against COVID-19.
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But it must be done in the right way The gold standard involves scrubbing thoroughly with soap and clean water for at least 20 seconds.
That time allows the soap to form foam that has needle-like surfactant molecules at both ends. One is a hydrophilic one that likes to interact with water The other end is a hydrophobic one that avoids water but readily interacts with other similar biological substances—such as oil, fat—and the outer membrane composition of the coronavirus.
In addition to avoiding water and being water-loving, surfactants in micelles can encapsulate and transport viral debris from our hands using water. In other words, the soap molecules make the basically insoluble viral molecules easily soluble in water (and thus drainable from hands).
But there are many surfaces and parts of your hands that need to be cleaned separately, and foam needs to cover them all to trap bacteria—palms, claws, nails, between fingers, under rings, bandages or splints. Injured finger If you do it right, 20 seconds is plenty of time to be thorough and for the soap molecules to do all the work.
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“It takes time to effectively clean all these surfaces,” says Gilbert. “If you try to do it in half the time, you’re probably not going to clean them effectively.”
That effect of soap can be seen when people use it to wash things like dirt off their hands, Gilbert says. Dirty washing can also show that if you don’t do it right, even 20 seconds won’t be enough to clean your hands. The same applies
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