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Stalking E.T.

There are over 100 billion galaxies in our universe. Each galaxy has billions of stars. Each star could have a planet. Planets can breathe life. Alessio Magro writes about his experience hunting for E.T. Illustrations by Sonya Hallett

In 1982, 4 years before I was born, the world fell in love with Spielberg’s E.T. the Extra-Terrestrial. Fifteen years later, the movie Contact, an adaptation of Carl Sagan’s novel, hit the big screen. Although at the time I was too young to appreciate the scientific, political, and religious themes I was captivated and it fired my thoughts. I questioned whether we are alone in this vast space. What would happen if E.T. does call? Are we even listening? If so, how? And, is it all a waste of time and precious money? Instead of deflating me, these questions inspired me to start a journey that led me to my collaboration with SETI, the Search for Extra Terrestrial Intelligence. I participated in ongoing efforts to try and find intelligent civilisations on other worlds.

The debate on whether we are alone started ages ago. It was first debated in Thales, Ancient Greece. Only recently has advanced technology allowed us to try and open up communication channels with any existing advanced extraterrestrial civilisations. If we do not try we will never answer this question.

For the past fifty years we have been scanning the skies using large radio telescopes and listening for signals which cannot be generated naturally. The main assumption is that any advanced civilisation will follow a similar technological path as we did. For example, they will stumble upon radio communication as one of the first wireless technologies.

SETI searches are usually in the radio band. Large telescopes continuously scan and monitor vast patches of the sky. Radio emissions from natural sources are generally broadband, encompassing a vast stretch of the electromagnetic spectrum — waves from visible light to microwaves and X-rays — whilst virtually all human radio communication has a very narrow bandwidth, making it easy to distinguish between natural and artificial signals. Most SETI searches therefore focus on searching for narrow band signals of extraterrestrial origin.

Narrow bands are locked down by analysing a telescope’s observing band — the frequency range it can detect. This frequency range is broken down into millions or billions of narrow frequency channels. Every channel is searched at the same time. SETI searches for sharp peaks in these small channels. This requires a large amount of computational resources, such as supercomputing clusters, specialised hardware systems, or through millions of desktop computers. The infamous SETI@home screen-saver extracted computer power from desktops signed up to the programme, which started as the millennium turned.

E.T. civilisations might also transmit signals in powerful broadband pulses. This means that SETI could search for wider signal frequencies. However, they are more difficult to tease apart from natural emissions, so they require more thorough analysis. The problem is that as broadband signals — natural or otherwise — travel through interstellar space they get dispersed, resulting in higher frequencies arriving at the telescope before lower ones, even though they both were emitted at the same time. The amount of dispersion, the dispersion gradient, depends on the distance between the transmitter and receiver. The signal can only be searched after this effect is accounted for by a process called dedispersion. To detect E.T. signs, thousands of gradients have to be processed to try out all possible distances. This process is nearly identical to that used to search for pulsars, which are very dense, rapidly rotating stars emitting a highly energetic beam at its magnetic poles. Pulsars appear like lighthouses on telescopes, with a regular pulse across the entire observation band.

For the past four years I have been developing a specialised system which can perform all this processing in real-time, meaning that any interesting signals will be detected immediately. Researchers now do not need to wait for vast computers to process the data. This reduces the amount of disk space needed to store it all. It also allows observations to be made instantaneously, hence reducing the risk of losing any non-periodic, short duration signals. To tackle the large computational requirements I used Graphics Processing Units (GPUs) — typically unleashed to work on video game graphic simulations — because a single device can perform tasks of at least 10 laptops. This system can be used to study pulsars, search for big explosions across the universe, search for gravitational waves, and for stalking E.T..

The Electromagnetic Spectrum. Higher frequencies mean higher energies but shorter wavelengths. X-rays and Gamma rays are on the higher end of the spectrum making them so dangerous.

E.T. we love you

Hunting for planets orbiting other stars, known as exoplanets, has recently become a major scientific endeavour. Over 3,500 planet-candidates were found by the Kepler telescope that circles our planet, about 961 are confirmed. Finding so many planets is now leading scientists to believe that the galaxy is chock-full of them. The current estimate: 100 billion in our galaxy, with at least one planet per star. For us E.T. stalkers, this is music to our ears.

Life could be considered inevitable. However, not all planets can harbour life, or at least life as we know it. Humans need liquid water and a protective atmosphere, amongst other things. Life-supporting planets need to be approximately Earth-sized and orbit within its parent star’s habitable zone. This Goldilocks zone is not too far away from the sun, freezing the planet, or too close to it, frying it. These exoplanets are targeted by SETI searches, which perform long duration observations of exoplanets similar to Earth.

“The big question is: where do we look for E.T.? I would prefer rephrasing to: at which frequency do we listen for E.T.?”

By focusing on these planets, SETI is gambling. They are missing huge portions of the sky to focus on areas that could yield empty blanks. SETI could instead perform wide-field surveys which search large chunks of the sky for any interesting signals. Recent development in radio telescope technology allows for the instantaneous observation of the entire sky, making 24/7 SETI monitoring systems possible. Wide-field surveys lack the resolution needed to figure out where a signal would come from, so follow-up observations are required. Anyhow, a one-off signal would never be convincing.

For radio SETI searches, the big question is: where do we look for E.T.? I would prefer rephrasing to: at which frequency do we listen for E.T.? Imagine being stuck in traffic and you are searching for a good radio station without having a specific one in mind. Now imagine having trillions of channels to choose from and only one having good reception. One would probably give up, or go insane. Narrowing down the range of frequencies at which to search is one of the biggest challenges for SETI researchers.

The Universe is full of background noise from naturally occurring phenomena, much like the hiss between radio stations. Searching for artificial signals is like looking for a drop of oil in the Pacific Ocean. Fortunately, there exists a ‘window’ in the radio spectrum with a sharp noise drop, affectionately called the ‘water hole’. SETI researchers search here, reasoning that E.T. would know about this and deliberately broadcast there. Obviously, this is just guesswork and some searches use a much wider frequency range.

Two years ago we decided to perform a SETI survey. Using the Green Bank Telescope in West Virginia (USA), the world’s largest fully steerable radio dish, we scanned the same area the Kepler telescope was observing whilst searching for exoplanets. This area was partitioned into about 90 chunks, each of which was observed for some time. In these areas, we also targeted 86 star systems with Earth-sized planets. We then processed around 3,000 DVDs worth of data to try and find signs of intelligent life. We developed the system ourselves at the University of Malta, but we came out empty handed.

A camera shy E.T.

Should we give up? Is it the right investment in energy and resources? These questions have plagued SETI from the start. Till now there is no sign of E.T., but we have made some amazing discoveries while trying to find out.

Radio waves were discovered and entered into mainstream use in the late 19^th century. We would be invisible to other civilisations unless they are up to 100 light years away. Light (such as radio) travels just under 9.5 trillion kilometres per year. Signals from Earth have only travelled 100 light years, broadcasts would take 75,000 years to reach the other side of our galaxy. To compound the problem, technology advances might soon make most radio signals obsolete. Taking our own example, aliens would have a very small time window to detect earthlings. The same reasoning works the other way, E.T. might be using technologies which are too advanced for us to detect. As the author Arthur C. Clarke stated, ‘any sufficiently advanced technology is indistinguishable from magic’.

The Wow! signal is a brief, strong radio burst of unknown origin detected by the Big Ear Telescope, SETI search, 1977. If it originated from deep space, it could either be a new astrophysical phenomena or an alien signal.

At the end of the day, it is all a probability game, and it is a tough one to play. Frank Drake and Carl Sagan both tried. They came up with a number of factors that influence the chance of two civilisations communicating. One is that we live in a very old universe, over 13 billion years old, and for communication between civilisations their time windows need to overlap. Another factor is, if we try to detect other technological signatures they might also be obsolete for advanced alien life. Add to these parts, the assumed number of planets in the Universe and the probability of an intelligent species evolving. For each factor, several estimates have been calculated. New astrophysical, planetary, and biological discoveries keep fiddling with the numbers that range from pessimistic to a universe teeming with life.

The problem with a life-bloated galaxy is that we have not found it. Aliens have not contacted us, despite what conspiracy theorists say. There is a fatalistic opinion that intelligent life is destined to destroy itself, while a simpler solution could be that we are just too damned far apart. The Universe is a massive place. Some human tribes have only been discovered in the last century, and by SETI standards they have been living next door the whole time. The Earth is a grain of sand in the cosmic ocean, and we have not even fully explored it yet.

“Signals from Earth have only travelled 100 light years, broadcasts would take 75,000 years to reach the other side of our galaxy”

Still, the lack of alien chatter is troubling. Theorists have come up with countless ideas to explain the lack of evidence for intelligent alien existence. The only way to solve the problem is to keep searching with an open mind. Future radio telescopes, such as the Square Kilometre Array (SKA), will allow us to scan the entire sky continuously. They require advanced systems to tackle the data deluge. I am part of a team working on the SKA and I will do my best to make this array possible. We will be stalking E.T. using our most advanced cameras, and hopefully we will catch him on tape.

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Carl Sagan’s Cosmos

Exoplanets Galore

The Sky’s Limits

Europe has a dream: a single European sky. By unifying its air traffic it wants to clean up its skies and make them safer. To find out how Dr Sedeer El-Showk interviewed researchers at the University of Malta

Every day around 30,000 aircraft take to Europe’s skies. Choreographing this airborne dance is daunting. At the moment, it is orchestrated by the disparate air traffic management systems of each European country, with control handed over at border crossings. The aeronautics research team at the University of Malta is part of an ambitious EU project to change that by establishing a single European sky, enabling EU air traffic controllers to manage increasing amounts of traffic with greater safety, lower costs, and a reduced environmental impact.

A passion for flight

Ask Prof. Ing. David Zammit-Mangion (Department of Electronic Systems Engineering, UoM) what he loves and he will reply, ‘anything that flies’. He has come a long way since his childhood dreams of flight, when he would build model aeroplanes and scamper over fences to photograph real ones. Now he leads a major research team with an important role in Clean Sky, the EU’s €1.6 billion flagship project which aims to reduce the environmental impact of air transport.

The enthusiasm for flying never left Zammit-Mangion. As an adult, he eventually took to the skies himself, learning to fly during his doctoral research at Cranfield University in the UK, where he designed a cockpit instrument to monitor the take-off performance of aircraft. ‘My dream was to twin my passion with my profession,’ he said. It is a formula that has worked. Zammit-Mangion’s familiarity with commercial operations, safety procedures, and aircraft equipment has given his research an edge by enabling him to quickly estimate the cost and feasibility of different approaches. ‘When it comes to addressing problems, you need to have a very broad understanding of the whole industry,’ he says, and his hands-on industrial experience and hours logged in the cockpit have proven invaluable. Clean Sky is central to meeting the environmental goals embedded in the vision of a unified European sky. Launched in 2008, its goal is to reduce the excess noise and greenhouse gas emissions created by aeroplanes. Air transport is responsible for around 2% of global carbon dioxide (CO₂) emissions, but traffic is expected to more than double by 2030. By improving air traffic management (ATM) and aircraft technology, the 600-member Clean Sky project aims to ensure that emissions increase at a slower rate than demand.

Clearing the air

Aeroplanes currently follow flight paths through set air corridors, which can make routes unnecessarily long. They also may have to climb or descend in stages and wait in a holding pattern at their destination. These inefficient practices increase the amount of fuel used, leading to higher costs and greater greenhouse gas emissions. Each kilogram of jet fuel burned releases roughly three kilograms of CO₂ into the atmosphere, along with other greenhouse gases like nitrogen oxides. This happens high in the atmosphere, where these gases end up taking part in a variety of physical and chemical processes that cause them to have a greater environmental impact than they would closer to the ground. Given that many airliners burn around 50 kg of fuel per minute, even relatively small optimisations can have a significant impact.

“Each kilogram of jet fuel burned releases three kilograms of CO₂ into the atmosphere, along with other greenhouse gases like nitrogen oxides”

Improving air travel routes is not a simple task. It is what engineers call a ‘multi-criterion, multi-parameter problem’. In other words, you have to balance lots of factors, like the type and mass of the aeroplane, weather conditions, route limitations, and air traffic control constraints. At the same time, you need to maximise performance on different objectives such as fuel use, flight time, and environmental impact. Zammit-Mangion describes it as ‘a very complex mathematical problem’. That sort of complexity might sound like a nightmare to most people, but it is just the sort of thing Ing. Kenneth Chircop thrives on. ‘My real love is for engineering mathematics,’ said Chircop. He studied engineering for his degree, but then his passion for mathematical challenges drove him to join the aeronautics research team. ‘At the end of the day, I wanted to do something heavy in mathematics again.’ As their contribution to Clean Sky, the team developed a software package called Green Aircraft Trajectories under ATM Constraints (GATAC) to help optimise flight routes. Instead of just performing a single optimisation, GATAC provides an optimisation framework which aircraft operators can use with their own models. By plugging in models of aircraft and engine performance, emissions levels, noise production, and so on, users can work out optimal air travel trajectories to match their constraints and conditions. The core software developed at UoM incorporates various models from different research partners, but users are also free to plug in their own models. Aircraft manufacturer Airbus uses GATAC with its own proprietary models. ‘It’s great to see that foreign partners look at us as equals,’ said Chircop. ‘They trust us to develop state-of-the-art technology. We have delivered, and they trust us to keep delivering. We’re really proud of that; it’s what makes us tick and want to do more.’

Air traffic over Europe. Courtesy of Flightradar.com

Bringing it home

This work has brought more than just international recognition to Malta; the country will also enjoy practical benefits. Kenneth Chircop is spear-heading Clean Flight — a national research project financed by the Malta Council for Science and Technology’s national research and innovation programme 2011 — to apply the lessons from Clean Sky to Maltese airspace. ‘Our impact on the national scene can be remarkable,’ said Chircop, describing the gains to be made by optimising the arrival and departure routes aeroplanes use at Malta airport. As an island nation, Malta relies heavily on air traffic to connect it to the rest of the world. In 2013, Malta International Airport saw over 30,000 arrivals and departures, up from roughly 26,000 only seven years ago. Despite this, its air traffic systems need an overhaul; while the technology is state-of-the-art, some of the procedures are out of date. For example, aeroplanes arriving and departing from an airport follow standard, published routes, called STARs (Standard Terminal Arrival Route) and SIDs (Standard Instrument Departures) respectively, which can simplify airspace management. ‘The SIDs in Maltese airspace were designed years ago when fuel was relatively cheap, and the impact combustion made on the environment was not given due importance,’ said Chircop, ‘and we don’t even have STARs.’ Updating these procedures presented a clear opportunity to reduce fuel use and greenhouse gas emissions in Maltese airspace. Together with their partner, Maltese aeronautics consultancy company QuAero Ltd, Chircop, Zammit-Mangion, and the rest of the team analysed the flight paths taken by aircraft in Maltese airspace and discovered that they were scattered and inefficient. They developed a tool to design and analyse the best arrival and departure routes for aeroplanes, which they used to calculate revised routes for Malta’s airport. Based on fuel savings estimates for the Boeing 737 and Airbus A320, the two most common aircraft in Maltese airspace, the new routes could save 465 tonnes of fuel for departing aircraft and 200 tonnes for arrivals every year. The fuel reductions mean less money spent and lower CO₂ emissions in Maltese airspace. Not only does that directly benefit Malta’s environment, but it also offers indirect benefits by reducing the pressure on Malta’s carbon emission caps. In addition to improving the course followed by flights, the team has helped improve climbs and descents. Planes can approach the airport in many different ways: for example, a smooth, continuous descent, a series of steps interrupted by level flight, or a close approach at full altitude followed by a quick descent. Determining which approach is optimal is a dynamic problem that has to factor in the weight of aeroplane and its cargo, weather conditions, operational constraints, air traffic and so forth. Current optimisation methods try to balance flight time and fuel use, but do not take the other factors into account. The Clean Flight team developed a new approach using computer algorithms which can improve the efficiency of climbs and descents in around 10 minutes on a single computer. ‘So 15 minutes before departure, for example, an air traffic controller can calculate the optimal route for the flight at the current conditions,’ said Chircop. Altogether, this work could save 1,500 tonnes of fuel every year.

Upwards and onwards

The sky is the limit for this aeronautics team. As Clean Sky winds to a close, the EU is preparing to launch Clean Sky 2, and the UoM team will probably continue to play a significant role in the initiative. On the national front, the optimisation system developed in the Clean Flight project will be tested with actual flight trials over the coming months – a major step forward in a field where such tests are incredibly expensive and safety is always a paramount concern. According to Chircop, it is an indication that the potential benefits are large. ‘We’re pushing to get this technology into the field so we can see it making actual gains, instead of simply on paper,” he said. Meanwhile, the GATAC software package is already being used by key industrial players, according to Zammit-Mangion. Looking forward, it clearly has a scope beyond Clean Sky, and may even come to be used by other industries like maritime shipping, which faces similar problems. The team is also working on a project to test unmanned aerial vehicles (UAV) flying with commercial aircraft in an air traffic control environment. Although the UAV tech was developed in Italy, the Maltese team will test its operational aspects. If successful, the project could open the door to the integration of UAVs into the wider aviation community. The aeronautics team has put Malta on the map when it comes to aviation research, a major accomplishment for a nation with no significant track record in the field until ten years ago. ‘We’re well-established and recognised in European and global research circles,’ said Zammit-Mangion, describing the team’s success. With the network of partners they have built up and the quality of the team’s research, the future is looking up.

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Dr Sedeer El-Showk is a freelance science writer. He blogs at Inspiring Science and for Nature’s Scitable network.

Documentary on Maltese researchers by Science in the City

aeroplane air transport airplane Andrew Sammut carbon dioxide Clean Flight Clean Sky Cranfield University David Zammit-Mangion Environment greenhouse gas emissions Kenneth Chircop malta nitrogen dioxide QuAero Ltd university of malta

A Good Cause for Research

Why should public, private, and non-profit entities invest in research? Several reasons exist.

Firstly, research is key for our future. Research helps drive new knowledge that will improve the world. Society depends on research, across a wide range of disciplines, to strengthen our quality of life and sustain economic stability. By raising funds for University research the RIDT is surely not trying to reinvent the wheel. On the contrary, throughout Europe, the US and Asia public universities are enhancing their Government funding through various initiatives to sustain important research. Universities all across the globe appeal to public entities, private individuals and NGOs to fund research and invest in our society’s future.

Locally, we have just started scraping the surface of fundraising for research. Recently, the RIDT received a number of important donations which shall serve to continue fostering local research. In the first of its kind, we received €55,000 from local NGO ‘Action for Breast Cancer Foundation’ (ABCF), raised through the ALIVE Cycling Challenge. They are being used to launch a Ph.D. studentship in breast cancer research. The Lifecycle Foundation has also donated €70,000 towards kidney disease research. These NGOs have followed a stream of public and private entities, as well as students, who have been donating money for research for the last three years.

Secondly, don’t you want to be part of something bigger? You probably cannot find the cure for cancer yourself, but everyone can contribute to make that a possibility. As the University’s Research Trust, we do not only want to attract big corporate companies or NGOs to donate money, but we also want you — the students, the alumni, the professionals, the workers, the parents, to realise that donating for research is a noble cause. A recent Christmas campaign at the University of Malta that was spearheaded by KSU, the UoM staff and the Chaplaincy managed to raise €12,000 from students, staff, and academics on campus. A third of these funds were donated to the RIDT, which were devolved to the Department of Anatomy. They will be invested in specialised research projects focusing on specific strands of cancer, such as leukaemias, sarcomas, brain tumours, breast and colon cancer.

Research affects our day-to-day lives. Though research discoveries take time and need constant investment to benefit our society, we can come together as a Maltese community by investing in research for good causes. Ultimately, let us imagine a world where we have cured all major diseases, where we can move objects with our thoughts, and unravel the mysteries of the universe.Imagine, and let’s make it happen!

RIDT is the University’s Research Trust aimed towards fostering awareness and fundraising for high-calibre local research. We aim to achieve this by raising funds for various research projects undertaken at the University of Malta. Please visit www.ridt.eu to donate and our Facebook page on www.facebook.com/RIDTMalta for more information about our latest events and initiatives.

#research donation good cause lifecycle malta Mario Cachia ngo RIDT university of malta

Do we live our wishes when dreaming?

Made infamous by Sigmund Freud, the idea is that we spend one third of our lives dreaming about what we would like to do. Our rational brain suppresses these feelings.

On the other extreme, our brain is just as active in certain sleep stages. These neural firings express themselves in dreams. There are no deep hidden emotions behind them.

Somewhere in between lie recent studies that show that dreams are important in memory, learning and emotions. If you sleep without dreaming these qualities will suffer. For example, rat studies in 2001 showed how while dreaming they replayed solutions to mazes to commit them to their long-term memory.

Send your questions to think@um.edu.mt and we’ll find out if it’s the truth or just a fib!

2014 dream fact fiction malta sleep think university of malta

Decoding Language

Maltese needs to be saved from digital extinction. Dr Albert Gatt, Prof. Gordon Pace, and Mike Rosner write about their work making digital tools for Maltese, interpretting legalese, and making a Maltese-speaking robot

In 2011 an IBM computer called Watson made the headlines after it won an American primetime television quiz called Jeopardy. Over three episodes the computer trounced two human contestants and won a million dollars.

Jeopardy taps into general world knowledge, with contestants being presented with ‘answers’ to which they have to find the right questions. For instance, one of the answers, in the category “Dialling for Dialects”, was: While Maltese borrows many words from Italian, it developed from a dialect of this Semitic language. To which Watson correctly replied with: What is Arabic?

Watson is a good example of state of the art technology that can perform intelligent data mining, sifting through huge databases of information to identify relevant nuggets. It manages to do so very efficiently by exploiting a grid architecture, which is a design that allows it to harness the power of several computer processors working in tandem.

“Maltese has been described as a language in danger of ‘digital extinction’”

This ability alone would not have been enough for it to win an American TV show watched by millions. Watson was so appealing because it used English as an American would.

Consider what it takes for a machine to understand the above query about Maltese. The TV presenter’s voice would cause the air to vibrate and hit the machine’s microphones. If Watson were human, the vibrations would jiggle the hairs inside his ear so that the brain would then chop up the component sounds and analyse them into words extremely rapidly. The problem for a computer is that there is more to language than just sounds and words. A human listener would need to do much more. For example, to figure out that ‘it’ in the question probably refers to ‘Maltese’ (rather than, say, ‘Italian’, which is possible though unlikely in this context). They would also need to figure out that ‘borrow’ is being used differently than when one says borrowing one’s sister’s car. After all, Maltese did not borrow words from Italian on a short-term basis. Clearly the correct interpretation of ‘borrow’ depends on the listener having identified the intended meaning of ‘Maltese’, namely, that it is a language. Watson was equipped with Automatic Speech Recognition technology to do exactly that.

To understand language any listener needs to go beyond mere sound. There are meanings and structures throughout all language levels. A human listener needs to go through them all before saying that they understood the message.

Watson was not just good at understanding; he was pretty good at speaking too. His answers were formulated in a crisp male voice that sounded quite natural, an excellent example of Text-to-Speech synthesis technology. In a fully-fledged human or machine communicating system, going from text to speech requires formulating the text of the message. The process could be thought of as the reverse of understanding, involving much the same levels of linguistic processing.

Machine: say ‘hello’ to Human

The above processes are all classified as Human Language Technology, which can be found in many devices. Human Language Technology can be found everywhere from Siri or Google Now in smart phones to a word processing program that can spell, check grammar, or translate.

Human-machine interaction relies on language to become seamless. The challenge for companies and universities is that, unlike artificial languages (such as those used to program computers or those developed by mathematicians), human languages are riddled with ambiguity. Many words and sentences have multiple meanings and the intended sense often depends on context and on our knowledge of the world. A second problem is that we do not all speak the same language.

Breaking through Maltese

Maltese has been described as a language in danger of ‘digital extinction’. This was the conclusion of a report by META-NET, a European consortium of research centres focusing on language technology. The main problem is a lack of Human Language Technology — resources like word processing programs that can correctly recognise Maltese.

Designing an intelligent computer system with a language ability is far easier in some languages than it is in others. English was the main language in which most of these technologies were developed. Since researchers can combine these ready-made software components instead of developing them themselves, it allows them to focus on larger challenges, such as winning a million dollars on a TV program. In the case of smaller languages, like Maltese, the basic building blocks are still being assembled.

Perhaps the most fundamental building block for any language system is linguistic data in a form that can be processed automatically by a machine. In Human Language Technology, the first step is usually to acquire a corpus, a large repository of text or speech, in the form of books, articles, recordings, or anything else that happens to be available in the correct form. Such repositories are exploited using machine-learning techniques, to help systems grasp how the language is typically used. To return to the Jeopardy example, there are now programs that can resolve pronouns such as ‘it’ to identify their antecedents, the element to which they refer. The program should identify that ‘it’ refers to Maltese.

For the Maltese language, researchers have developed a large text/speech repository, electronic lexicons (language’s inventory of its basic units of meaning), and related tools to analyse the language (available for free). Automatic tools exist to annotate this text with basic grammatical and structural information. These tools require a lot of manual work however, once in place, they allow for the development of sophisticated programs. The rest of this article will analyse some of the on-going research using these basic building blocks.

From Legalese to Pets

Many professions benefit from automating tasks using computers. Lawyers and notaries are the next professionals that might benefit from an ongoing project at the University of Malta. These experts draft contracts on a daily basis. For them, machine support is still largely limited to word processing, spell checking, and email services, with no support for a deeper analysis of the contracts they write and the identification of their potential legal consequences, partly through their interaction with other laws.

Contracts suffer from the same challenges when developing Human Language Technology resources. A saving grace is that they are written in ‘legalese’ that lessens some problems. Technology has advanced enough to allow the development of tools that analyse a text to enable extraction of information about the basic elements of contracts, leaving the professional free to analyse the deeper meaning of these contracts.

Deeper analysis is another big challenge in contract analysis. It is not restricted to just identifying the core ‘meaning’ or message, but needs to account the underlying reasoning behind legal norms. Such reasoning is different from traditional logic, since it talks about how things should be as opposed to how they are. Formal logical reasoning has a long history, but researchers are still trying to identify how one can think precisely about norms which affect definitions. Misunderstood definitions can land a person in jail.

Consider the following problem. What if a country legislates that: ‘Every year, every person must hand in Form A on 1^st January, and Form B on 2^ndJanuary, unless stopped by officials.’ Exactly at midnight between the 1^st and 2^nd of January the police arrest John for not having handed in Form A. He is kept under arrest until the following day, when his case is heard in court. The prosecuting lawyer argues that John should be found guilty because, by not handing in Form A on 1^st January he has violated the law. The defendant’s lawyer argues that, since John was under arrest throughout the 2^nd of January he was being stopped by officials from handing in Form B, absolving him of part of his legal obligation. Hence, he is innocent. Who is right? If we were to analyse the text of the law logically, which version should be adopted? The logical reasoning behind legal documents can be complicated, which is precisely why tools are needed to support lawyers and notaries who draft such texts.

Figuring out legal documents might seem very different to what Watson was coping with. But there is an important link: both involve understanding natural language (normal every day language) for something, be it computer, robot, or software, to do something specific. Analysing contracts is different because the knowledge required involves reasoning. So we are trying to wed recent advances in Human Language Technology with advances in formal logical reasoning.

Contract drafting can be supported in many ways, from a simple cross-referencing facility, enabling an author to identify links between a contract and existing laws, to identifying conflicts within the legal text. Since contracts are written in a natural language, linguistic analysis is vital to properly analyse a text. For example in a rent contract when making a clause about keeping dogs there would need to be a cross-reference to legislation about pet ownership.

We (the authors) are developing tools that integrate with word processors to help lawyers or notaries draft contracts. Results are presented as recommendations rather than automated changes, keeping the lawyer or notary in control.

Robots ’R’ Us

So far we have only discussed how language is analysed and produced. Of course, humans are not simply language-producing engines; a large amount of human communication involves body language. We use gestures to enhance communication — for example, to point to things or mime actions as we speak — and facial expressions to show emotions. Watson may be very clever indeed, but is still a disembodied voice. Imagine taking it home to meet the parents.

“Robby the Robot from the 1956 film Forbidden Planet, refused to obey a human’s orders”

Robotics is forging strong links with Human Language Technology. Robots can provide bodies for disembodied sounds allowing them to communicate in a more human-like manner.

Robots have captured the public imagination since the beginning of science fiction. For example, Robby the Robot from the 1956 film Forbidden Planet, refused to obey a human’s orders, a key plot element. He disobeyed because they conflicted with ‘the three laws of robotics’, as laid down by Isaac Asimov in 1942. These imaginary robots look somewhat human-shaped and are not only anthropomorphic, but they think and even make value judgements.

Actual robots tend to be more mundane. Industry uses them to cut costs and improve reliability. For example, the Unimate Puma, which was designed in 1963, is a robotic arm used by General Motors to assemble cars.

The Puma became popular because of its programmable memory, which allowed quick and cheap reconfiguration to handle different tasks. But the basic design was inflexible to unanticipated changes inevitably ending in failure. Current research is closing the gap between Robby and Puma.

Opinions may be divided on the exact nature of robots, but three main qualities define a robot: one, a physical body; two, capable of complex, autonomous actions; and three, able to communicate. Very roughly, advances in robotics push along these three highly intertwined axes.

At the UoM we are working on research that pushes forward all three, though it might take some time before we construct a Robby 2. We are developing languages for communicating with robots that are natural for humans to use, but are not as complex as natural languages like Maltese. Naturalness is a hard notion to pin down. But we can judge that one thing is more or less natural than another. For example, the language of logic is highly unnatural, while using a restricted form of Maltese would be more natural. It could be restricted in its vocabulary and grammar to make it easier for a robot to handle.

Take the language of a Lego EV3 Mindstorms robot and imagine a three-instruction program. The first would be to start its motors, the second to wait until light intensity drops to a specific amount, the third to stop. The reference to light intensity is not a natural way to communicate information to a robot. When we talk to people we are not expected to understand how the way we put our spoken words relates to their hardware. The program is telling the robot to: move forward until you reach a black line. Unlike the literal translation, this more natural version employs concepts at a much higher level and hence is accessible to anybody with a grasp of English.

The first step is to develop programs that translate commands spoken by people into underlying machine instructions understood by robots. These commands will typically describe complex physical actions that are carried out in physical space. Robots need to be equipped with the linguistic abilities necessary to understand these commands, so that we can tell a robot something like ‘when you reach the door near the table go through it’.

To develop a robot that can understand this command a team with a diverse skillset is needed. Language, translation, the robot’s design and movement, ability to move and AI (Artificial Intelligence) all need to work together. The robot must turn language into action. It must know that it needs to go through the door, not through the table, and that it should first perceive the door and then move through it. A problem arises if the door is closed so the robot must know what a door is used for, how to open and close it, and what the consequences are. For this it needs reasoning ability and the necessary physical coordination. Opening a door might seem simple, but it involves complex hand movements and just the right grip. Robots need to achieve complex behaviours and movements to operate in the real world.

The point is that a robot that can understand these commands is very different to the Puma. To build it we must first solve the problem of understanding the part of natural language dealing with spatially located tasks. In so doing the robot becomes a little bit more human.

A longer-term aim is to engage the robot in two-way conversation and have it report on its observations — as Princess Leia did with RT-D2 in Star Wars, if RT-D2 could speak.

Language for the World

Human Language Technologies are already changing the world. From automated announcements at airports, to smartphones that can speak back to us, to automatic translation on demand. Human Language Technologies help humans interact with machines and with each other. But the revolution has only just begun. We are beginning to see programs that link language with reasoning, and as robots become mentally and physically more adept the need to talk with them as partners will become ever more urgent. There are still a lot of hurdles to overcome.

To make the right advances, language experts will need to work with engineers and ICT experts. Then having won another million bucks on a TV show, a future Watson will get up, shake the host’s hand, and maybe give a cheeky wink to the camera.

2014 albert gatt artificial intelligence decoding language faculty of ict forbidden planet gordon pace human-machine interaction it malta maltese language maltese-speaking mike rosner robby the robot Think Magazine Think Website university of malta UoM

Flying in the face of Neurodegeneration

Fruit flies are not human. Yet they are close enough to have been used for over 100 years by scientists to find out more about humans. Dr Ruben J. Cauchi writes about his relationship with the fly. He uses it to find out how to stop Alzheimer’s disease, Parkinson’s disease, and Motor Neuron Disease that affect tens of millions

It was a cold and grey February afternoon. Snowflakes were pelting the dreaming spires of Oxford. This gloomy weather did nothing to impede the warmth and buzz exuding from the laboratories crammed in the iconic Sherrington building. Less than a century earlier, this labyrinthine edifice was the habitat of Sir Charles Sherrington whose experiments shaped our understanding of the ‘synapse’ or the minute gaps between one brain cell (neuron) and another. The Sherrington building (part of the Department of Physiology, Anatomy, and Genetics at Oxford University) has undergone several expansions over the years. In its newest wing, nowadays it houses the research group of Dr Ji-Long Liu, a rising star in the field of genetics and cell biology.

For me, this was no ordinary afternoon. Together with Liu’s lab teammates, I was perched on a stereomicroscope whilst holding a delicate brush in my hands. On one side was a tray jammed with vials populated with fruit flies and the usual good strong cuppa. Fruit flies are no house flies: each adult fly is only a few millimetres long, their beautiful bodies are pale with black zebra-like stripes and their eyes a bright apple-red colour. I grabbed a vial, fired a puff of carbon dioxide gas through its fluffy plug and then firmly rapped the upended vial to shake its sleepy occupants onto an illuminated pad. I took a deep breath before peering at them through the eyepieces.

At the time, I was more than mid-way through my doctoral studies, and the results of my experiments were far from extraordinary. I was researching the most common genetic killer of human infants, a neuromuscular degenerative disease known as spinal muscular atrophy or SMA in short. I was exploiting the tiny fruit fly to gain new insight into this catastrophic disease.

I decided to up my efforts by generating a series of mutants or faults in Gemin3, the gene that I was investigating. I was targeting these mutants to different organs such as brain, muscle, or gut. The results of this screen were due today. With a few flicks, I deftly flipped and sorted the minuscule fly bodies into neat piles taking note of differences that are invisible to the untrained eye. The mutants did not produce any dramatic effect. Damn! Another experiment down the drain! Frustrated by the result, I mistakenly knocked over a vial, dislodging its plug. Usually, released flies would happily escape by flying. Strangely, my flies were jumping as if attempting flight but just couldn’t make it into the air — an unexpected but interesting trait or phenotype. I checked the tag on the vial. In these flies the mutant was targeted to that part of the body that powers movement, the so-called ‘motor unit’. Following that afternoon, which will remain forever etched in my memory, the results just flowed in and a few months down the line I would find myself donning my subfusc (Oxford-speak for academic dress) to defend my doctorate.

Fly Superstar

The rise to biological stardom for the fruit fly, scientifically known as Drosophila melanogaster, began in 1907 when my great-great-grandfather (by academic lineage) Thomas Hunt Morgan adopted this organism to understand heredity or genetics. Morgan was the first to harness the major advantages of working with this organism: they have an insatiable sexual appetite and a speedy development (only 10 days) from embryo to adult. This means that large-scale experiments are doable in record time. Morgan’s infamous ‘Fly Room’ at Columbia University in New York set the stage for a new ‘religion’ practiced and preached across the globe.

Morgan spent years searching unsuccessfully for flies with clear, heritable differences so that he could investigate how they are inherited. A breakthrough happened in April 1910 when he discovered his first mutant, a white-eyed male fly amongst many red-eyed flies. Morgan took great care of this special fly: he kept it in a bottle and after a day’s lab work he used to take it home! At the same time his wife Lilian, who also became a famous geneticist, gave birth to a child. And such was the excitement surrounding Morgan’s discovery that on his first visit to the hospital, Morgan’s wife said: ‘How’s the fly?’ To which, Morgan replied: ‘How’s the baby?’.

When the white-eyed fly was bred or crossed with a virgin red-eyed female, their offspring were all red-eyed. When sisters and brothers were crossed, half of the male progeny gained back their white-eye colour. This hereditary pattern is typical for a sex-linked (recessive) variation, since the gene for eye colour in Drosophila, named by Morgan as the white gene, is on the X chromosome which determines sex. Similar to us, male flies are XY whereas females are XX. This key experiment and numerous others that followed expanded on the knowledge gained through the ingenious cross-breeding experiments of pea plants by the Austrian monk Gregor Mendel half a century earlier. Importantly, this fly-based work found that characteristics like eye colour are inherited from parents through chromosomes — large structures which package DNA in our cells. Furthermore, Morgan and his gifted students uncovered that the thousands of genes in our genome are arranged along chromosomes in a precise order, like beads in a necklace. Each gene can be identified by its specific location on a chromosome.

“Flies could be used as models of human disease”

In 1933, Morgan won the Nobel Prize for these great discoveries. The first of six awards was to recognise seminal insights into our biology through this tiny fly. Hence, in 1946 one of Morgan’s protégés, Hermann Muller, was recognised for his fly research demonstrating that X-rays can damage chromosomes. Then in 1995, Ed Lewis, Christiane Nüsslein-Volhard, and Eric Wieschaus shared the Nobel Prize for their herculean efforts in discovering the genes that controlled early development in Drosophila. In the embryo, waves of master genes are triggered that lead to eyes, brains, and the body’s patterning. Similar genes were later found in humans doing the same function. In 2011 Jules Hoffman received the Nobel Prize for finding how the body’s inbuilt immunity works through the use of the fly model organism. I suspect that there is still room for more trophies in the fly triumph cabinet.

At the dawn of this century, the genomics revolution led to the complete DNA sequencing of an organism including fly and human. These monumental projects revealed that an astonishing number (more than two-thirds) of human genes involved in disease have counterparts in the fly. This development meant that flies could be used as models of human disease. It sparked off a renaissance of Drosophila research. The fly was good at modelling neuro-degenerative conditions because their nervous system has stunning similarities to ours. Neuro-degenerative diseases including Alzheimer’s, Parkinson’s, Huntington’s, and Motor Neuron Disease occur when neurons in the brain and spinal cord begin to die slowly. Patients may lose their ability to function independently or think clearly. Symptoms progressively worsen and ultimately, many die. Most neuro-degenerative diseases strike later in life, so we should expect their frequency to soar as our population ages — Alzheimer’s disease may triple in the US alone by 2050.

Malta: the right time to fly?

Together with my students in my lab at the University of Malta I am working with flies to learn more about neuro-degenerative disease. We continue to focus on SMA, a genetic disorder arising from the deterioration of motor neurons which are nerves that communicate with and control voluntary muscles. As the motor neurons die, the muscles weaken with drastic effect on the walking, crawling, breathing, swallowing, and head and neck control of unfortunate children afflicted by this condition. The child’s intellectual capacity is unaffected but vulnerability to pneumonia and respiratory failure means that many patients die a few years after diagnosis.

The underlying cause of SMA is usually a gene flaw that results in low levels of a protein called SMN for survival of motor neurons. Inside cells, SMN is bound to other proteins called Gemins. The SMN-Gemins alliance is involved in building the spliceosome, which is the chief editor of messenger RNA molecules. Messenger RNA carry the DNA code that instruct cells how to fabricate proteins. If SMN is absent spliceosomes do not form, correctly-edited messenger RNA are not produced and protein synthesis is heavily disrupted — the cell should shut down. Spliceosomes are required in each of the 120 trillion cells forming our body. Yet, in the disease SMA only motor neurons die. The reason has baffled researchers for decades and remains unsolved.

Is it possible that SMN has another function in motor neurons? And does it act alone? Our flies were crucial in providing some answers to these questions. Our work showed how the SMN-Gemins family is tightly-knit. In this regard, we recently demonstrated that both SMN and Gemins can be detected in prominent spherical specks in different cellular compartments. Within the cytoplasm, these organelles are known as U bodies because they probably are the factories of spliceosome components, which themselves are rich in the chemical Uridine. In the nucleus, the structures containing the SMN-Gemins family hug the mysterious Cajal bodies — discovered over a century ago by Spanish Nobel laureate Santiago Ramón y Cajal.

“We are feeding these flies the Mediterranean diet derivatives to see whether Alzheimer’s can be stopped in flies, which will bring us one step closer to treating it in humans”

And what about the flightless flies? Think about it. Considering that SMA is a neuromuscular disease, it makes perfect sense that on loss of SMN, muscles become so weak that flies are unable to flap their tiny wings fast enough to fly. Our latest work reveals that flightlessness is seen in flies without enough Gemin proteins. This means that SMN does not function alone but hand in hand with the Gemins. Our next step was to find out the pathway connecting the SMN-Gemins family to the motor defects. We linked the Gemin mutant which did not work properly to a tag called green fluorescent protein or GFP. GFP glows under the right light in cells. We managed to create genetically-modified flies with this modified gene — a first for Malta and a powerful tool to solve the mysteries of this disease.

Fluorescent proteins let researchers figure out a protein’s location. And by knowing the location of proteins we gain of lot of information about what they do. Consider this analogy with a VIP. If we tagged the Prime Minister of Malta we would find that he is most probably found in Valletta most time of the year. If we were aliens from another planet, this knowledge would allow us to refine our understanding of the Prime Minister’s function. Therefore, we can eliminate a function in the entertainment industry (weak signal from Paceville) but we cannot exclude a function in government (strong signal from Valletta). Likewise, we found that our GFP-Gemin mutant is mostly found in the cell’s nucleus. The nucleus houses life’s instruction manual: DNA. Our work now needs to zero in on the other proteins the SMN-Gemins family works with in the nucleus. Doing so will open new therapies to halt neuro-degeneration in children. Back to our analogy, we need to zoom in on Valletta until Auberge de Castille, the Prime Minister’s office, is clearly in focus.

Several neuro-degenerative diseases occur because of sticky protein clumps that wreak havoc inside, and outside, neurons. This is typical in Alzheimer’s disease, Parkinson’s disease and Motor Neuron Disease. With Dr Neville Vassallo’s research group, and local industry (Institute of Cellular Pharmacology), we are testing chemical derivatives of the Mediterranean diet and flora on fruit flies to see whether they can curb the protein clumps’ toxicity. They definitely do in a test tube. Flies mutated to be remarkably similar to human Alzheimer’s lose their ability to climb up the sides of their vial habitats and die prematurely because of neuro-degeneration. We are feeding these flies the Mediterranean diet derivatives to see whether Alzheimer’s can be stopped in flies, which will bring us one step closer to treating it in humans.

Through flies we have understood human biology. Apart from choosing Mr and Mrs Right, a good geneticist must learn to focus and listen to what flies are really saying. This is easier said than done but achievable. Flies have spurred me to pursue unexpected but interesting paths. In the years to come I, together with my students, will continue to flip, sort, screen and tag, looking for fly mutants who will continue to teach us about ourselves. And yes, we will be all ears!

The author is indebted to colleagues at the UoM and worldwide for their constant support and inspiration. The research of Dr Ruben Cauchi (Department of Physiology & Biochemistry, UoM) is funded by the Faculty of Medicine and Surgery, the University of Malta Research Fund and the Malta Council for Science & Technology (MCST) through the National R&I Programme 2012 (Project R&I-2012-066). For more about Dr Cauchi’s research click here.

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