Virtual Kills, Real Anxiety: Predicting from online gaming

Research has shown that those who are diagnosed with Internet Gaming Disorder may demonstrate other psychological and behavioural issues such as impulsivity, hostility, emotional distress and low self-esteem. Can behaviour during online games help predict the propensity for such disorders? A team led by Swati Aggarwal from the Netaji Subhas University of Technology, New Delhi looked into the association between psychological conditions such as attention deficit hyperactive disorder, generalized anxiety disorder and internet gaming disorder and gamer statistics. They took PUBG as a case. Player Unknown’s Battlegrounds is an online game where multiple players can engage in virtual battles. The team sent Asian gamers the link to a survey containing questions
related to sociodemographics and gaming information as well as psychometric instruments. Thirty-five who played the game on computers and 19 who played on mobile responded. The team extracted gamer statistics and screenshots of mobile phones during the game. They used the pre-processed data and the scores obtained from the
questionnaires to train various supervised machine learning classifier models. Given the low number of samples, they adopted the leave-one-out to train and test. In each run,
one sample is left out and the outcome is tested against it. Thus, using 44 iterations, they strengthened the learning by the machine. The researchers tried various machine learning strategies: Logistic Regression, KNearest Neighbor, Naive Bayes, Decision Tree and Decision Tree with Adaboost… And found that the Logistic Regression classifier
could predict internet gaming disorder with an accuracy of more than 93% and attention deficit disorder with an accuracy of more than 81%. However, the Decision Tree classifier was better at predicting generalised anxiety disorder with an accuracy of nearly 85%. ‘Only two out of 44 were females –either because violent games are not popular among females or online gamers are mostly male,’ wonders Shubhi Gupta. ‘About 20% of teenagers between 15 and 18 years in our study suffer from ADHD. But half of those between 24 and 27 have generalised anxiety disorder,’ adds VarshikaGambhir. ‘When we left out gender, age or self-esteem, the accuracy dropped significantly, suggesting that these factors play important roles,’ says Swati Aggarwal, Netaji Subhas University of Technology. ‘Similarly, there are factors such as number of kills and number of wins that emerge as significant,’ says Shivin Saluja, her colleague. ‘The more the kills and wins, the more the chances of becoming addicted,’ says Simrat Pal Singh Satia. ‘And the number of hours spent on the game, though not proficiency in
the game, is strongly correlated with ADHD.’ There is one question that remains. Does internet gaming cause these disorders or do these disorders predispose you to gaming? Further studies are needed to understand the correlations in terms of causation.

DOI: 10.1016/j.addbeh.2019.106132

Spinning our way into the world of atoms

By Siva Shakthi and Vimal Simha, Research Matters.

In most scientific experiments, noise, consisting of random fluctuations that interfere with the measurement one is trying to make, is often a source of nuisance and anguish. However, in some experiments, scientists actually set out to probe the pattern of noise and draw useful inferences from it. For example, in 1928, scientists used random voltage fluctuations in a conductor to measure its resistance to electric current. Spatial and temporal variations are common in physical systems, and accurately measuring them can help us better understand the internal structure and other characteristics of such systems.

In a recent study, researchers at the Raman Research Institute, Bengaluru, have used a technique known as spin noise spectroscopy to probe the atomic, magnetic and sub-atomic properties of rubidium vapour. The study, published in the journal Optics Express, demonstrates that spin noise spectroscopy is a practical, non-invasive technique to study the atomic properties of many physical systems. It performs better than hitherto used methods to study the atomic properties of an element in detail.

Spin noise spectroscopy is a technique to probe physical systems using random spin fluctuations of the electrons. Like other subatomic particles, electrons have a charge and a mass, and another fundamental property known as spin. Experiments have shown that electrons behave as if they are spinning about an axis similar to a spinning top. However, unlike the spinning top, the spin of an electron appears to be an intrinsic property, and not caused by anything physically rotating within it.

There are two types of electron spin—spin-up and spin-down, roughly corresponding to anti-clockwise and clockwise rotation. In any given material, on average, there are equal numbers of spin-up and spin-down electrons. However, there can be fluctuations in the spin properties, and a detailed map of such changes could tell us more about the intrinsic properties of the material.

In the current study, the researchers used a laser beam to probe a cell containing vapours of rubidium-87, an isotope of rubidium. Like all light, the laser beam consists of oscillating electric and magnetic fields. The researchers subjected the rubidium atoms to a uniform magnetic field perpendicular to the direction of the probe beam. They then analysed the transmitted laser beam to decipher the properties of the element.

When the applied magnetic field was low, the researchers obtained a noise spectrum, caused by random spin fluctuations of the electrons. They observed two distinct peaks at two different frequencies of the transmitted light, indicating spin fluctuations of two different substances in the sample. It was because the sample, which mostly contained rubidium-87, also had trace quantities of rubidium-85, another isotope of rubidium. Traditional spectroscopy, which differentiates two substances based on the wavelengths of light they absorb, would not have revealed the presence of rubidium-85, because there is not enough of it to produce an observable absorption line.

As the strength of the magnetic field is increased, the researchers observed that the peaks in the transmitted spin noise spectrum broadened. From this, they say that a precise measurement of the magnetic field could be established.

“Even at room temperature the spin noise signal is reasonably narrow in frequency, making it a useful tool for precise detection of the external magnetic field,” say the researchers.

At low temperatures, the precision is expected to be far better since cold atoms collide less often, producing fewer effects that interfere with the measurement.

The researchers also extended the spin noise spectroscopy technique to explore what happens under non-equilibrium conditions, where the balance between the spin-up and spin-down states, was disturbed. They used a control laser beam to obtain different spin populations of electrons and then demonstrated that these differences are reflected in the noise spectra they get.

The researchers say that the technique can also be used to probe other properties such as the boundary between different phases of matter by mapping the spins of atoms in the substance.

“The origin of magnetism of matter can also be better understood using this technique”, say the researchers. “In a nutshell, this technique can be used to explore several open questions in quantum magnetism,” they conclude.

Tremor Free Detectors

Gravitational wave detectors rigorously probe the universe to reveal phenomena that have remained mysteries. But these instruments are highly sensitive. Scientists say that
even earthquakes of magnitude four on the Richter scale could interfere with the detector’s functions.

Last month, Nikhil Mukund of IUCAA in collaboration with institutes in Italy, the United States, and the United Kingdom reported a technique for dealing with earthquakes. They took archival data on seismic events and, using machine learning algorithms, devised ways to predict the impact of earthquakes and take appropriate measures. Using algorithms, they can now switch control configurations, such that the interferometers remain locked even under excessive ground motions.

Though measures have been taken to isolate these detectors from large-magnitude earthquakes, small magnitude tremors still posed a problem. Last fortnight, Nikhil Mukund and Sanjith Mitra from the IUCAA, Pune and Surendra Nadh Somala from the IIT Hyderabad collaborated with the Laser Interferometer GravitationalWave Observatory in Livingston, USA to develop a model to understand the effects of these small-magnitude earthquakes.

They found that the major source for such earthquakes is the hydromechanical drilling carried out by oil industries in the surrounding region. Such drilling exposes the underlying fault lines to high pressure, resulting in tremors. Though these seismic events cannot cause any structural damage, they affect gravitational wave detectors. However, the algorithms created to deal with large earthquakes cannot deal with small tremors caused by nearby industries. The team stresses the need to curb such activities by oil industries in the vicinity of the detectors. They also call for highly sensitive seismometers that can detect low magnitude tremors precisely and rapidly.

With many countries aiming to build both above ground and underground detectors, such contributions make Indian scientists leaders in this area of research, even before gravitational detectors are built here.

DOI: 10.1088/1361-6382/ab0d2c 2
DOI: 10.1088/1361-6382/ab1360

Body cells to bird flocks: Decoding glassiness

It might be baffling to think that tissues, comprising of motile cells, behave like glass. But, did you know that many living systems, like armies of ants, flocks of birds, and cancerous cells are also glass-like? One thing that is common to all these systems is that the others in the system severely restrict the movement of one of the constituent units. In a recent study, researchers from Bengaluru’s Indian Institute of Science (IISc), National Centre for Biological Sciences (NCBS), International Centre for Theoretical Sciences (ICTS) and Israel’s Weizmann Institute of Science, have successfully developed a model to explain the dynamics of collective systems that are motile at high density.

What makes such collective systems glassy? Imagine some motile cells confined to a small region. When there are far too many ants, there would be multiple head-on collisions between them, leading to a significant rise in the ‘cellular traffic’. On a larger scale, the increase in traffic could bring some regions to a standstill, without any movement. Some parts that do not have many encounters, on the other hand, continue to have a fluid-like motion. The solid-like and fluid-like regions may interchange their positions over time. This behaviour is akin to glass—a state of matter that behaves like a solid for short periods of time but relaxes to a liquid state over an infinitely long time.

The other property common to both collective living systems and glass is jamming. When a liquid changes to a solid in a slow process at low temperatures,  the atoms have enough time to rearrange themselves in an orderly fashion. However, in the case of glass, this change from liquid to solid is rapid, resulting in a disordered solid through a process called jamming.

Studying the properties of such active systems has many implications. “Developing a proper theoretical framework for such a system should help to understand them within a coherent framework. Beyond biology, activity provides an interesting control parameter for a glassy system. We hope, our work will lead to deeper insights into the glassy systems in general”, says Dr. Saroj Nandi, a Postdoctoral Fellow at the Weizmann Institute of Science, Rehovot, Israel.

The researchers of the current study, published in the Proceedings of the National Academy of Sciences, have used random first-order theory—a fundamental mathematical concept—to understand the behaviour of complex systems. The total energy of the system depends on the surface density and evolves depending on the movement within the collective system. It also influences a thermodynamic property called configurational entropy—the different ways in which constituent particles rearrange within a system. In systems devoid of activity, configurational entropy is determined only by the temperature, the number of constituent particles, and the internal energy.

Since the random first-order approximation applies for systems in equilibrium, the researchers modified it to suit active collective systems that are out of equilibrium. They constructed a new model to incorporate the effects of activity in a collective system. The researchers then validated their model through simulations and showed that the behaviour of active glassy systems depends on the nature of the activity.

Since the random first-order approximation applies for systems in equilibrium, the researchers modified it to suit active collective systems that are out of equilibrium. They constructed a new model to incorporate the effects of activity in a collective system. The researchers then validated their model through simulations and showed that the behaviour of active glassy systems depends on the nature of the activity.

“We have a well-established theory for an equilibrium system. We now extend it for active systems so we can understand the assumptions of the theory. It will also be easier to test and establish the predictions by others. This approach is in contrast to modelling a particular biological system”, says Dr Nandi.

The study is an essential milestone in the exploration of activity-driven glass-like systems. It is funded by the Koshland Foundation, Council of Scientific and Industrial Research (India), and the Harold Perlman Family Foundation, and has broad applications not just in studying the nature of the collective behaviour of biological systems but also in areas such as non-equilibrium thermodynamics and disordered magnetism.

Published in Research Matters

Aha Octopus

It’s your favorite eight-legged science teacher, the mighty Aha Octopus! As a highly curious creature, I’m always exploring the depths of science and discovering new wonders of the natural world. I’m also a champion problem-solver. Whether I’m camouflaging myself to avoid predators or figuring out how to open a tricky jar, I’m always up for a challenge.

Aha Octopus

So what we do at Aha Octopus?

The main aim of this volunteer-led club is to take science to the larger mass. We also debunk myths and misinformation in science in regional languages, Indian Sign Language and English. We follow the path led by visionaries like Narendra Dabholkar, Gauri Lankesh, and Kalburgi to instil a scientific spirit and curiosity among the Indian masses.

If you are interested in joining hands with us, do ping me at a.sivashakthi@gmail.com

Note – We have currently put a rain check on the club’s activities as we are giving it a facelift. We will be back soon!

Conference Presentations

1. Siva Shakthi A., Astronomy outreach: a multilingual approach, Public Engagement in Astronomy in the Pandemic Era, 2021
2. Siva Shakthi A., Communicating Science in India: A Multilingual Approach, Inclusive SciComm Symposium, 2021
3. Siva Shakthi A., Science Communication: A Multilingual Approach, No Coast SciComm, 2022

Race to Global Leadership

Is the West at a loss in Science?

After the Second World War, Europe lost its long-standing position as the global leader in science. Since then, the United States of America has been the doyen of scientific research. But the pivot seems to have shifted again – this time to China. Several quantitative indicators show the rapid rate at which China is moving ahead. These indicators include quantitative indicators of science such as the number of researchers, papers and patents, besides exchange rate, purchasing power parity, and gross expenditure on research and development. But where exactly is China in the race?

Last fortnight, researchers from the South Asian University, New Delhi, in collaboration with researchers in the USA, reported an analysis. They considered not just quantitative indicators but also qualitative indicators such as strategic investment, longterm plans, and science education.

Qualitative indicators are not as easy to interpret as quantitative indicators. The researchers took strategic investment in science and technology as a qualitative indicator. They also relied on anecdotes from the World Technology Evaluation Center, US. The researchers stress the need for such indicators to understand the full picture.

China has been allocating funds to boost research in nanotechnology, biotechnology and information technology. At present, China is the lead manufacturer of carbon nanotubes and boasts some 170 best supercomputers. The country has the capacity to launch humans into space – once an American dream.

Another qualitative indicator favoring China’s position as the global leader is its effort to bring home Chinese scientists trained in the West. By offering attractive packages and facilities, China has strengthened its scientific and technological workforce. This, in turn, has improved the quality of science education within the country – of vital importance in the long run. China’s march to achieve the goal of indigenous innovation is another qualitative indicator.

The studies by the World Technology Evaluation Center appreciate the level of sophistication achieved by China to perform high-quality interdisciplinary research. However, China is still behind the West in terms of the number of citations and patents.
What is more, high levels of plagiarism plague the country! While China’s rise towards global leadership is prominent, it might take another decade or so for it to capture the throne, say the researchers.

Scientometrics 117.1 (2018): 249-269.

CURRENT SCIENCE, VOL. 115, NO. 7, 10 OCTOBER 2018

Lab-on-body: Wearable Sensors

Flexible electronics step forward

In the past two decades, the electronics industry has witnessed some paradigm shifts – device miniaturisation, organic base materials and flexible components. Thanks to these advancements, we now have wearable health monitors, human–robot interfaces, and soft-actuators. But there remains an underlying challenge: developing components that are pliable and which adapt to human skin.

Though there exist magneto-electric systems based on ultra-thin glass, metal foil and polymer substrates, these fall short of expectations due to their fragility, opacity and thermal instability. Last fortnight, scientists from the Indian Institute of Science, Bengaluru and the National Chiao University, Taiwan presented an approach to overcome these limitations. They developed a pliable magneto-electric nano-composite that responds to changes in the magnetic field by changing its electrical properties.

To build the nano-composite, the researchers used muscovite, a transparent, poly-silicate mineral containing potassium and aluminium, as substrate. Muscovite is elastic and has
high thermal stability, properties that make it a good choice as substrate. Moreover, the two-dimensional nature of muscovite facilitates van der Waals epitaxy, alleviating stringent lattice matching conditions. The result is a sensing structure with almost freestanding layers, an essential property of pliable devices.

The researchers fabricated a heterostructure comprising bismuth ferrite rods embedded in a cobalt ferrite matrix. Cobalt ferrite has large magneto-striction and bismuth ferrite has ferroelectric properties. Together, they offer high magneto-electric coupling. This, in turn, influences the sensitivity of the device.

Thus, with a sound combination of materials and fabrication techniques, the researchers created the largest lab-on-body to perform non-invasive sensing. They are sure that this would accelerate progress in the area of flexible electronics. For capitalists aiming to find a niche, here is something to invest in.

J. Phys. D: Appl. Phys., 51(23): 234006

CURRENT SCIENCE, VOL. 114, NO. 12, 25 JUNE 2018

 

Automatic Emotion Recognition

The human mind has remained a puzzle for ages. From marketing to mental health monitoring, there is a dire need for automatic detection of human emotions in candid environments.

The current facial recognition technologies are not sufficient to decode emotions. They detect emotions but these work only within laboratory conditions. Now, Aparna Mohanty and Rajiv Sahay from the IIT Kharagpur have come up with a solution.

The researchers used a machine learning technique, convolution neural network, a bio-inspired technology based on how neurons take up a signal, process it, and elicit an action in the brain. A convolution neural network acts as a stack of detection filters with every subsequent layer searching for more abstract details than the preceding layer.

The researchers employed a Microsoft Kinect sensor to collect colour and depth information from pictures that depict emotions. They then fed the information to the convolution neural network. And compared details from the filters against an inbuilt dataset of various emotions.

To validate their technique, Aparna and Rajiv used photographs of Bharatanatyam dancers.

Navarasa or the nine emotions along with hand gestures form the soul of Bharatanatyam. The researchers collected photographs of fourteen individuals each performing a navarasa ten times.

A subset of these photographs formed the dataset for training the network. The team used two other subsets for validation and for testing.

By tweaking the number of network layers and the detection capacity of each layer, the researchers could achieve high accuracy in detecting emotions.

To validate the efficiency of their technique in unconstrained environments, they used videos from dance concerts. Despite confounding factors such as make-up, lighting and
non-frontal postures, their system accurately recognised emotions from the video frames.

In a world where human-computer interaction is on the rise, emotion recognition has become imperative. Once considered a superpower in a fictional universe, automatic emotion recognition is now within our reach.

Pattern Recognition, 79: 97–113

CURRENT SCIENCE, VOL. 115, NO. 1, 10 JULY 2018

Circular Economy

A sustainable business model?

As population grows, so does dependence on natural resources. Resources are dwindling. The planet can no longer support ‘take-make-dispose’ industrial models.

To restore balance, researchers propose a circular economy. Here, resource input, waste production, and energy leakage are minimised. A circular economy suggests slowing, closing and narrowing energy and material loops to allow the system to regenerate.

Researchers from the Institute for Competitiveness, India and the Grenoble Ecole de Management, France examined how feasible circular economy would be in India. With 17% of global population, India has a well-balanced population pyramid. The researchers evaluated the business models of three companies, Goonj, Attero and HaathiChaap, as
case studies.

HaathiChaap, based in Rajasthan, makes paper products out of elephant dung. The manure is disinfected, dried, beaten to pulp, and drawn to sheets of paper. Water from
the treatment is used as fertiliser. Elephant dung has, thus, created employment opportunities for tribal communities in the region. The researchers laud HaathiChaap for removing taboos associated with using animal waste.

Goonj, a Delhi-based NGO, collects unused clothes, sorts and distributes them to weaker sections. Goonj also trains women from rural communities to make sanitary pads and mattresses with unused clothes – a parallel economy for weaker sections, drawing resources from urban communities. The researchers found Goonj successful in creating a trash to cash system.

Noida-based Attero is an electronic waste management enterprise. Tonnes of electronic waste go untreated in India. Attero extracts metals of value from waste. The metals are
then used as raw material in the electronics industry. Attero has also launched an online platform to directly sell refurbished products. With Attero, the researchers identify efficient management of waste.

The researchers highlight the importance of entrepreneurs in value creation and value delivery. For a more sustainable future, industries would do well to adopt circular economy models.

Thunderbird Int. Bus. Rev., 60(5): 729–740

Science Last Fortnight, CURRENT SCIENCE, VOL. 115, NO. 5, 10 SEPTEMBER 2018

Quest for Rechargeable Cells

Lithium sulphur combination

Lithium–sulphur composites have transformed batteries over the past decade. Lithium–sulphur batteries are economical, lighter and offer high energy density. Such features are in high demand.

However, lithium–sulphur batteries are unstable. Polysulphides that form during every battery cycle dissolve the cathode: electrodes degrade fast. This affects battery efficiency over time, preventing large-scale commercial exploitation of the technology.

Last fortnight, researchers from the IIT Kharagpur reported developing a prototype of a lithium–sulphur based composite cathode with improved electrochemical activity. They impregnated titanium dioxide, the base of the cathode, with sulphur. Titanium dioxide is polar. So it adsorbs sulphur better, boosting discharge capacity. But it also weakens electrical conductivity.

To keep the electrical pathway between sulphur and titanium oxide strong, the researchers used reduced graphene oxide. And to reduce the loss of sulphur during discharge cycles, they coated the sulphur on the cathode with polyaniline.

The researchers say that even after twenty cycles, the discharge capacity reduced only by less than three percent before stabilising. In available lithium–sulphur batteries, efficiency reduces drastically within the first few cycles before stabilising.

The cathode composite not only offers better electrical conductivity but is flexible. So, beyond improving lithium–sulphur batteries, the research may lead to new applications.

DOI: 10.1016/j.matlet.2018.05.070

Science Last Fortnight, CURRENT SCIENCE, VOL. 115, NO. 6, 25 SEPTEMBER 2018