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.
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!
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 1st January, and Form B on 2nd January, unless stopped by officials.’ Exactly at midnight between the 1st and 2nd 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 1st January he has violated the law. The defendant’s lawyer argues that, since John was under arrest throughout the 2nd 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.
Illustration by Sonya Hallett
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 Unimate Puma 200
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.
Lego Mindstorms EV3 brick
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.
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.
Relationships have changed hand in hand with society. More couples are living far apart from each other. Marc Buhagiar speaks to Mary Ann Borg Cunen to explore how technology can lend a hand. Illustrations by Sonya Hallett.
Stick to one language! Was the old maxim. Otherwise, you’ll risk confusing your kids and they will never learn to speak properly. Research by Prof. Helen Grech and her team shows that this is not true: bilinguals usually do better. Teaching your child two languages at a go might delay them initially but helps them in the long run. Words by Dr Edward Duca.
The role of women in academia has always greatly interested me. Several years ago, when I was asked to become Gender Issues Committee chairperson at the University of Malta, I readily accepted. Apart from other tasks, the committee has just compiled a booklet about the profiles of senior female academics. Our objectives are twofold: one is to incentivise junior staff to aim higher and move forward in their career; the other, to help sensitise male colleagues to better appreciate the hurdles women face when pursuing an academic career together with raising a family.Continue reading
Computational chemistry is a powerful interdisciplinary field where traditional chemistry experiments are replaced by computer simulations. They make use of the underlying physics to calculate chemical or material properties. The field is evolving as fast as the increase in computational power. The great shift towards computational experiments in the field is not surprising since they may reduce research costs by up to 90% — a welcome statistic during this financial crisis.
Keith M. Azzopardi (supervised by Dr Daphne Attard) used two distinct computational techniques to uncover the structure of a carcinogenic chemical called solid state benzene. He also looked into its mechanical properties, especially its auxetic capability, materials that become thicker when stretched. By studying benzene, Azzopardi is testing the approach to see if it can work. Many natural products incorporate the benzene ring, even though they are not toxic.
The crystalline structures of solid state benzene were reproduced using computer modelling. The first technique used the ab initio method, that uses the actual physical equations of each atom involved. This approach is intense for both the computer and the researcher. It showed that four of the seven phases of benzene could be auxetic.
The second less intensive technique is known as molecular mechanics. To simplify matters it assumes that atoms are made of balls and the bonds in between sticks. It makes the process much faster but may be unreliable on its own due to some major assumptions. For modelling benzene, molecular mechanics was insufficient.
Taken together, the results show that molecular mechanics could be a useful, quick starting point, which needs further improvement through the ab intio method.
This research was performed as part of a Masters of Science in Metamaterials at the Faculty of Science. It is partially funded by the Strategic Educational Pathways Scholarship (Malta). This Scholarship is part-financed by the European Union – European Social Fund (ESF) under Operational Programme II –Cohesion Policy 2007-2013, “Empowering People for More Jobs and a Better Quality Of Life”. It was carried out using computational facilities (ALBERT, the University’s supercomputer) procured through the European Regional Development Fund, Project ERDF-080 ‘A Supercomputing Laboratory for the University of Malta’.
At a site in East London, two construction workers inadvertently unearth the tomb belonging to the late King Charles II. Upon entering the crypt, they are assaulted, bitten and unkilled by former plague victims. Meanwhile, brothers Terry (Rasmus Hardiker) and Andy (Harry Tread- away), with their cousin Katy (Mi- chelle Ryan), are planning a bank heist. The trio concoct this heinousness with a noble intent: saving their grandad’s (Alan Ford) retirement home from be- ing demolished by heartless property developers. But of course, everything goes pear-shaped when the entire neighbourhood is invaded by hordes of the undead.
Cockneys and zombies: that’s what the title promises and that’s exactly what it delivers. Given the self-conscious- ly schlocky title, you would expect a crudely-made, amateurish production,
the likes of which litter the internet. The truth is, thankfully, very different. Cockneys has quite a high production value. It’s not World War Z but footage of London enfolded in chaos and may- hem is rendered in good quality CG, as are the close-up shots of carnage.
Still, one problem with comedy zombie flicks is that they will forever be in the shadow of Edgar Wright’s masterful Shaun of the Dead (2004). Shaun was a perfect storm of comedy, horror, excellent production, inspired casting, and fortuitous timing. Just as everybody was trying to get his/her head around the seemingly dubious merits and immense popularity of tor- ture porn horror films (Saw and The Passion of the Christ were both released in 2004), in waltzed Messrs. Wright, (Simon) Pegg and (Nick) Frost who made everybody’s sides split with laughter.
Luckily, even though Cockneys vs Zombies is nowhere near as brilliant as Shaun, it still can hold its head high. Director Matthias Hoene and writers James Moran (Severance, 2005) and Lucas Roche touch upon, but don’t expand much, on the zombie-as-meta- phor angle. They just want to play it for laughs and get more hits than misses. The scene in which poor old Hamish (Richard Briers) is being chased by the notoriously slow-moving zombies is pure gold and West Ham United sup- porters can put their mind at rest that, even after death, the feud with Millwall still rages on. In an inspired scene, we are at last shown that even infants are not immune to a zombie infestation.
Cockneys is no (early) George A. Romero and does not aspire to be. It just wants you to relax, pop some corn, sip on soda, and enjoy a zombie-tour around the streets of East London.
Take the language of a 
