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In a recent study, researchers at Harvard University set out to understand the mathematical principles underlying kirigami, which is a variation of origami and an old Japanese cultural tradition. They were able to come up with a mathematical model allowing them to cut a kirigami sheet of paper in a way in which it ‘can be moulded into just about any 3D shape’.

Kirigami, also known as origami’s lesser-known cousin, relies on cutting paper instead of folding it, with ‘kiri’ meaning ‘cut’ and ‘kami’ standing for ‘paper’. The study’s team sought to uncover the basic mathematical principles underlying kirigami, using them to create algorithms which allowed for the design of the number, size and orientation of the cuts in a flat sheet, thus ensuring it could morph into any given shape. For the study, they solved this problem by first identifying the constraints which must be satisfied in order to achieve such a cut pattern, using a numerical optimisation approach to determine the patterns, and finally verifying this experimentally.

Their mathematical framework is thought to be able to turn any sheet of material into any shape using kirigami cuts. The team is confident their work is ‘just the beginning of a class of new ways to engineer shape in the digital age using geometry, topology, and computation’. Further, they believe their work may potentially be used to ‘apply the tradition of kirigami to engineering by creating flexible construction shapes’. Such work is said to draw ‘on inspiration from art, tempered by the rigor of mathematics, and the challenges of engineering shape’.

Applicants for Mathematics, as well as those applying for Engineering might reflect on how such a peculiar link, between the topics of art, design, and mathematical principles, might be beneficial for future innovative applications, for example by using such findings for concepts such as ‘creating foldable shelter and housing’.

Amazon recently unveiled the latest version of their delivery drone at a conference in Las Vegas, stating its plans to be delivering packages by drone “within months”.

In the past, Amazon has been accused of using the idea of a drone as a publicity stunt, making it into the news in order to push their Prime membership. However, they ran a successful trial in Cambridge in December 2016, in which a drone delivered a package in 13 minutes.

Although the company have not made clear where they intend the drones to be in use, the US Federal Aviation Administration has granted a permit to operate them in the US.

At the conference - ‘Re:Mars’, an event run to highlight Amazon’s work in machine learning, robotics, automation and space - the company was keen to emphasise what is new about the drones they have developed.

Amazon executive Jeff Wilke presented the new technology, stating that “some drones are autonomous but not able to react to the unexpected, relying simply on communications systems for situational awareness”.  Their drone, however, “sees” the surroundings using data from visual, thermal and ultrasonic sensors.  This means it should be “independently safe” as it will avoid objects in its path.

This development may be of interest to Engineering, Computer Science and Mathematics applicants, who could further research the state of drone technology and how it is advancing.  Economics applicants might also consider the role of technology in economic development.

Maya Ackerman, a computer scientist at Santa Clara University in California, has developed a programme that uses data analysis to create songs, producing both the melody and lyrics.

The programme, called ALYSIA, or Automated Lyrical Songwriting Application, uses machine-learning algorithms, which “learn” about how to construct songs through exposure to large data-sets.

Ackerman released ALYSIA as an app at the beginning of this year.  The program generates melodies and lyrics, from which the user picks and then assembles to form a song. The user can also request specific instruments or input a lyric and receive a corresponding melody.  One user who had never played a musical instrument was able to compose an aria for an opera, in Italian.

Ackerman acknowledges the potential controversy around such technology: “Humans have a strong bias against thinking about computers as being creative”.  However, she states that ALYSIA’s function is not to replace human songwriters, but rather to act as a collaborator and inspiration.

She states that she developed the programme out of frustration that she was unable to compose music that she enjoyed listening to.  Regarding this, she says, “The computer has a meaningful role. It does something that I’m no good at.”

Applicants for arts subjects, such as English, History of Art and Music, might consider to what extent we might value art created by machines.  They, along with Engineering applicants, might also reflect on the way in which technology is changing these creative fields.

If you’re not applying for Maths, it may have passed you by that the 14th March was the official Pi day! This year, Google had some incredible news to share, letting it be known that one of its employees Emma Haruka Iwao significantly increased the known numbers of Pi.

Pi is considered irrational because it cannot be expressed as an a/b fraction, where ‘a’ is an integer and ‘b’ is an integer that is not zero. With the help of the Google’s global computing cloud service and a huge a processing effort, Emma has now discovered 31,415,926,535,897 digits i.e. the Pi number of digits of Pi!

The amount of processing power required (the speed at which computer a can run mathematical equations) came to approximately 170 terabytes, which is around the same size as the entire internet in back in the early 2000s. Emma had been interested in Pi since a child, so the achievement is not only an incredible professional achievement, but also a personal one.

Applicants going for Mathematics or Computer Science would be wise to look more into the technical details of how Emma was able to so rapidly expand the known number of digits in Pi.

The British-Lebanese mathematician Sir Michael Atiyah spoke at the Heidelberg Laureate Forum on 24th September.  In a 45 minute talk he claimed to have found a “simple proof” to the Riemann hypothesis, a problem that has remained unsolved since 1859.  Correct proof to support the hypothesis, labelled by the Clay Mathematics Institute as one of the seven “Millenium Prize Problems”, could have huge implications for the majority of modern day cryptography, including cryptocurrencies like Bitcoin.

The hypothesis concerns prime numbers and the ability to find the number of primes smaller than any given integer, N.  The hypothesis relies on the Riemann zeta function and its return of zero.  It is known that zero is returned when a negative integer is used in the function, these are known as trivial zeros.  This is also the case with any complex number whose real part is ½, known as non-trivial zeros.  The non-trivial zeros have varying imaginary units but consistent ½ values, allowing for their calculation.

However, the continuing problem is the lack of proof that complex numbers with a ½ real value are the only form of non-trivial zeros.  Until now this has been assumed to be true and has provided the basis for modern cryptography.  This is due to the property of prime numbers where calculating the product of two primes is simple but finding the two primes used when the only information given is the result is very difficult.  This allows for one-way functions that cannot be easily inversed by those that are not the intended recipient.

But proof of the hypothesis may lead to a connection being observed between prime numbers and this could be exploited to counteract contemporary forms of coding.  This could lead to hash algorithms being easily hacked and bitcoin being mined at an exponentially faster rate. 

Atiyah’s claim of proof is currently met with scepticism but if correct his work could have an enormous impact.  Computer Science and Mathematics applicants can develop their understanding of the Riemann hypothesis and its underpinning of cryptography and its other applications.

How many primes can you name? In March this year mathematician Robert Langlands won the Abel Prize for research showing how concepts from different branches of mathematics all share links to prime numbers. To analyse these numbers mathematicians have to sift through numbers using mathematical filters, eliminating all non-primes. This search has its origins in antiquity; Euclid wrote in 300 BC that “a prime number is that which is measured by the unit alone”, and it was he who proved that the number of primes is infinite. However, it was probably Eratosthenes who first developed the sifting process, which filters out all multiples of 2, 3, 5, and 7—the first 4 primes.

A notable figure in the early history of the study of primes is John Pell, whose urge to categorise and collect useful numbers led him to identify and publish the primes up to 100,000 in the early 1700s. A century later, others had found the primes up to 1 million. As more and more primes were found, the process was made easier by the invention of sliders and stencils to quickly eliminate multiples. However, it was Carl Friedrich Gauss who decided to actually analyse prime numbers, looking for interesting patterns. He found, for example, that the higher he counted, the fewer prime numbers there were. More recently it has been found that, with the exception of 2 and 5, all prime numbers end in 1,3,7, or 9.

Langlands’ research, which has been described as “revolutionary”, is founded on the work of previous mathematicians, in particular Gauss. In the late 18th century he formulated a law of reciprocity whereby certain types of primes share defining characteristics; for example, primes that are the sum of two squares also leave a remainder of 1 when divided by 4. Langlands built on this by proposing that prime numbers encoded in higher-degree equations than simply squares might be in a reciprocal relationship with the branch of mathematics known as harmonic analysis, which is often used in physics.

Applicants for Mathematics may wish to read Langland’s research and look into the contemporary questions in the study of prime numbers. Students wishing to study Physics could familiarise themselves with harmonic analysis and learn about how prime numbers are relevant to physics.

It has long been understood that dolphins are intelligent, social creatures, and that they have their own distinct language that humans can’t understand. Although we can distinguish the different sounds that dolphins make, and understand that each dolphin has a unique call, scientists face struggles when trying to study their communication, due to the difficulty in tracking which dolphin is making which sound and why. However, recently, psychologist and marine mammal scientist Diana Reiss and a group of biophysicists have built a ‘dolphin touchscreen’ in the form of a window into the wall of a pool at the National Aquarium in Baltimore. The researchers project interactive progammes onto it, and optical sensing technology can detect when the window is being touched by the dolphins. The project was inspired by an experiment Reiss conducted in the 1980s with an electronic keyboard with unique symbols on each key. Each key made a dolphinesque whistle when touched, with the idea that dolphins could use the keyboard to make requests of their handlers. When listening to recordings, Reiss noticed that the dolphins were mimicking the sounds made by the keyboard and combining with their own unique sounds.

One of the programmes the team have developed is a dolphin version of ‘whack-a-mole’. In the game, fish swim across the scream and disappear when touched. Within seconds of the screen turning on, the scientists witnessed the dolphin approaching the screen and touching the fish with his melon, or forehead. Motivated by this success and with the 1980s experiment in mind, the team are now developing an app similar to the keyboard. Alongside this the team will use microphones embedded in the walls to record the sounds, and multiple cameras to track the locations of the dolphins. The combination of audio and visual data the team will be able to trace the sounds back to a particular point in the pool and thus a specific dolphin. Data-mining algorithms will then be used to look for patterns in this information. 

Psychology, Biology and Veterinary students should explore our understanding of animal intelligence and consciousness and how technology is allowing us greater insight into this. Physics students can consider how such technology may help us communicate with potential extre-terrestrial life forms as we continue to pursue space exploration. Computer Scientists and Mathematicians can investigate the nature of the programmes and technology used to pursue this research.

The AlphaGo artificial intelligence program has defeated Ke Jie, the human champion of the game Go, in a series of three matches of designed to test its intelligence.

Developed by Alphabet Inc.’s Google’s DeepMind unit, AlphaGo is a computer programme designed to play the ancient Chinese board game. Go is one of the oldest and most complex in the world and involves placing either black or white stones to form territories on the board.

The co-founder and co-CEO of Deep Mind, Demis Hassabis has announced that AlphaGo’s recent triple victory is ‘the highest possible pinnacle’ that the competitive program could have possibly reached and therefore the program will now be retired. According to Mr Hassabis, the research team behind the A.I. program will now go on to use their algorithmical learnings on more complex projects, such as curing diseases, creating new types of materials and solving energy problems.

Many Go competitors are disappointed at this news that AlphaGo will no longer be playing games as they are eager to attempt to beat the machine. The data from the 50 online games that AlphaGo has played, however, will be shared with the Go community, so they can develop their own gameplay. After losing his final match to the computer, Ke Jie proclaimed that the ‘future belongs to A.I.’

Maths students should look at the algorithms used by the AlphaGo and Computer Science students would be wise to investigate zero-player games. Those going to study other logic based subjects should investigate the reasoning pattern employed by the game.

The US have slipped as a progressive nation for women – moving from 23rd place to 45th place this year in the WEF’s Global Gender Gap Report.

The report, established in 2006, compares the national, annual average income for men and women as one measure of equality. The US’s slip perhaps can be down to a chance in how the WEF recorded income; prior to this year, they measured incomes up to and including $40,000 as they believed that income above $40,000 doesn’t have a meaningful impact on someone’s quality of life. They now believe, however, that this threshold should be $75,000. Mathematics and Statistics students should consider how changes in the collection of data allow us to make meaningful year-by-year comparisons.

The fall of the US isn’t solely down to the change in measurement, however; women’s participation in the labour force has decrease, and “is stagnating among legislators, senior officials and managers.” HSPS and PPE applicants should consider how useful income is as a measure of gender equality.

Reaching the top of the table were the Nordic countries of Iceland, Finland, Norway and Sweden, which plays into the general conception of these countries as liberal and progressive. Geography students should consider perhaps the more surprising fifth place entry, Rwanda, and why they might have pay parity.

After performance enhancing drugs were almost eradicated from baseball in the early 2000s, far fewer people were hitting home runs – but this trend has reversed.

Research from Penn State University looked in to the trend of baseball players skewing increasingly heavier than in previous decades. Using self-reported heights and weights, researchers found that 70% of players between 1991 and 2015 had BMIs that classified them as overweight or obese, but before this, the average was between 30 and 40%.

Biological Sciences and Medicine applicants should note the flaw with using BMI as a measure of obesity, as by itself, you cannot determine the distribution of muscle versus fat. Nevertheless, it does make logical sense that a heavier weight behind a hit will lead to the ball being propelled further.

Physics students will be familiar with the formula k=(1/2)mv2  where m is the mass of the system and v is the velocity. In theory, a heavier batter will therefore hit the ball further than a smaller man with the same strength. However, there are many variables to consider including momentum and power which Natural Sciences (P) and Mathematics applicants would do well to investigate further.

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