Tag: patterns

37 Incredible Modular Origami Works by Ekaterina Lukasheva

Ekaterina ‘Kate’ Lukasheva is an incredible Origami artist and designer from Moscow, Russia. The artist has had a fascination with puzzles and construction sets since childhood and first discovered origami in her teens. With its intricate folds and geometric patterns, there’s a lot of math in origami and Ekaterina would later graduate with honors from Moscow State Lomonosov University as a mathematician and programmer.

As Origami has come to describe a broad field with a number of niche disciplines, Lukasheva’s artwork focuses primarily around modular origami and Kusudama. She has even authored a number of books of her own original designs for others to try.

Below you will find a collection of some of her incredible works but you can find hundreds more at the links below

Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

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Ekaterina Lukasheva
Website | Facebook | Flickr | Instagram | Books

Read more: http://twistedsifter.com/2018/02/modular-origami-by-ekaterina-lukasheva-gallery/

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Scientists Have Found A Way To Slow Light To A Complete Stop

Scientists have proposed a theoretical way that light could be slowed down to a complete stop, using something called “exceptional points”.

Published in Physical Review Letters, the authors describe in their study how previous methods included using a cloud of ultracold atoms of sodium to slow light down to speeds approaching zero, but not quite there.

Their method, however, involves using a waveguide – a structure that guides waves in other words, like a tube – to create exceptional points. These are regions where two complex wavelength patterns meet and merge.

What does that mean exactly? Well, we know that light is a wave (most of the time), and these waves constantly change their shape depending on what they’re moving through.

As Live Science notes, if you tune the properties of a container, you can collapse one of light’s complex waves with its mirror twin. Essentially, they cancel each other out. And the point at which that happens is called an exceptional point.

“In this work, we disclose the relation of the stopped light effect with the phenomenon of [the] exceptional point,” the researchers, Tamar Goldzak and Nimrod Moiseyev from the Israel Institute of Technology and Alexei Mailybaev from the Institute for Pure and Applied Mathematics in Brazil, wrote in their paper.

Exceptional points have been shown to have some weird physics before, such as causing lasers to switch on despite energy seemingly being taken away. Sending two wave modes past an exceptional point was described as “driving a car into an icy two-lane tunnel, in which one slides around wildly, but from which one always comes out on the correct side of the road.”

According to this latest paper, in theory, you can cause beams of light to stop moving completely at an exceptional point by changing their properties. The light can then move again when the properties are reversed.

This research is, right now, theoretical. But it could open some interesting avenues for so-called “slow-light applications”, useful for things like telecommunications. And the researchers said the method could apply not just to light waves, but other waves like sound too.

 

Read more: http://www.iflscience.com/physics/scientists-have-found-a-way-to-slow-light-to-a-complete-stop/

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Unravelling Ropes Into Fractal-Like Patterns (10 Photos)

In an ongoing series of artworks entitled ‘Ciclotramas‘, Brazilian artist Janaina Mello Landini unravels ropes into incredible fractal patterns that evoke tree roots, river basins, lightning strikes and circulatory systems.

Landini has been developing this concept since 2010, using threads and strings to create site-specific installations that occupy the space in an immersive way. She adds:

The idea is to “unstitch†Time from its inside, unraveling the threads of the same rope in constant bifurcations, until the last indivisible stage is reached, a point that holds everything together in perfect equilibrium.

Below you will find our favourite Ciclotramas but be sure to check out her website for additional shots and dozens of more examples. Janaina is represented by the Zipper Gallery in São Paulo, Brazil

Janaina Mello Landini
Website | Gallery Representation

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Janaina Mello Landini
Website | Gallery Representation

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Janaina Mello Landini
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Janaina Mello Landini
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Janaina Mello Landini
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Janaina Mello Landini
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Janaina Mello Landini
Website | Gallery Representation

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Janaina Mello Landini
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Janaina Mello Landini
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Janaina Mello Landini
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Janaina Mello Landini
Website | Gallery Representation

Read more: http://twistedsifter.com/2017/11/unravelling-ropes-into-fractal-like-patterns/

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Scientists Discover 40 New Genes Linked To Intelligence

As the great debate over nurture versus nature continues, a team of geneticists have identified 40 new genes that have a direct influence over human intelligence. Writing in the journal Nature Genetics, the team conclude that there are now at least 52 genes that have a direct influence on a persons IQ.

Analyzing the genomes of 60,000 adults and 20,000 children, the team led by the Free University of Amsterdam found that these 40 new genes guide the construction of healthy neurons, as well as the synapse connections that branch between them.

Its likely that there are hundreds of additional genes that have an influence over IQ, so although this study represents the biggest haul yet in this regard, theres still a long way to go before the cartography of our cognitive abilities is complete.

The team note that these 40 new genes, when all other factors are ruled out, explain just 4.8 percent of the variation in human intelligence seen over their subjects. If 50 percent of a persons IQ can be explained genetically, then this means that there is a huge chasm of knowledge that geneticists have yet to fill.

These findings provide starting points for understanding the molecular neurobiological mechanisms underlying intelligence, one of the most investigated traits in humans, the authors write in their study.

Just to clarify straight off the bat these genes have an influence on intelligence, but environmental factors, including lifestyle, healthcare, socio-economic background, education, and so on also have a huge effect.

Furthermore, IQ tests two types of cognitive facets known as crystallized intelligence and fluid intelligence.

The former is the ability of a person to solve puzzles or answer questions when the parameters of the problem have already been understood or conveyed clearly mathematics is a good example of this. Fluid intelligence is the ability to solve brand new and more abstract problems, like navigating a maze, spotting hidden patterns, or even weaving through a conversation with a complete stranger.

content-1495532096-shutterstock-60771881
Ooh! There’s one. (Note: This is not how science is actually done.) vchal/Shutterstock

There are plenty of other types of intelligence, including emotional intelligence the ability to empathize, to regulate ones own emotions, and to handle interpersonal relationships well. IQ does not take this into account, and neither do these 52 genes.

This study also only looked at the genomes of those with European descent. Other research groups will have to peer into the genetic makeup of those from other geographical settings to see if the same genes are present all over the world.

In any case, this is a remarkable study that represents a giant leap forward in our understanding of what has been referred to as the architecture of intelligence. Its a tall mountain to climb, but another ledge has just been scaled by this research team.

[H/T: Guardian]

Read more: http://www.iflscience.com/brain/scientists-discover-40-new-genes-linked-intelligence/

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Paradoxes Of Probability And Other Statistical Strangeness

The Conversation

Statistics is a useful tool for understanding the patterns in the world around us. But our intuition often lets us down when it comes to interpreting those patterns. In this series we look at some of the common mistakes we make and how to avoid them when thinking about statistics, probability and risk. The Conversation


You dont have to wait long to see a headline proclaiming that some food or behaviour is associated with either an increased or a decreased health risk, or often both. How can it be that seemingly rigorous scientific studies can produce opposite conclusions?

Nowadays, researchers can access a wealth of software packages that can readily analyse data and output the results of complex statistical tests. While these are powerful resources, they also open the door to people without a full statistical understanding to misunderstand some of the subtleties within a dataset and to draw wildly incorrect conclusions.

Here are a few common statistical fallacies and paradoxes and how they can lead to results that are counterintuitive and, in many cases, simply wrong.


Simpsons paradox

What is it?

This is where trends that appear within different groups disappear when data for those groups are combined. When this happens, the overall trend might even appear to be the opposite of the trends in each group.

One example of this paradox is where a treatment can be detrimental in all groups of patients, yet can appear beneficial overall once the groups are combined.

How does it happen?

This can happen when the sizes of the groups are uneven. A trial with careless (or unscrupulous) selection of the numbers of patients could conclude that a harmful treatment appears beneficial.

Example

Consider the following double blind trial of a proposed medical treatment. A group of 120 patients (split into subgroups of sizes 10, 20, 30 and 60) receive the treatment, and 120 patients (split into subgroups of corresponding sizes 60, 30, 20 and 10) receive no treatment.

The overall results make it look like the treatment was beneficial to patients, with a higher recovery rate for patients with the treatment than for those without it.

image-20170330-8593-t93w83.pngThe Conversation, CC BY-ND

However, when you drill down into the various groups that made up the cohort in the study, you see in all groups of patients, the recovery rate was 50% higher for patients who had no treatment.

image-20170330-30365-f2956l.pngThe Conversation, CC BY-ND

But note that the size and age distribution of each group is different between those who took the treatment and those who didnt. This is what distorts the numbers. In this case, the treatment group is disproportionately stacked with children, whose recovery rates are typically higher, with or without treatment.


Base rate fallacy

What is it?

This fallacy occurs when we disregard important information when making a judgement on how likely something is.

If, for example, we hear that someone loves music, we might think its more likely theyre a professional musician than an accountant. However, there are many more accountants than there are professional musicians. Here we have neglected that the base rate for the number of accountants is far higher than the number of musicians, so we were unduly swayed by the information that the person likes music.

How does it happen?

The base rate fallacy occurs when the base rate for one option is substantially higher than for another.

Example

Consider testing for a rare medical condition, such as one that affects only 4% (1 in 25) of a population.

Lets say there is a test for the condition, but its not perfect. If someone has the condition, the test will correctly identify them as being ill around 92% of the time. If someone doesnt have the condition, the test will correctly identify them as being healthy 75% of the time.

So if we test a group of people, and find that over a quarter of them are diagnosed as being ill, we might expect that most of these people really do have the condition. But wed be wrong.


image-20170329-1664-htfx0x.pngIn a typical sample of 300 patients, for every 11 people correctly identified as unwell, a further 72 are incorrectly identified as unwell. The Conversation, CC BY-ND


According to our numbers above, of the 4% of patients who are ill, almost 92% will be correctly diagnosed as ill (that is, about 3.67% of the overall population). But of the 96% of patients who are not ill, 25% will be incorrectly diagnosed as ill (thats 24% of the overall population).

What this means is that of the approximately 27.67% of the population who are diagnosed as ill, only around 3.67% actually are. So of the people who were diagnosed as ill, only around 13% (that is, 3.67%/27.67%) actually are unwell.

Worryingly, when a famous study asked general practitioners to perform a similar calculation to inform patients of the correct risks associated with mammogram results, just 15% of them did so correctly.


Will Rogers paradox

What is it?

This occurs when moving something from one group to another raises the average of both groups, even though no values actually increase.

The name comes from the American comedian Will Rogers, who joked that when the Okies left Oklahoma and moved to California, they raised the average intelligence in both states.

Former New Zealand Prime Minister Rob Muldoon provided a local variant on the joke in the 1980s, regarding migration from his nation into Australia.

How does it happen?

When a datapoint is reclassified from one group to another, if the point is below the average of the group it is leaving, but above the average of the one it is joining, both groups averages will increase.

Example

Consider the case of six patients whose life expectancies (in years) have been assessed as being 40, 50, 60, 70, 80 and 90.

The patients who have life expectancies of 40 and 50 have been diagnosed with a medical condition; the other four have not. This gives an average life expectancy within diagnosed patients of 45 years and within non-diagnosed patients of 75 years.

If an improved diagnostic tool is developed that detects the condition in the patient with the 60-year life expectancy, then the average within both groups rises by 5 years.

image-20170328-21243-1wcp3a8.pngThe Conversation, CC BY-ND


Berksons paradox

What is it?

Berksons paradox can make it look like theres an association between two independent variables when there isnt one.

How does it happen?

This happens when we have a set with two independent variables, which means they should be entirely unrelated. But if we only look at a subset of the whole population, it can look like there is a negative trend between the two variables.

This can occur when the subset is not an unbiased sample of the whole population. It has been frequently cited in medical statistics. For example, if patients only present at a clinic with disease A, disease B or both, then even if the two diseases are independent, a negative association between them may be observed.

Example

Consider the case of a school that recruits students based on both academic and sporting ability. Assume that these two skills are totally independent of each other. That is, in the whole population, an excellent sportsperson is just as likely to be strong or weak academically as is someone whos poor at sport.

If the school admits only students who are excellent academically, excellent at sport or excellent at both, then within this group it would appear that sporting ability is negatively correlated with academic ability.

To illustrate, assume that every potential student is ranked on both academic and sporting ability from 1 to 10. There are an equal proportion of people in each band for each skill. Knowing a persons band in either skill does not tell you anything about their likely band in the other.

Assume now that the school only admits students who are at band 9 or 10 in at least one of the skills.

If we look at the whole population, the average academic rank of the weakest sportsperson and the best sportsperson are both equal (5.5).

However, within the set of admitted students, the average academic rank of the elite sportsperson is still that of the whole population (5.5), but the average academic rank of the weakest sportsperson is 9.5, wrongly implying a negative correlation between the two abilities.

image-20170329-1649-h3kvxl.pngThe Conversation, CC BY-ND


Multiple comparisons fallacy

What is it?

This is where unexpected trends can occur through random chance alone in a data set with a large number of variables.

How does it happen?

When looking at many variables and mining for trends, it is easy to overlook how many possible trends you are testing. For example, with 1,000 variables, there are almost half a million (1,000×999/2) potential pairs of variables that might appear correlated by pure chance alone.

While each pair is extremely unlikely to look dependent, the chances are that from the half million pairs, quite a few will look dependent.

Example

The Birthday paradox is a classic example of the multiple comparisons fallacy.

In a group of 23 people (assuming each of their birthdays is an independently chosen day of the year with all days equally likely), it is more likely than not that at least two of the group have the same birthday.

People often disbelieve this, recalling that it is rare that they meet someone who shares their own birthday. If you just pick two people, the chance they share a birthday is, of course, low (roughly 1 in 365, which is less than 0.3%).

However, with 23 people there are 253 (23×22/2) pairs of people who might have a common birthday. So by looking across the whole group you are testing to see if any one of these 253 pairings, each of which independently has a 0.3% chance of coinciding, does indeed match. These many possibilities of a pair actually make it statistically very likely for coincidental matches to arise.

For a group of as few as 40 people, it is almost nine times as likely that there is a shared birthday than not.

image-20170329-1664-1tb8sti.pngThe probability of no shared birthdays drops as the number of people in a group increases. The Conversation, CC BY-ND

Stephen Woodcock, Senior Lecturer in Mathematics, University of Technology Sydney

This article was originally published on The Conversation. Read the original article.

Read more: http://www.iflscience.com/editors-blog/paradoxes-of-probability-and-other-statistical-strangeness/

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This Light Painting, Double Pendulum Elegantly Demonstrates Chaotic Movement

Pendulus” is a double pendulum built by Devin Montes that visualizes the unpredictable patterns of chaotic movement in real-time, using an LED light and glow-in-the-dark paint.

For more cool projects, check out Devin’s YouTube channel, Make Anything // 3D Printing Channel

Read more: http://twistedsifter.com/videos/light-painting-double-pendulum-visualizes-chaotic-movement/

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