Data Science for Science

Courtesy: James Stuby (NASA) / Wikimedia Commons A crater is a structure or geological formation that is produced as a result of impact of a smaller body upon a larger heavenly body. Craters are found on all solid heavenly bodies such as Earth, the Moon, Mars, Mercury, Venus etc.  Studying craters is important because they are time capsules to how our Solar System evolved and gives us clues to the past, present and future of the evolution of planetary bodies without humans setting foot on them. Crater densities have been correlated with surface age and crater counts have been used used to estimate the relative age of the lunar surface. There are many other uses to studying craters, so it is important to be able to detect craters quickly in an automated fashion. This research uses a novel method of detecting craters by using multiple co-registered data sources: optical images, digital elevation maps (DEMs) and slope maps of the lunar surface. The method uses a deep learning architec...

  Credit: Acropolis Museum/Socratis Mavrommatis Ancient civilizations have held fascination for historians and anthropologists ever since humans became curious about the past. Deciphering life in civilizations past meant that excavated tools, vessels, assorted items, inscriptions etc. had to be unearthed and examined. The most informative of these would be the inscriptions on scrolls, papyri, stone, metal, or pottery. A lot of these inscriptions are incomplete due to damage and large chunks of the inscribed text are often illegible. Determining where the texts originated from can be a challenge since they may have been moved multiple times. Dating these texts is another challenge as radiocarbon dating and similar methods can't be used since they can damage the priceless artifacts. Enter AI. Researchers from DeepMind collaborated with researchers from the University of Oxford to develop Pythia , an ancient-text restoration system based on Deep Learning. The database used w...

The Coma Cluster contains more than 1,000 galaxies. Scientists have long been frustrated by large uncertainties in its mass. Credit: PSC  A galaxy, as you may know, is a huge collection of stars that has a certain overall shape and which moves as a unit across the cosmos. Even larger groupings such as galaxy clusters  exist. The individual galaxies in a cluster move about relative to each other and revolve around their common center of mass. Their velocities relative to our observation point can be gleaned from measurements of their red-shifts or blue-shifts.  Estimation of the mass of galaxy clusters is still fraught with uncertainties. It is not yet clear how to determine the three-dimensional structure of galaxy clusters which reduces further the confidence of estimating the mass.  But why estimate the mass? It is now known that stars in a galaxy revolve around the center of mass of the galaxy. But their velocities exceed the calculated velocity based on the dete...

  Hello! Today we have an entry in the field of medicine. What is skin cancer recurrence? An early-stage skin cancer type called  melanoma  is treatable if diagnosed early enough. Most melanoma deaths in the US occur because of recurrence of the disease which was early stage at the time of diagnosis. However, recurrence is not detected until the cancer starts to spread; called symptomatic metastatic progression. This is where prognostic tools can be helpful for regular surveillance and quick action to stave off mortality and ensure health. Also, identifying high-risk patients can help in determining who should receive special therapies and treatments. Enter Machine Learning. A team led by investigators at Massachusetts General Hospital performed two types Machine Learning prediction with nine different models: Melanoma Recurrence Classification: Where the prediction would be a probability that melanoma recurrence would occur. Time-To-Event Melanoma Recurrence Risk Predict...

      (Credit: Retinal scan courtesy UK Biobank) Artificial Intelligence can now identify patients with a high risk of heart attack just by an eye scan that can be taken at an optician or eye clinic. Sounds too good to be true? The size and pumping efficiency of the left ventricle (one of the four chambers) of the heart is linked to risk of heart attack. An oversized left-ventricle leads to higher risk of heart disease. In turn, the retinal scans are linked to the size and pumping efficiency of the left ventricle. Currently, risk of heart disease can be determined through expensive diagnostic tests using MRI and ECG which are available only in a hospital setting. These tests are also unavailable in less well-resourced healthcare systems in developing countries and unnecessarily increase healthcare costs in developed countries.  Retinal scans on the other hand are comparatively cheap and available in many optician practices. Patients who are found to be at high risk...

    (Photo credit: BBC) Are We Alone?  It is a question that humans have had ever since we realized there are other worlds, other planets out there in the cosmos. The implications of the answer to this question are staggering no matter what that answer is. In pursuit of an answer scientists have been searching for planets that could potentially harbor life. Planets that are outside of our solar system are termed Exoplanets. The exploratory pursuit is to find "earth-like" exoplanets because these would have the greatest chance of harboring life as we know it. Determining the habitability of exoplanets is not an easy task. Existing ML methods such as Metric-based quantification (using metrics like surface temperature) or Supervised Learning (based mainly on estimated surface temperature) are not reliable enough.  Astronomers from the Indian Institute of Astrophysics along with astronomers from BITS Pilani and Goa campus designed an anomaly detection method to identify ...

  Drug development for the treatment of various diseases is the cornerstone of medicine for human health. Drug development is an expensive and time-consuming process. Most drugs developed up to the human-trials stage end up having no effect at all or too many side-effects. These drugs are thus discarded resulting in wasted time, money and effort. The cost of these drugs end up on the price tags of drugs that do become successful. Before drug development can even take place the drug discovery process must occur. Briefly, drug discovery involves a process of finding promising drug-like molecules that can bind or "dock" properly onto certain protein targets. After successfully docking to the protein, the binding drug, also known as the ligand, can stop a protein from functioning. If this happens to an essential protein of a bacterium, it can kill the bacterium, conferring protection to the human body. Drug discovery, the process of discovering new candidate medications, involves...

Hubble Deep Field. Courtesy: Encyclopedia Britannica Space is vast. The number of objects in the Universe is literally astronomical. The first step toward exploring these objects is to identify them aka classify them. Objects could be stars, galaxies, quasars, supernovae etc. Due to the sheer number and complexity of objects the task is very challenging to do manually. The further away a source of light is, the harder it is to distinguish its features and thus classify it. Astronomers have now sought the aid of AI in this task. A machine learning pipeline called SHEEP has been developed. SHEEP first extracts the photometric redshift of celestial objects and then uses this as one of the data features fed into an ML model for training. SHEEP combines several ML algorithms: XGBoost , LightGBM , and Catboost to obtain better classification performance. SHEEP contains two distinct classification methodologies: (i) Multi-class and (ii) one versus all with correction by a meta-learner. ...

Courtesy: UNDP Moldova Civilian drones today are flown under very specific and safe weather and wind conditions. This is because these drones have adaptive control algorithms that are lacking. This applies to remote-controlled drones as well as autonomous ones. The direct and specific effect of various wind conditions on aircraft dynamics, performance, and stability cannot be accurately characterised as a simple mathematical model. Engineers at Caltech have developed Neural-Fly, a deep-learning method that can help drones cope with new and unknown wind conditions in real time. Existing Machine Learning methods require a huge amount of data to train the model and adapting these large models in real-time is all but impossible. To overcome this, Neural-Fly was developed with a "separation strategy". Only a few parameters of the neural network must be updated in real time and this is achieved with a new meta-learning algorithm, which pre-trains the neural network so that only the...

  "Power of the sun in the palm of my hand" Many may remember this line from Toby Maguire's Spiderman 2 uttered by Dr. Otto Octavius. Well, the technology of the power of the sun is not far off in real-life. Usable fusion power has been dreamed of for decades and we get closer to it every year. Practical fusion reactors of today apply heat to atoms to generate fusion plasma. This plasma, when heated to the requisite temperatures (hundreds of millions of degrees), begin to cause atoms to fuse and release large amounts of energy. One day, we hope, the amount of energy used to run the reactor will be surmounted by the energy released, thus providing a clean, unlimited, eco-friendly power source, one to match the sun itself. In order to contain the fusion plasma (after all, earthly materials are not going to be capable of withstanding the heat), magnetic containment is necessary. To help control the delicate process of confinement of ultra-hot plasma, AI techniques are now be...

Courtesy: CERN Photolab Physicists have found evidence of mysterious particles known as "X" particles, which were first thought to form just after the Big Bang. "X" particles, called so because of their mysterious unknown inner structure, were created millionths of a second after the Big Bang. In a trillion degree sea of quarks and gluons that randomly collided, "X" particles were formed before the plasma cooled down and such stable particles as protons and neutrons were created. Today, X particles are extremely rare.  X (3872) was first discovered in 2003 by the Belle experiment, a particle collider in Japan that smashes together high-energy electrons and positrons. Within this environment, however, the rare particles decayed too quickly for scientists to examine their structure in detail.  Evidence of X particles in the quark-gluon plasma produced in the Large Hadron Collider (LHC) at CERN based near Geneva, Switzerland has now been found. The LHC's ...

Courtesy: University of Tennessee Knoxville Hey Folks, We have an intriguing application of Machine Learning (ML) today: Knots and Symmetries in Mathematics! ML, as you're probably aware, works when we have a whole lot of data. In fact, the more data we have, the more likely we are to use ML or its more sophisticated brethren Deep Learning (DL). So without further ado, let's dive in! What are knots and symmetries in mathematics? A knot in mathematics is, as you would expect, inspired from real-life knots but isn't so exactly. Simply put a knot is a 2-D closed loop that exists in 3-D space. This concept could of course be extended to n-dimensional loops in m-dimensional space. Knots can be described mathematically in various ways. Sometimes two seemingly different descriptions are actually of the same knot. This can be determined by comparing properties of knots known as invariants . One of the questions surrounding invariants is: Are two invariants related? To answer this ...

 Hello Fellow Internet User! How has your day been? If you're like me, you're thinking "Um...good or bad or something in between. It is still a great time to be alive!" Welcome to this blog!  Data Science is everywhere! Because data is everywhere! Data Science is fascinating as it is our very human yearning to know  what all of this data tells us . If not out of curiosity then to find out how those stories can help us in various endeavours. Science and Engineering can also benefit from Data Science, maybe even recursively ;-) This blog is meant to bring together a curated set of advancements on how Data Science has been used to further science and engineering endeavours. Apart from drawing your attention to the substance of these advancements, I shall add my own commentary. Should be a fun ride! Hope you enjoy it! Joie de vivre pour toi! Rahul PS: I am open to comments and suggestions. Please let me know what you think of this blog, its posts or anything else of relev...

The single most significant starting point for a researcher in any field is the Literature Review. This is where the researcher reads through large troves of research papers in order to absorb and understand the current state of research in their chosen field. Wouldn't it be wonderful if someone (or something) could summarise these papers so that only relevant research could be chosen in order to do a deep-dive?  Researchers at the Allen Institute for Artificial Intelligence have developed just such an AI model. It summarises text from scientific papers and presents them in a few sentences in the form of TL;DR (Too Long; Didn't Read).  The AI model takes the most important parts from the Abstract, Introduction, and Conclusion section of a research paper to form the summary. Researchers first “pre-trained” the model on the English language. Then they created a SciTLDR data set of over 5,400 summaries of computer science papers. It was further trained on more than 20,000 titles ...

Artificial Intelligence is now helping to predict the eventual onset of Alzheimer's disease in healthy people. The research conducted by IBM Research and Pfizer uses short standardised speech tests with better results than current methods.  Alzheimer's is a disease of the brain. Those afflicted by it, typically people over 60 years of age, slowly lose their ability to think, ability to recall from memory and eventually the ability to carry out simple tasks. Prediction of the onset of the disease can lead to the development of a simple, straightforward and accessible metric to help clinicians assess the risk of Alzheimer’s disease in an individual, leading to earlier intervention. There is no effective cure or prevention of this disease but the best way to delay onset and slow progression is to intervene early which may be possible one day.  AI techniques were used to train models using short language samples from the Framingham Heart Study . Sample were selected based on age-g...

Archaeologists, most exemplified in popular culture by the character of Indiana Jones, are more often seen as people who do a lot of manual field work: exploring hitherto unknown areas of land to find objects or patterns that would give some clues to the ancient past. They are now catching up with the rest of the sciences in utilising the amazing technology of AI. Uncovering long-abandoned ancient settlements in Madagascar, detecting nearly indiscernible bumps of earthen mounds left behind by prehistoric North American cultures, mapping Bronze Age river systems in the Indus Valley, and many more such activities are seeing the involvement of AI. Such activities called Landscape Archaeology are examples of areas where AI is helping scientists hunt for new archaeological digs as well as understand ancient cultures at large scale and great pace. So what data is used by AI to help with Landscape Archaeology? The near-ubiquitous availability of satellite data and other kinds of aerial ima...

Aloha! Today we have an entry in Geology. Earthquakes are notoriously difficult to predict. Now researchers have found a way, using AI techniques, to predict the occurrence of "slow" earthquakes. Slow earthquakes can last for a period of weeks or even months but because of their low intensity nature do not cause much damage. They may not even be felt by us. Continuous seismic waves carry the potential signature of an upcoming  slow slip  failure. These seismic waves can be analysed to find patterns and from the regularity in these patterns predictions can be made as to when an event could occur and its intensity. Credit: Earthquake Research Institute, University of Tokyo The researchers created a list of characteristics that precede the appearance of earthquakes. Among them, the researchers noted an exponential increase in seismic energy prior to rupture, as if more and more tiny seismic waves were being emitted from the seismic zone. These crackles were noticeable up to thre...

Namaskaram! Today we have an application of AI in Astronomy. The Universe is vast. So mind-boggling is its vastness that astronomers need the use of technology to find and classify astronomical objects. The Subaru Telescope, located in Hawaii, USA, had taken numerous images of galaxies from Earth's vantage point. Thanks to its high sensitivity, as many as 560,000 galaxies have been detected in the images. It would be extremely difficult to visually process this large number of galaxies one by one with human eyes for morphological (shape) classification. The AI technique enabled astronomers of the NAOJ (National Astronomical Observatory of Japan) to process these galaxies without human intervention. Deep Learning based image classification techniques have been used to classify images based on their pixel-data. You might have heard of the "dog" and "cat" classifier. Well, it turns out Deep Learning is also good at distinguishing galaxies "with spiral patterns...

Hello, hello! This one's going to sound like it's from a sci-fi movie, if you haven't already heard about it. It's about reconstructing images by reading signals from the human brain! And it is non-invasive! The study of signals in the human brain (brain waves) using fMRI (functional Magnetic Resonance Imaging or EEG (Electroencephalogram) has been around for some time now. For the first time, image reconstruction from brain waves using A.I techniques is producing decent results.  The brain-computer interface (BCI) developed by MIPT (Moscow Institute of Physics and Technology) and Neurobotics relies on artificial neural networks and electroencephalography, or EEG, a technique for recording brain waves via electrodes placed noninvasively on the scalp. By analysing brain activity, the system reconstructs the images seen by a person undergoing EEG in real time. Feel free to skip this bit if you don't need the technicals. The BCI Operation Algorithm laid out in this res...

Courtesy NASA/JPL-Caltech Hello, Today we have an entry in the field of Astronomy. It is specifically about planetary systems around other stars and their orbits. Astronomers detect planets around other stars and collect data. There are enough data points to confirm that they have indeed detected a planet but not enough to determine the exact orbit of that planet around its host star. Throw in multiple planets around a single host star and you have a planetary system for which you do not know the stable orbital configuration. Knowing the stable orbital configuration allows astronomers to predict planetary positions and movements which would in turn be useful for making observations (such as atmospheric composition) and help bolster or weaken theories of exoplanets. How can ML help? Previously, orbital configurations would have to be simulated over many billions of orbits using brute-force techniques in order to find stable configurations. These would take many hours even on modern supe...