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Image Name: Great Egret

The Great Egret, also known as the common egret or great white egret, is a tall, stately wading bird with a

distinctive appearance. It stands over 3 feet tall, has a long, S-curved neck, dagger-like yellow bill, and long

black legs. With its graceful presence in quiet waters, foraging mainly on ﬁsh and other aquatic creatures by

patiently waiting in shallow waters and catching prey with a rapid thrust of its bill, it breeds in colonies near

large lakes with reed beds, forming monogamous pairs each season and raising up to six bluish-green eggs at a

time. Both parents incubate the eggs, and the young are fed by regurgitation, becoming capable of ﬂight within

6-7 weeks. To know more see https://en.m.wikipedia.org/wiki/Egret

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Editorial

by Fr Dr Abraham Mulamoottil

airis4D, Vol.2, No.4, 2024

www.airis4d.com

In this edition, we embark on a journey through

the cosmos, exploring the cutting-edge intersection of

science and technology. Atharva Pathak, a Software

Engineer & Data Manager at the Pune Knowledge

Cluster, sets the stage with his article ”Astronomy:

Gazing into the Future with AI.” The article discusses

the transformative role of artiﬁcial intelligence (AI)

and machine learning (ML) in revolutionizing the ﬁeld

of astronomy. Traditional methods of analyzing vast

astronomical datasets are being replaced by AI algo-

rithms, allowing for faster and more accurate classiﬁca-

tion of celestial objects such as galaxies and exoplanets.

AI’s potential extends to proposing scientiﬁc hypothe-

ses and assisting with data interpretation in upcoming

astronomical projects like the Vera C. Rubin Obser-

vatory and radio astronomy initiatives like the Square

Kilometer Array. The article also suggests ways for

individuals to get involved in this exciting intersection

of AI and astronomy through citizen science projects

and online courses.

The article ”Black Hole Stories-8: Light Ray

Paths in General Relativity” delves into the behaviour

of light rays, or photons, in the gravitational ﬁeld of

a black hole according to Einstein’s theory of gen-

eral relativity. It discusses how the curved spacetime

around a black hole aﬀects the paths of light rays, in-

troducing concepts like null geodesics and the aﬃne

parameter to describe these trajectories. The article

explores the impact of conserved quantities such as

energy and angular momentum on the paths of light

rays, highlighting diﬀerences from timelike geodesics.

It also explains the shape of orbits for light rays around

a Schwarzschild black hole, emphasizing the absence

of stable circular orbits and the existence of a photon

sphere. Professor Ajit Kembhavi, serving as the driv-

ing force behind this initiative, has been a consistent

contributor to AIRIS4D, actively promoting astronomy

outreach and research in India.

The article ”Does the Universe Speak the Lan-

guage of Radio Waves?” explores the fascinating world

of electromagnetic waves, focusing particularly on ra-

dio waves. It begins by discussing the various sources

of light, both natural and artiﬁcial, and then delves

into the electromagnetic nature of light. The article

explains the historical development of radio wave the-

ory, from Maxwell’s equations to Heinrich Hertz’s ex-

periments. It highlights the unique characteristics of

radio waves and their importance in communication

and astronomy. Furthermore, it discusses the funda-

mental processes that generate electromagnetic waves,

such as the acceleration of charges and quantum state

transitions. The author, Linn Abraham, is a physicist

specializing in artiﬁcial intelligence applications to as-

tronomy, providing valuable insights into the topic.

The article ”Sun to Black Holes: An X-ray Voy-

age” discusses the signiﬁcance of studying X-rays in

astronomy, particularly in understanding cosmic phe-

nomena ranging from the sun to black holes. It begins

with the historical background of X-ray discovery and

the challenges of studying X-rays due to the Earth’s

atmosphere. The article highlights key milestones in

X-ray astronomy, including the pioneering work of Ric-

cardo Giacconi, which led to the discovery of cosmic

X-ray sources. It also discusses the evolution of X-ray

telescopes and detectors, leading to the development

of advanced satellites like Chandra X-ray Telescope

and XPoSat. The author, Aromal P, emphasizes the

importance of studying cosmic X-rays and their role in

unravelling the mysteries of the universe.

The article ”Color-Magnitude Diagram, Part-3”

by Sindhu G explores the signiﬁcance and interpreta-

tion of color-magnitude diagrams (CMDs) in astron-

omy. CMDs are graphical representations of stars

within a speciﬁc region of space, illustrating their

brightness and color. They serve as powerful tools for

studying star clusters and galaxies, providing insights

into stellar evolution, age, metallicity, and distance.

The article discusses the key features of CMDs, such

as the main sequence, paths of stellar development,

and insights into metallicity, age, and distance deter-

mination. CMDs oﬀer valuable insights into how stars

evolve within clusters and galaxies, shedding light on

the intricate dynamics of the universe. Through the

analysis of CMDs, astronomers can unravel the com-

plexities of galactic evolution over billions of years.

The article explores the signiﬁcance of Odonata,

including dragonﬂies and damselﬂies, as bioindicators

for assessing ecosystem health, with a focus on un-

polluted freshwater habitats. Speciﬁc Odonata species

such as Euphaea fraseri, Neurobasis chinensis, Vestalis

apicalis, Vestalis gracilis, and Heliocypha bisignata are

highlighted as indicators of unpolluted waters due to

their sensitivity to pollution and well-resolved taxon-

omy. Each species is described taxonomically, includ-

ing physical characteristics, habitat preferences, and

breeding behaviours. These descriptions emphasize

the importance of Odonata species in environmental

assessments and their role as sensitive indicators of

freshwater ecosystem health.

This edition ends with the article of Jinsu Ann

Mathew that discusses the signiﬁcance of key epige-

netic clocks in understanding biological ageing and its

health implications. It starts by introducing the concept

of DNA methylation and its role in determining biolog-

ical age through epigenetic clocks. The Horvath Clock

developed in 2013, is highlighted for its ability to accu-

rately predict biological age across various tissues and

organisms, oﬀering insights into health outcomes and

lifespan. Subsequent clocks like the Hannum Clock,

Weidner Clock, and Levin Clock (DNAm PhenoAge)

are discussed, each with its unique methodology and fo-

cus. The GrimAge Clock, introduced in 2019, is noted

for its emphasis on predicting mortality risk and age-

related diseases by incorporating DNA methylation-

based biomarkers. Despite diﬀerences, these clocks

provide valuable insights into the ageing process and

hold promise for personalized medicine approaches

aimed at promoting healthy ageing and longevity.

iii

Contents

Editorial ii

I Artiﬁcial Intelligence and Machine Learning 1

1 Astronomy: Gazing into the Future with AI 2

1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.2 The Data Deluge: Upcoming Astronomical Projects . . . . . . . . . . . . . . . . . . . . . . . . . 2

1.3 AI: The Astronomer’s Powerful Ally . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.4 How Can You Get Involved? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

II Astronomy and Astrophysics 5

1 Black Hole Stories-8

Light Ray Paths in General Relativity 6

1.1 The Eﬀective Potential in General Relativity for Light Rays . . . . . . . . . . . . . . . . . . . . . 6

1.2 The Shape of Orbits of Light Rays or Photons Around a Schwarzschild Black Hole . . . . . . . 7

2 Does the Universe Speak the Language of Radio Waves? 9

2.1 Let there be Light . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.2 An Electromagnetic Wave at Heart . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.3 Radio Waves Arriving A Little Late to the Party . . . . . . . . . . . . . . . . . . . . . . . . . . . 9

2.4 Fundamental Processes that Generate EM Waves . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.5 Tuning into Radio Broadcasts from the Cosmos . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

2.6 How Messages Get Changed by the Medium . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

3 Sun to Black Holes : An X-ray Voyage 12

3.1 Game of Hide-and-Seek . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

4 Color - Magnitude Diagram, Part-3 15

4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

4.2 Color - Magnitude Diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

4.3 Interpreting the Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4.4 Key Features of the Color Magnitude Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.5 Insights from Color-Magnitude Diagrams . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

4.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

III Biosciences 18

1 Part 3

Odonates: Sensitive Indicators of Aquatic Ecosystem Health and Pollution

Taxonomic description of odonates seen in unpolluted waters 19

CONTENTS

1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

1.2 Species Description of Odonata Species Strictly Found in Fresh, Unpolluted Waters. . . . . . . . 19

2 Key Epigenetic Clocks: Shedding Light on Signiﬁcant Aging Biomarkers 23

2.1 Horvarth Clock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

2.2 Hannum Clock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.3 Weidner Clock . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.4 Levin clock (DNAm PhenoAge) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24

2.5 Lu clock (GrimAge Clock) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

2.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25

Part I

Artiﬁcial Intelligence and Machine Learning

Astronomy: Gazing into the Future with AI

by Atharva Pathak

airis4D, Vol.2, No.4, 2024

www.airis4d.com

1.1 Introduction

Astronomy, the age-old study of stars, galaxies,

and the cosmos, is undergoing a revolution, not with

a new telescope, but with the help of artiﬁcial intel-

ligence (AI) and machine learning (ML). These pow-

erful tools are assisting astronomers in unravelling the

universe’s mysteries at an unprecedented pace.

As famed astronomer Carl Sagan once said, ”Some-

where, something incredible is waiting to be known”.

AI and ML are helping us discover these incredible

things by sifting through massive datasets collected

by powerful telescopes like the James Webb Space

Telescope. Imagine a telescope capturing millions of

images every night – a human astronomer would be

overwhelmed! Here’s where AI steps in.

One exciting area is using AI to classify galaxies.

Traditionally, this was a slow, manual process. Now,

AI algorithms can analyze vast amounts of data, iden-

tifying diﬀerent types of galaxies, like majestic spirals

or swirling ellipticals, much faster and with higher ac-

curacy. This frees up astronomers’ time to focus on

deeper analysis and theorizing about the formation and

evolution of these celestial structures.

Another fascinating application is using AI to look

for exoplanets, i.e., planets orbiting stars beyond our

solar system. These alien worlds often hide in the faint

starlight of their suns. ML algorithms can analyze

subtle dips in a star’s brightness, which might indicate

a planet passing in front of it. The transit method

has helped discover thousands of exoplanet candidates,

some of which could harbour life!

However, AI’s potential goes beyond classiﬁca-

tion and detection. Imagine AI-powered telescopes

that can observe the universe and propose scientiﬁc

hypotheses based on their ﬁndings! For example, AI

could analyze a never-before-seen object and suggest

potential explanations for its unusual properties. This

would be a game-changer, accelerating scientiﬁc dis-

covery in astronomy.

1.2 The Data Deluge: Upcoming

Astronomical Projects

Image Credits: https://utilitymagazine.com.au/analysing-the-data-ﬂood-opportunities-and-

challenges-in-a-changing-energy-market/

The future of astronomy with AI is wide open,

fueled by a coming data deluge(ﬂood).

Here are some upcoming projects that will gener-

ate massive datasets:

1.3 AI: The Astronomer’s Powerful Ally

Figure 1: The Vera C. Rubin Observatory or Large

Synoptic Survey Telescope (LSST).

The Vera C. Rubin Observatory or Large Synop-

tic Survey Telescope (LSST): Nicknamed the ”cosmic

movie camera”, LSST will scan the entire sky every

few nights for a decade, generating an estimated 200

petabytes (that’s 200,000,000,000,000,000 bytes!) of

data. This treasure trove will allow astronomers to

study everything from transient phenomena like ex-

ploding stars to the evolution of dark matter.

Figure 2: The Thirty-Meter Telescope (TMT).

The Thirty-Meter Telescope (TMT): This next-

generation telescope, currently under construction, will

have a mirror three times larger than current ones. This

will allow it to peer deeper into space and collect de-

tailed data on distant galaxies and exoplanets. The

sheer volume of information will require sophisticated

AI tools for analysis.

Figure 3: The Square Kilometer Array (SKA)

Radio Astronomy Projects: Powerful radio tele-

scopes like the Square Kilometer Array (SKA) are de-

signed to detect faint radio signals from across the

universe. These signals can reveal information about

black holes, the formation of stars and planets, and

even the very ﬁrst moments of the Big Bang. Process-

ing and interpreting this complex radio data will be a

perfect use case for AI algorithms.

1.3 AI: The Astronomer’s Powerful

Ally

The vast amounts of data generated by these projects

pose a signiﬁcant challenge for astronomers. Here’s

where AI comes in as a powerful ally:

Pattern Recognition: AI excels at ﬁnding patterns

in large datasets. This can help astronomers identify

subtle variations in stellar light curves, revealing new

classes of variable stars or even signs of extraterrestrial

intelligence.

Signal Processing: Radio astronomy data is of-

ten noisy and complex. AI algorithms can be trained

to ﬁlter out noise and extract meaningful information,

allowing astronomers to study faint and distant objects.

Simulations and Modeling: AI can be used to cre-

ate sophisticated simulations of the universe, helping

astronomers test theories about galaxy formation, dark

matter, and the nature of spacetime.

1.4 How Can You Get Involved?

Are you intrigued by the intersection of AI and

astronomy? You don’t need a PhD to get started! Here

are some ways you can delve into this exciting ﬁeld:

Citizen Science Projects: Several online plat-

forms allow you to contribute to astronomical research

by classifying galaxies or helping identify potential

exoplanets using actual telescope data. These projects

often have user-friendly interfaces and are a great way

to get your feet wet. (E.g. csa.pkc.org, zooniverse.org)

1.4 How Can You Get Involved?

Image Credits: illustration-community-citizen-science-boat-help-frits-ahlefeldt

Online Courses and Tutorials: Many universities

and institutions oﬀer free online courses or tutorials on

machine learning basics or using AI tools for astron-

omy. These resources can equip you with the funda-

mental knowledge to understand how AI is used in the

ﬁeld.

Image Credits:

https://www.skyatnightmagazine.com/space-science/artiﬁcial-intelligence-astronomy

References

1. https://www.skyatnightmagazine.com/space-science/

artiﬁcial-intelligence-astronomy

2. https://developer.nvidia.com/blog/ai-detects-gravitational-waves-faster-than-real-time/

3. https://www.wired.com/2017/03/astronomers-deploy-ai-unravel-mysteries-universe/

4. https://www.pbs.org/newshour/science/analysis-how-ai-is-helping-astronomers-study-the-universe

About the Author

Atharva Pathak currently work as a Soft-

ware Engineer & Data Manager for the Pune Knowl-

edge Cluster, A project under the Oﬃce of Principal

Scientiﬁc Advisor, Govt. of India & Supported by

IUCAA, Pune, IN. Before this, I was an Astronomer

at the Inter-University Centre for Astronomy & Astro-

physics, IUCAA. I have also worked on various free-

lance projects, development required for websites and

applications, And localization of diﬀerent software.

I am also a life member of Jyotirvidya Parisanstha,

India’s Oldest association of Amateur Astronomers,

and I look after the IOTA-India Occultation section

as a webmaster and data curator.

Part II

Astronomy and Astrophysics

Black Hole Stories-8

Light Ray Paths in General Relativity

by Ajit Kembhavi

airis4D, Vol.2, No.4, 2024

www.airis4d.com

In Black Hole Stories-5 (BH5) we considered how

we could make a transition from Newtonian gravity and

mechanics to the more complex situation of Einstein’s

theory of gravitation, which is the general theory of rel-

ativity. In Einstein’s theory space-time is curved, and

we have to reinterpret basic notions like the distance r

of the particle from the centre of the coordinates. We

also considered how conserved quantities, i.e. quanti-

ties like energy and momentum which remain constant

for a particle moving in a gravitational, can be deﬁned

in general relativity. In Black Hole Stories-6 (BH6) we

considered particle trajectories in the Schwarzschild

metric of a black hole and found that we could have

bound orbits, where a particle is trapped in the gravita-

tional well around the black hole. We also considered

orbits which can reach very large distances from the

black hole, and orbits along which a particle will fall

into the black hole. We will now consider the paths or

orbits followed by light rays in the gravitational ﬁeld of

a black hole. Here we will use the terms light rays and

photons interchangeably, depending on the context. So

instead of considering the path of a light ray, we could

equally well use the phrase photon orbit.

1.1 The Eﬀective Potential in General

Relativity for Light Rays

In BH6 we found that in general relativity, the path

of a particle in the gravitational ﬁeld of a black hole

is described by a time like geodesic, because a particle

with mass always moves with speed less than the speed

of light. The position of such a particle along the path

is given as a function of the proper time, which is the

time as measured by a clock moving with the particle.

As described in BH6, the nature of the path of a particle

with given energy and momentum can be understood

from the eﬀective potential V

e,S

without having to solve

the geodesic equations. For the Schwarzschild black

hole, the eﬀective potential V

e,S

is given by

We can ﬁnd a similar eﬀective potential for the

path of light rays, but there are some important dif-

ferences from our earlier considerations. In BH5 we

learned that the paths of light rays, i.e. photons, and

other particles with zero rest mass, are described by

null geodesics. For such geodesics the proper time in-

terval between any two points along the trajectory is

zero. So we clearly cannot use proper time for marking

positions along the path of a light ray. Instead we have

to us a quantity called the aﬃne parameter and the

equations of the null geodesic are given as a function

of this parameter.

Our analysis of timelike geodesics in the Schwarzschild

metric depended on two conserved quantities, energy E

and angular momentum L. These conserved quantities

can be deﬁned for light rays or photon orbits too. For

the gravitational ﬁeld around a black of mass M and

1.2 The Shape of Orbits of Light Rays or Photons Around a Schwarzschild Black Hole

Figure 1: A particle (yellow) approaches a black hole

(black) from a great distance. The impact parameter b

is shown. As the particle approaches the black hole,

its trajectory deviates from a straight line path. The

smaller the impact parameter, the greater is the devi-

ation due to closer approach to the black hole. Image

courtesy: Evan Halstead through LibreTexts Physics.

zero spin, which is a Schwarzschild black hole, analysis

of the null geodesics then leads to the equations

where b =

is known as the impact parameter,

which would be the distance of the light ray from the

centre at r=0 if it passed through without any bending,

as is shown in Figure 1. The greater the impact param-

eter, the lesser would be the eﬀect of the black hole on

the shape of the trajectory.

The eﬀective potential is given by

For timelike geodesics that we have described in

BH5-BH7, the geodesic equation and the eﬀective po-

tential depended on two quantities, energy E and angu-

lar momentum L. For the null geodesics the situation

is simpler. The trajectories depend only on the impact

parameter b=L/E deﬁned above, and not on the indi-

vidual values of E and L. The eﬀective potential W

depends only on M. The shape of the eﬀective potential

as a function of

is shown in Figure 2.

It is seen from the Figure 1 that the eﬀective po-

tential goes to zero for large values of r and plunges to

very large negative values for 2

< 3, i.e., r < 1.5r

Figure 2: The eﬀective potential W

as a function of

where r

is the Schwarzschild radius. Various

features in the ﬁgure are described in the text.

where r

is the Schwarzschild radius. The potential has

a maximum at 1.5r

, but no minimum. This is diﬀerent

from the case for timelike geodesics described in BH6.

There the potential had a minimum and a maximum,

so a potential well was present.

1.2 The Shape of Orbits of Light

Rays or Photons Around a

Schwarzschild Black Hole

The equation above for the r coordinate, has to be

supplemented by an equation for the angular coordinate

φ, and the change in the two coordinates as a function

of the aﬃne parameter determine the actual shape of

the orbit of a light ray or photon. This is very similar to

our considerations for timelike orbits in BH6. There,

because of the existence of a potential well, it was

possible for particles with mass to be trapped in the

gravitational potential, and to have orbits which go

round the black hole. The shape of the orbits were

like precessing ellipses in the general case, but when a

trapped particle had energy such that it was located at

the minimum of the potential well, then the orbits were

circular.

In the eﬀective potential for photons, there is no

minimum in the potential, and so a potential well is

not present. So there can be no orbits which go round

the black hole, but with one exception. If a photon

has just the correct impact parameter of b = 3

√

1.2 The Shape of Orbits of Light Rays or Photons Around a Schwarzschild Black Hole

then it is be located at the maximum of the potential,

as is shown by the large black dot in Fig 2. In this case

the radial coordinate r of the photon is constant, and

the photon is in a circular orbit around the black hole.

But such an orbit is unstable, i.e. if the photon were

to be nudged a bit, it would either escape to inﬁnity or

plunge into the black hole. One can imagine a swarm

of photons all with the correct impact parameter to be

at the maximum of the potential. Such a collection

of photons in circular orbits around the black hole is

known as a photon sphere.

If a photon approaches the black hole with impact

parameter b < 3

√

, then its r coordinate decreases

as shown by the green line in Figure 2 and the photon

eventually plunges into the black hole. The red line

represents the change in r coordinate of a particle ap-

proaching the black hole from a great distance with b >

√

. The value of r at which the red line meets the

eﬀective potential is the smallest r value reachable by

the photon. From this minimum the r value increases

so that the photon trajectory recedes from the black

hole.

The shape of the trajectories for various values

of the impact parameter are shown in Figure 3, with

the photons in all cases approaching the black hole

from a great distance. For impact parameter b = 0, the

trajectory is radial with a constant value of the angular

coordinate ϕ, and ends at the black hole. For b =

√

, the incoming photon is trapped into a circular

orbit with radius 1.5r

, which is marked as the photon

sphere in the ﬁgure. For values of b > 3

√

, the

photon arrives from a large distance, goes around the

black hole and returns to large values of r. For b <

√

, the trajectories always end on the black hole,

since the photon approaches the black hole too closely

to be able to escape from it.

Next Story: The strong gravitational ﬁeld of a

black hole can bend light paths so much that a suitably

placed distant observer wills see a grossly distorted im-

age of the regions around the black hole, which leads to

very interesting eﬀects. In forthcoming stories we will

consider some of these applications of light bending

that we have studied so far.

(Figure courtesy: Vojtech Ullmann.)

Figure 3: The shape of photon trajectories around

a Schwarzschild black hole for various values of the

impact parameter b. The quantity M in the ﬁgure

corresponds to our r

About the Author

Professor Ajit Kembhavi is an emeritus

Professor at Inter University Centre for Astronomy

and Astrophysics and is also the Principal Investiga-

tor of the Pune Knowledge Cluster. He was the former

director of Inter University Centre for Astronomy and

Astrophysics (IUCAA), Pune, and the International

Astronomical Union vice president. In collaboration

with IUCAA, he pioneered astronomy outreach ac-

tivities from the late 80s to promote astronomy re-

search in Indian universities. The Speak with an

Astronomer monthly interactive program to answer

questions based on his article will allow young enthu-

siasts to gain profound knowledge about the topic.

Does the Universe Speak the Language of

Radio Waves?

by Linn Abraham

airis4D, Vol.2, No.4, 2024

www.airis4d.com

2.1 Let there be Light

Everyone is familiar with light and its sources,

natural as well as artiﬁcial. The Sun, moon and the

stars are some of the most well known natural sources

of light. Bio-luminescence is also seen in nature in

forms of ﬁreﬂies etc. Fire was tamed by early men to

be used as a source of both light and heat. For a very

long time most of our lamps made use of ﬁre. The

electric bulb exploited the fact that substances glow

when heated to very high temperatures. Electricity

provided a controlled way to heat certain materials to

very high temperatures. It also provided a way to excite

electrons in a gas and make them emit light on their

own. Nowadays there exists more sophisticated ways to

produce light such as LEDs that make use of the ability

of semiconducting materials altered using a “doping”

process, to emit light.

2.2 An Electromagnetic Wave at

Heart

The great uniﬁcation of electricity and magnetism

took place when it came to be known that all magnetism

is ultimately linked to electric ﬁelds and conversely that

electricity can be generated just by changes in the mag-

netic ﬁeld. Consequently it was realized that light was

nothing more than an electromagnetic wave. However

this is only partly true. Because of the diﬀerence in

their frequencies and hence energies, visible light and

other forms of the electromagnetic spectrum manifest

diﬀerently in their interaction with matter. Also the

physical processes that lead to their generation are dif-

ferent. Combinedly this makes a world of diﬀerence

and diﬀerent observation windows in the electromag-

netic spectrum sheds light on a diﬀerent aspect or un-

derlying phenomenon regarding the objects of study.

Radio waves form a part of this electromagnetic spec-

trum, speciﬁcally the low frequency end of the spec-

trum.

2.3 Radio Waves Arriving A Little

Late to the Party

After Maxwell put forward the theory of electro-

magnetism and predicted the existence of electromag-

netic waves, Heinrich Hertz in 1887 became the ﬁrst

person to generate radio waves. It is interesting to note

that the unit of frequency itself is named after him.

A new wireless form of communication was born to

replace the telegraph and other sources of wired com-

munication. It might be an understatement to say that

this discovery of radio waves revolutionized communi-

cation. However because of their low frequecny and by

extension low energy, radio waves have little to no ef-

fect on living organisms. In contrast even the adjacent

regions of the spectrum like microwaves and infrared

has eﬀects on living organisms. This is probably why

the hand of evolution didn’t ﬁnd it worthy to endow

any living organism with radio wave detectors simi-

lar to how the eyes and ears are used to detect visible

2.4 Fundamental Processes that Generate EM Waves

light and sound waves. However imaginations of ex-

tra terrestrial life as portrayed in literature and ﬁlms

often depict aliens capable of directly communicating

with each other through antenna like structures on their

bodies. It is because of this handicap that radio waves

remained unknown for a long time and also why the

need exists to convert radio waves to other forms like

sound and light in order to enjoy content from our

favourite radio stations.

2.4 Fundamental Processes that

Generate EM Waves

2.4.1 Acceleration of charges

It is well known that the study of blackbody ra-

diation lead eventually to the discovery of quantum

mechanics and the quantum mechanical model of the

atom. The Bohr quantization of orbits was put for-

ward as an ad-hoc solution to a problem that could

not be addressed in classical physics. When trying to

know more about this problem, you come across the

often repeated statement that electric charges emit radi-

ation when they accelerate. Hence electrons revolving

around the nucleus of an atom cannot have stable or-

bits. The explanation for how this happens does not

seem to be that simple but is beyond the scope of this

article. If you take it as a given, a follow up question

may be asked, is there a relation between the acceler-

ation of the particle and the frequency of the emitted

radiation? The answer seems to be that it is not a sin-

gle frequency that is emitted but a range of frequencies.

However there must be some relation between the na-

ture of acceleration and nature of the distribution of

frequencies. Coming back to the blackbody radiation,

is acceleration of charges the fundamental processes

that generates the blackbody spectrum? It must be,

because blackbody radiation is fundamentally thermal

in nature and a system of particles at a non-zero tem-

perature undergoes vibrations, rotations and collisions

etc. which is capable of producing electromagnetic

radiations.

2.4.2 Quantum state transitions

The other well known way in which EM radia-

tion is generated is due to transitions between diﬀerent

quantum mechanical states of the system. For e.g. the

atomic emission lines in hydrogen and the hyperﬁne

structure line in hydrogen at 21 cm wavelength. These

two mechanisms of EM wave generation are some-

times considered to be the thermal sources of radiation.

Electromagnetic radiation can also be generated due to

certain non-thermal sources which we shall now see in

the context of radio wave generation.

2.5 Tuning into Radio Broadcasts

from the Cosmos

We saw that accelerating charges can produce

radio waves along with radiation in other frequency

ranges. And that the blackbody radiation is a manifes-

tation of such charge accelerations at the microscopic

level. Radio waves are generated artiﬁcially by us-

ing time varying electric currents ﬂowing in specially

shaped metal conductors called antennae. Soon after

the discovery of radio waves people started looking for

natural sources of radio waves that are around us. The

Sun is the biggest source of radio emission because

of its high temperature and proximity. Thunderstorms

are a source of radio noise since charged particles gets

accelerated during these events. The ﬁeld of radio

astronomy opened up soon with the contributions of

people like Karl Jansky, Grote Reber and Jocelyn Bell

amongst others, who discovered several astronomical

sources of radio waves. What other mechanism other

than the blackbody radiation that we have already seen

is capable of producing radio wave emissions?

2.5.1 Continuum Emissions from Ionized

Gas

Plasma is the most common form of matter in the

universe (99 percent of it). An ionized gas becomes

a plasma when enough of the atoms are ionized and

it exhibits collective behaviour. On Earth it can be

found in the ﬂash of a lightning and in auroras. Be-

yond the Earth’s atmosphere the Van Allen belts and

2.6 How Messages Get Changed by the Medium

the solar wind comprises of plasma. As mentioned be-

fore any body with a temperature above absolute zero

emits blackbody radiation across a range of radiation

including radio waves. However the region in which

the bulk of the energy is emitted depends on the tem-

perature of the body. For bulk emission in the radio

wave region the temperature has to be less than 10 K

which is true of dark dust clouds in the universe. Ther-

mal radiation has a characteristic that distinguishes it

from non-thermal sources of radio waves. It produces

a pure static hiss on a loudspeaker.

2.5.2 Non-thermal Sources of Radio Waves

The non-thermal source of radio waves include the

cyclotron, synchrotron and the astronomical masers.

Such radiation arises as a result of the interaction of

charged particles with magnetic ﬁelds. The ﬁelds

makes it move in a circular or spiral path and the

particle thus gets accelerated and radiates energy. In

contrast to thermal radiation where the energy radiated

increases with frequency. The intensity of non-thermal

radiation usually decrease with frequency.

2.6 How Messages Get Changed by

the Medium

The properties of the intervening media between

the source and the detector also aﬀects the observed

radio spectrum. When oppositely charged ions recom-

bine to a neutral state, the atom gets highly excited

and several transitions occur. The resulting lines in

emission or absorption are called recombination lines.

Some of these lines particularly those due to carbon

ions falls in the radio range of the spectrum. Another

eﬀect is due to the existence of quantized rotational

states of molecules that fall in the microwave and long

wavelength infrared regions of the spectrum. The spec-

tral lines themselves can undergo doppler shifting due

to the multiple reasons. This also aﬀects the observed

spectrum.

References

[1] Diane Fisher Miller. Basics of Radio Astronomy

for the Goldstone-Apple Valley Radio Telescope.

[2] Thomas L. Wilson, Kristen Rohlfs, Susanne

H¨uttemeister, and Kristen Rohlfs. Tools of Radio

Astronomy. Astronomy and Astrophysics Library.

Springer, New York, 5th ed edition, 2009. ISBN

978-3-540-85122-6.

[3] Radio Wave. https://en.wikipedia.org/wiki/Radio

wave.

[4] How and why do accelerating charges ra-

diate electromagnetic radiation?. https:

//physics.stackexchange.com/questions/65339/

how-and-why-do-accelerating-charges-radiate-electromagnetic-radiation.

[5] What is the relation between the fre-

quency of the light produced and the ac-

celeration of the charged particle. https:

//physics.stackexchange.com/questions/481679/

what-is-the-relation-between-the-frequency-of-the-light-produced-and-the-acceler.

[6] At the Fundamental Level, are Radio Waves and

Visible Light Produced in the Same Way? . https:

//physics.stackexchange.com/questions/498709/

at-the-fundamental-level-are-radio-waves-and-visible-light-produced-in-the-same?

rq=1.

About the Author

Linn Abraham is a researcher in Physics,

specializing in A.I. applications to astronomy. He is

currently involved in the development of CNN based

Computer Vision tools for prediction of solar ﬂares

from images of the Sun, morphological classiﬁca-

tions of galaxies from optical images surveys and ra-

dio galaxy source extraction from radio observations.

Sun to Black Holes : An X-ray Voyage

by P Aromal

airis4D, Vol.2, No.4, 2024

www.airis4d.com

Figure 1: PSLV C58 carrying XPoSat from Satish

Dhawan Space Centre.

Credits: ISRO

January 01, 2024

09:10 Hrs IST

3..

2..

1..

0..

Lift oﬀ Normal..

Bright morning of the new year’s day made brighter

by a majestic liftoﬀ PSLV C58 carrying India’s X-

ray Polarimetric satellite towards its destination..

Science enthusiasts in the country and around the globe

celebrated the new year with the successful launch of

India’s XPoSat, ﬁrst dedicated scientiﬁc satellite devel-

oped by Indian Space Research Organisation (ISRO)

to study the polarimetry and spectroscopy in x-ray do-

main.

Why do we(humans) send satellites to space to

study X-rays?

Why it is important to study X-rays?

Let us discuss the answers to these questions and the

questions that come up during our discussion.

3.1 Game of Hide-and-Seek

X-ray was discovered by W.C.Roentgen in the

year 1895 for which he was awarded the ﬁrst Nobel

Prize in Physics in 1901. Today we consider the elec-

tromagnetic radiation that lies between the energy 0.1

keV and 100 keV as X-rays. X-ray belongs to one of

the highest energies in the entire electromagnetic spec-

trum, which makes it an ionizing radiation. X-rays

ionize the atoms on its path and it makes it diﬃcult for

the cosmic x-rays to penetrate through the thick atmo-

sphere of the earth. In fact only a very small window

of the entire electromagnetic spectrum is visible from

earth’s surface, which are visible light and a portion

of radio waves. That’s why most of the telescopes we

see on earth’s surface are dedicated to visible light and

radio waves.To observe other wavelengths we should

place our telescope or detector in space.

3.1 Game of Hide-and-Seek

Figure 2: Opacity of diﬀerent wavelengths in the

electromagnetic spectrum as it passes the atmosphere.

Credits: NASA

Earth’s atmosphere won’t allow x-rays to penetrate

through it. Even though it makes hard to study about

x-rays, it also makes life on earth easier as the long

exposure to x-rays are harmful to living organisms.

It has become necessary to go to space to study x-

rays. In the middle of the twentieth century scientists

started attempts to send rockets into space having x-ray

detectors attached on top of them. Most of the X-ray

experiments in the earlier stages were part of military

space programmes, ﬁrst Solar X-rays were detected by

the Hermes program in 1948. Even Though X-rays are

detected from the sun, which is not strong so there was

no hope in detecting X-rays from stars which are light

years away from us.

A rocket launch on July 18 1962 changed the

entire outlook of X-ray astronomy!. The mission was

planned to measure x-ray emission from celestial ob-

jects; an Aerobee rocket was launched from White Sand

missile range in New Mexico. The experiment was led

by Riccardo Giacconi, father of X-ray Astronomy. On

analyzing the data, they found evidence of x-rays from

a source outside the solar system and as well as the cos-

mic x-ray background radiation. The source identiﬁed

by them was Scorpius X-1. In 2002 Riccardo Giac-

coni shared the Nobel Prize in physics for pioneering

contributions to astrophysics, which have led to the

discovery of cosmic X-ray sources. The discovery of

X-rays coming from sources outside our solar system

revitalized the ﬁeld of X-ray astronomy. Many more

balloons and rockets were sent into space to study cos-

mic x-rays and a new world was revealed in front of the

Figure 3: Riccardo Giacconi, Credits: NSTMF

science communities.

From the beginning of the 1970s scientists started

to send dedicated satellites to study cosmic x-ray sources.

Uhuru being the ﬁrst of its kind, and many advanced

satellites followed it. By the end of the 1970s satellites

with dedicated optics also launched. Chandra X-ray

Telescope, XMM-Newton, NuStar, AstroSat, NICER,

IXPE, XRISM, XPoSat and many other satellites joined

in the stellar wastness to study the energetic world of

X-rays and many proposed mega missions are on the

list, we can discuss about all the x-ray missions in de-

tails in the upcoming articles. Detectors that are one

million times more sensitive than the original detec-

tors used in the Aerobee rockets are currently in use,

following the discovery of cosmic x-rays 62 years ago.

By comparison, it took optical astronomy over 400

years to get this considerably greater sensitivity from

the telescopes used by Galileo!. Despite being one of

astronomy’s more recent ﬁelds, X-ray research has de-

veloped at a faster rate. We will discuss the importance

of studying cosmic X-rays in the coming articles.

3.1 Game of Hide-and-Seek

Figure 4: Image from the eROSITA X-ray telescope

shows the energetic Universe. Credits: Max Planck

Institute for Extraterrestrial Physics.

References:

120 YEARS SINCE THE DISCOVERY OF X-

RAYS

X-ray Polarimeter Satellite (XPoSat)

X-ray Astronomy

X-Ray Absorption

History of X-Ray Astronomy

A Hero of the Heroic Age of Astronomy

Santangelo, Andrea and Madonia, Rosalia and

Piraino, Santina A Chronological History of X-

Ray Astronomy Missions. Handbook of X-ray

and Gamma-ray Astrophysics.ISBN 9789811645440

About the Author

Aromal P is a research scholar in Depart-

ment of Astronomy Astrophysics and Space Engineer-

ing (DAASE) in IIT Indore. His research mainly focuses

on neutron stars and blackholes

Color - Magnitude Diagram, Part-3

by Sindhu G

airis4D, Vol.2, No.4, 2024

www.airis4d.com

4.1 Introduction

Astronomy depends on interpreting the subtle sig-

nals of light emitted by distant stars. The color-magnitude

diagram (CMD) emerges as a potent instrument in this

celestial investigation. It serves as a snapshot of stars,

unraveling the mysteries concealed within a star clus-

ter or even a whole galaxy. Picture a family portrait of

stars. A CMD resembles a unique rendition of this por-

trait, where instead of age, stars are categorized based

on their color and brightness. In astronomy, color cor-

responds to a star’s surface temperature: blue stars

emit intense heat, while red stars are comparatively

cooler. The Color Magnitude Diagram (CMD) stands

as a fundamental tool in astronomy, employed to study

star clusters and galaxies, oﬀering invaluable insights

into stellar evolution, age, metallicity, and distance.

This article explores the importance and interpretation

of CMDs within the ﬁeld of astrophysics.

4.2 Color - Magnitude Diagrams

A color-magnitude diagram (CMD) is like a graph

that shows how bright objects are compared to their

color. A color magnitude diagram (Figure: 1) is a

variant of the Hertzsprung-Russell diagram (Figure:

2). While the Hertzsprung-Russell (H-R) diagram is a

summary of temperatures and magnitudes of individ-

ual stars, a color magnitude diagram (CMD) is dedi-

cated to the study of star clusters. On the HRD, the

brightness of stars goes up the graph, and their temper-

ature or type of star goes across. This helps us group

stars based on where they are in their life cycle, like if

they’re on the main sequence or in the giant phase. A

color-magnitude diagram is a graphical representation

of the characteristics of stars within a speciﬁc region

of space. It plots two essential properties of stars:

their brightness (magnitude) and their color. The ver-

tical axis typically represents the magnitude, which is a

measure of a star’s brightness as seen from Earth. The

horizontal axis represents the color of the stars, usually

derived from the diﬀerence in brightness between two

diﬀerent wavelengths or ﬁlters, such as blue and visual

(B-V) or infrared (V-K).

Figure 1: Observed Colour-Magnitude Diagram.

Credit: Laura Porter

4.3 Interpreting the Diagram

Figure 2: Schematic HRD Credit: ESO

In real observations, the brightness of stars, which

is related to how much light they give oﬀ, can be used

to guess how bright they really are. This works well

for star clusters because all the stars are about the same

distance away and get dimmed by the same amount by

dust between us and them. Also, the color diﬀerence

between stars, like the diﬀerence between blue and red,

tells us about their temperature because diﬀerent colors

mean they give oﬀ diﬀerent types of light.

HRDs and CMDs are super helpful for scientists to

learn about stars and how they change over time. They

can compare theoretical HRDs with ones made from

real observations to see if their ideas are right. CMDs

of star clusters also help ﬁgure out how far away they

are and how old the stars in them are.

It serves as a powerful instrument for understand-

ing the life cycle of stars within a cluster or galaxy.

Color-magnitude diagrams (CMDs) excel in their util-

ity when analyzing star clusters, which consist of stars

that form together. Because these stars share similar

ages and distances, their CMD serves as a distinctive

identiﬁer. The arrangement of stars on the diagram

provides insights into the cluster’s age and the devel-

opmental phases of its stellar ensemble. Young clusters

tend to exhibit a prevalence of hot, blue stars, whereas

older clusters showcase a higher proportion of red gi-

ants.

CMDs extend beyond the realm of star clusters;

astronomers employ them to investigate entire galax-

ies. Through scrutinizing the collective arrangement

of stars depicted on a galactic CMD, they can infer

the galaxy’s age, composition, and the timeline of star

formation events. These diagrams serve as formidable

instruments for astronomers, revealing the mysteries

concealed within stars and galaxies. By analyzing the

coloured patterns within these celestial snapshots, we

can weave together the expansive saga of stellar evolu-

tion and the boundless expanse of our universe.

4.3 Interpreting the Diagram

Main Sequence: The most prominent feature of

a CMD is the main sequence, a diagonal band running

from the upper left (bright and blue stars) to the lower

right (faint and red stars). This sequence represents

stars undergoing hydrogen fusion in their cores, the

main energy-producing mechanism for most stars, in-

cluding our Sun. Stars spend the majority of their lives

on the main sequence, where they maintain a stable bal-

ance between inward gravitational forces and outward

radiation pressure.

Red Giants and Supergiants: Above and to the

right of the main sequence lie red giants and super-

giants. These are evolved stars that have exhausted their

core hydrogen fuel and have expanded and cooled as

a result. They shine brightly due to their large surface

area but are cooler than main-sequence stars, giving

them a reddish hue.

White Dwarfs: At the lower left of the diagram,

we ﬁnd white dwarfs. These are the remnants of low

to medium-mass stars (such as our Sun) after they have

exhausted their nuclear fuel. White dwarfs are incred-

ibly dense objects, typically about the size of Earth but

with masses comparable to that of the Sun. They emit

faint light and appear white or bluish-white.

Stellar Clusters: Stellar clusters, groups of stars

that formed from the same molecular cloud, often pop-

ulate CMDs. These clusters provide astronomers with

a wealth of information, as the stars within them share

similar ages and compositions. By analyzing the dis-

tribution of stars in a cluster’s CMD, astronomers can

determine its age, distance, and chemical composition.

4.4 Key Features of the Color Magnitude Diagram

4.4 Key Features of the Color

Magnitude Diagram

Main Sequence and Paths of Development: Stars

of diﬀerent masses take distinct paths of development

on the CMD. The main sequence represents stars un-

dergoing hydrogen fusion, while the red giant area indi-

cates stars that have exhausted their hydrogen reserves

and moved on to the subsequent stage of stellar evo-

lution. CMDs serve as invaluable tools for studying

stellar evolution. By comparing observed diagrams

with theoretical models, astronomers can reﬁne our

understanding of the processes governing star forma-

tion, evolution, and eventual fate. The positions of

stars on the CMD provide crucial information about

their masses, ages, and compositions.

Metallicity and Age Inferences: The CMD can

provide insights into a cluster’s metallicity, with el-

evated metal content being signaled by speciﬁc color

indices. Furthermore, by scrutinizing how stars are dis-

persed on the diagram, astronomers can approximate

the cluster’s age.

Distance Determination: The intrinsic bright-

ness of stars varies with their properties, making CMDs

useful for estimating distances to stellar populations.

Using the distance modulus formula, astronomers can

estimate the distance to a star cluster by comparing the

absolute magnitude of stars with established properties

to those within the cluster. By comparing observed

brightness with theoretical expectations, astronomers

can determine the distances to clusters, galaxies, and

even the farthest reaches of the universe.

4.5 Insights from Color-Magnitude

Diagrams

CMDs oﬀer insight into how stars evolve in a clus-

ter, showing us things like how white dwarfs form and

why there are blue stragglers. In the context of galax-

ies, CMDs can reveal the bimodal distribution of red

and blue galaxies, highlighting the evolution of galac-

tic populations over cosmic time. Studying CMDs

in diﬀerent regions of galaxies allows astronomers to

reconstruct their evolutionary histories. By analyz-

ing the ages, metallicities, and spatial distributions of

stars, scientists can unravel the complex interplay of

processes shaping galactic evolution over billions of

years.

4.6 Conclusion

Studying how stars are spread out on the CMD

helps scientists learn a lot about the characteristics and

histories of objects in cosmos. This helps us under-

stand more about how the universe is made up. Using

CMDs helps astronomers learn even more about uni-

verse. They ﬁnd new things and learn more about how

things work in universe. CMD serves as a window

into the intricate dance of stellar evolution, oﬀering in-

sights into the nature of stars, their characteristics, and

the dynamics of the universe. In the upcoming article,

we will delve further into the topic of CMD.

References:

Colour-Magnitude Diagrams of Star Clusters:

Determining Their Relative Ages

Color Magnitude Diagram of Cluster M67

ASTR469 Lecture 4: HR Diagram and Color-

magnitude Diagrams

Cluster Colour-Magnitude Diagrams

Color-Magnitude Diagram Lab Manual

The colour-magnitude diagramme

About the Author

Sindhu G is a research scholar in Physics

doing research in Astronomy & Astrophysics. Her

research mainly focuses on classiﬁcation of variable

stars using diﬀerent machine learning algorithms. She

is also doing the period prediction of diﬀerent types

of variable stars, especially eclipsing binaries and on

the study of optical counterparts of X-ray binaries.

Part III

Biosciences

Part 3

Odonates: Sensitive Indicators of Aquatic

Ecosystem Health and Pollution

Taxonomic description of odonates

seen in unpolluted waters

by Geetha Paul

airis4D, Vol.2, No.4, 2024

www.airis4d.com

1.1 Introduction

The study in this volume emphasises the signif-

icance of Odonata, including dragonﬂies and dam-

selﬂies, as bioindicators for evaluating ecosystem health

and delving into the taxonomy of unpolluted freshwa-

ter odonates. Odonates are crucial in oﬀering valu-

able insights into ecosystem well-being. Speciﬁcally,

species such as Euphaea frasseri, Neurobasis chinen-

sis, Vestalis apicalis, Vestalis gracilis, and Heliocypha

bisignata are highlighted as being speciﬁc to unpol-

luted freshwater habitats, showcasing their importance

in environmental assessments. Odonates bridge the

gap between aquatic and terrestrial habitats, providing

health information. Various water quality parameters,

such as pH, conductivity, and dissolved oxygen, inﬂu-

ence their distribution, abundance, and diversity. Stud-

ies have shown that increased conductivity levels cor-

relate with higher pollution, while changes in species

composition reﬂect environmental disturbances. No-

tably, speciﬁc odonate species are known to be sensitive

to pollution, serving as valuable indicators of overall

freshwater ecosystem health. It explains the unique

characteristics of Odonates that make them suitable for

biomonitoring.

1.2 Species Description of Odonata

Species Strictly Found in Fresh,

Unpolluted Waters.

In freshwater, unpolluted waters, Odonata species

exhibit distinct characteristics. These species are typi-

cally sensitive to pollution and habitat alterations, mak-

ing them valuable bioindicators for assessing ecosys-

tem health. They often have well-resolved taxonomy,

are diurnal adults, and have a broad range of environ-

mental sensitivity across diﬀerent species. In terms of

physical appearance, these Odonata species may have

metallic green colouration, dark brown eyes above and

greenish yellow eyes below, and transparent wings with

a bluish tinge. Their distribution and abundance are

signiﬁcantly inﬂuenced by factors in the quality of wa-

ter parameters. These species are commonly used in

ecological assessments due to their sensitivity to envi-

ronmental changes, making them crucial for monitor-

ing the quality of freshwater habitats.

1.2:1 Euphaea fraseri, also known as the Malabar

Torrent Dart, belongs to the order Odonata, family of

1.2 Species Description of Odonata Species Strictly Found in Fresh, Unpolluted Waters.

Figure 1: Euphaea fraseri (m) Euphaea fraseri (f)

Euphaeidae. Here is the taxonomic description based

on the provided sources:

Kingdom: Animalia

Phylum: Arthropoda

Class: Insecta

Order: Odonata

Family: Euphaeidae

Genus: Euphaea Selys, 1840

Scientiﬁc Name: Euphaea fraseri

Authority: Laidlaw, 1920

Common Name: Malabar Torrent Dart

IUCN Red List Category: Least Concern

Endemic Status: Endemic to the Western Ghats

Euphaea fraseri is commonly found in hill streams

at elevations ranging from about 90m to 1000m. Males

are more common than females, with males often seen

using the same perch for days. The breeding season

for Euphaea fraseri spans from May to December, and

the larvae can be collected throughout the year. The

species faces threats due to potential habitat pollution

from anthropogenic activities.

Size: Euphaea fraseri is a medium-sized dam-

selﬂy.

Colouration: Male: The male has a black head

with brown-capped pale grey eyes. Its thorax is black

with sky-blue ante humeral and reddish-yellow humeral

stripes. The base of the thorax’s lateral sides is red.

The legs are red, with the ﬁrst pair being dark. The

wings are narrower than Euphaea cardinalis, with hind

wings shorter than fore wings. The fore-wings are

transparent with brown on the apices, while the hind-

wings are transparent with a broad black portion from

the apices. The abdomen is bright red up to segment 7,

with the apical third of segment 7 to the end segment

being black. The anal appendages are black. Female:

The female is short and robust, with the ochreous-red

colour of the male replaced by yellow. All wings are

transparent, enfumed with black in adults. The black

abdomen has yellow lateral stripes up to segment 6,

continuing to segment 7. Segment 8 is narrow, and

segment 9 has a broad yellow apical annule covering

the dorsal half.

Habitat: Euphaea fraseri breeds in hill streams

but at lower elevations. Males are typically found on

low herbage along the banks or in the middle of streams.

Figure 2: Neurobasis chinensis (m) Neurobasis chi-

nensis (f)

1.2:2 Neurobasis chinensis or Stream glory is a

common species distributed across much of Asia.

Kingdom: Animalia

Phylum: Arthropoda

Class: Insecta

Order: Odonata

Family: Calopterygidae

Genus: Neurobasis

Species: Neurobasis chinensis

Authority: Linnaeus, 1758

Common Name: Stream Glory

IUCN Red List Category: Least Concern

Male: The male Neurobasis chinensis is a large

metallic bronze-green coloured damselﬂy with trans-

parent fore-wings tinted in pale yellow and hind-wings

that are opaque in brilliant metallic green or peacock-

blue, displaying colours to attract females. Female:

The female Neurobasis chinensis is very similar to

the male but has transparent wings that are light cof-

fee brown with white wing spots and creamy yellow

patches at the nodes. These diﬀerences in coloura-

tion and wing characteristics between male and female

Neurobasis chinensis are essential for species identiﬁ-

cation and play a role in their reproductive behaviours

and interactions.

Size: Neurobasis chinensis is a large-sized dam-

selﬂy.

1.2 Species Description of Odonata Species Strictly Found in Fresh, Unpolluted Waters.

Habitat: Neurobasis chinensis breeds in forest

streams, with males maintaining territories along mod-

erately fast-ﬂowing streams. The species is typically

found near water bodies, and the female lays eggs in

submerged vegetation, while the naiads have speciﬁc

adaptations for their aquatic habitat.

Figure 3: Heliocypha bisignata (m) Heliocypha

bisignata (m)

1.2:3 Heliocypha bisignata, the Stream Ruby, be-

longs to Odonata and the family Chlorocyphidae. Here

is the taxonomic description based on the provided

sources:

Kingdom: Animalia

Phylum: Arthropoda

Class: Insecta

Order: Odonata

Family: Chlorocyphidae

Genus: Heliocypha Fraser, 1949

Species: Heliocypha bisignata

Authority: Hagen, 1853

Common Name: Stream Ruby

IUCN Red List Category: Least Concern

Male: The male Heliocypha bisignata has an ab-

domen measuring about 19 to 20 mm. It typically has

hind wings of about 24 to 25 mm. The male dam-

selﬂy displays distinct features such as black and red

colouration, with red-coloured iridescent streaks on its

wings, which are longer than its abdomen. Female:

The female Heliocypha bisignata has a slightly smaller

abdomen, measuring about 15 to 17 mm. The hind

wings of the female are similar in size to the male,

around 24 to 25 mm. The female damselﬂy resembles

the male but with more pronounced markings. These

physical diﬀerences in size and colouration between the

male and female Heliocypha bisignata allow for their

easy visual distinction within the species. Heliocypha

bisignata is a species of damselﬂy endemic to speciﬁc

regions, characterized by its unique features within the

Chlorocyphidae family.

Size: Heliocypha bisignata is a medium-sized

damselﬂy.

Habitat: Heliocypha bisignata’s habitat includes

various environments such as hill streams, rocks, ﬂoat-

ing logs, grassy areas, and forest streams. This dam-

selﬂy species is adapted to live in these habitats, show-

casing its ecological diversity and ability to thrive in

diﬀerent settings. The male and female Heliocypha

bisignata, also known as the Stream Ruby, can be dis-

tinguished based on their physical characteristics:

Figure 4: . Vestalis apicalis (m) Vestalis apicalis (f)

1.2:4 Vestalis apicalis is a species of damselﬂy

belonging to the family Calopterygidae, found in In-

dia and Sri Lanka. It is characterized by its metallic

emerald-green colouration, brown-capped yellowish-

green eyes, and blackish-brown tips on the apices of

its wings. This species breeds in forest streams and is

commonly observed resting in groups among bushes

in forest paths and shades,

Kingdom: Animalia

Phylum: Arthropoda

Class: Insecta

Order: Odonata

Suborder: Zygoptera

Family: Calopterygidae

Genus: Vestalis

Species: V. apicalis

Authority: Selys, 1853

Common Name: Black-tipped forest glory

IUCN Red List Category: Least Concern

Size: Vestalis apicalis is a large-sized damselﬂy.

Habitat: This species breeds in forest streams

and is commonly observed resting in groups among

bushes in forest paths and shades, often seen alongside

Vestalis gracilis.Vestalis apicalis, black-tipped forest

glory, is a species of damselﬂy belonging to the fam-

1.2 Species Description of Odonata Species Strictly Found in Fresh, Unpolluted Waters.

ily Calopterygidae, found in India and Sri Lanka. It

is characterised by its metallic emerald-green coloura-

tion, brown-capped yellowish-green eyes, and blackish-

brown tips on the apices of its wings. Male: The male

Vestalis apicalis is described as iridescent green with a

yellow and black underside, brown legs, blue-tinged

transparent wings, and dark brown eyes above and

greenish yellow below. Female: The female Vestalis

apicalis is likely to exhibit similar characteristics to

the male but with some diﬀerences in colouration and

markings, which may be pale-coloured in females.

Figure 5: Vestalis gracilis (m) Vestalis gracilis (m)

1.2:5 Vestalis gracilis is a damselﬂy species be-

longing to the family Calopterygidae, commonly known

as the Clear-winged Forest Glory. This species is

widely distributed from eastern India to Vietnam and

Peninsular Malaysia throughout the Oriental region.

Kingdom: Animalia

Phylum: Arthropoda

Class: Insecta

Order: Odonata

Suborder: Zygoptera

Family: Calopterygidae

Genus: Vestalis

Species: Vestalis gracilis

IUCN Red List Category: Least Concern

Size: Vestalis gracilis is a large-sized damselﬂy.

Habitat: Vestalis gracilis breeds in forest streams

and is frequently seen resting in clusters among bushes

along forest paths and shaded areas, often coexisting

with Vestalis apicalis. Known for its clear-winged ap-

pearance, it thrives in forested river habitats, partic-

ularly in regions with slow-moving water and dense

forest cover. Typically found near sluggish wooded

streams, it can be observed at elevations up to 1000

meters. Male: The male Vestalis gracilis is a large

and elegant damselﬂy with an abdomen length ranging

from 45 to 46 mm and hindwing length from 34 to 38

mm. It displays a metallic green colouration, with dark

brown eyes above and greenish-yellow eyes below. The

thorax and abdomen shimmer in emerald green above,

while the thorax is yellow and the abdomen is black

below. Legs are brown, and the wings are transparent

with a bluish tinge, lacking wing spots. Female: The

female Vestalis gracilis has an abdomen length varying

from 43 to 50 mm and a hindwing length from 36 to

39 mm. It exhibits a duller greenish-brown colouration

compared to the male. The female closely resembles

the male but has a stout abdomen and prominent caudal

appendages.

References

https://indiabiodiversity.org/species/show/227144

https://en.wikipedia.org/wiki/Neurobasis chinensis.

https://doi.org/10.1093/oso/9780192898623.003.

0026 Pages 371–384

https://intapi.sciendo.com/pdf/10.1515/eko-2017-

0030

About the Author

Geetha Paul is one of the directors of

airis4D. She leads the Biosciences Division. Her

research interests extends from Cell & Molecular Bi-

ology to Environmental Sciences, Odonatology, and

Aquatic Biology.

Key Epigenetic Clocks: Shedding Light on

Signiﬁcant Aging Biomarkers

by Jinsu Ann Mathew

airis4D, Vol.2, No.4, 2024

www.airis4d.com

In our previous article, we explored the fascinating

world of DNA methylation and its role in unveiling

biological age through epigenetic clocks. These clocks,

built on the foundation of DNA methylation patterns,

oﬀer a window into our body’s internal clock, often

ticking at a diﬀerent pace than our chronological age.

While DNA methylation is crucial for these clocks,

there’s a whole variety of them out there, each with

its own way of showing us how we age and why it

matters for our health. So, let’s take a journey through

these diﬀerent clocks, discovering how they help us

understand the secrets of aging and staying healthy.

2.1 Horvarth Clock

The Horvath Clock, named after its creator Dr.

Steve Horvath, is a groundbreaking epigenetic clock

developed in 2013. It measures biological age based on

DNA methylation patterns across the genome. Unlike

traditional measures of age that rely solely on count-

ing years since birth, the Horvath Clock oﬀers a more

nuanced and dynamic perspective on aging, reﬂecting

the biological changes occurring within an individual’s

cells over time(Figure 1).

This ingenious clock works by analyzing the methy-

lation patterns at 353 speciﬁc CpG sites on our DNA.

CpG sites are speciﬁc regions in the DNA where cyto-

sine nucleotides are followed by guanine nucleotides,

and they are known to undergo age-related changes in

methylation levels. By examining these changes, the

Horvath Clock can discern patterns associated with

(image courtesy:https://newsroom.ucla.edu/releases/ucla-scientist-uncovers-biological-248950)

Figure 1: llustration from Horvath’s paper highlight-

ing the concept of epigenetic clocks in human aging.

chronological age and use them to predict an individ-

ual’s biological age with remarkable accuracy.

One of the deﬁning features of the Horvath Clock

is its versatility. Unlike some other epigenetic clocks,

which may be limited to speciﬁc tissues or cell types,

the Horvath Clock has been shown to accurately predict

biological age across a wide range of tissues and organ-

isms. Whether it’s blood, brain, saliva, or even diﬀerent

species like humans, mice, or chimpanzees, the Hor-

vath Clock demonstrates its robustness and reliability

in estimating biological age across diverse biological

contexts.

One key aspect of Horvath clocks is their ability

to predict health outcomes and lifespan based on epi-

genetic age. These clocks have been associated with

2.2 Hannum Clock

various age-related conditions and diseases, such as

type 2 diabetes, chronic obstructive pulmonary disease

(COPD), and ischemic heart disease. By incorporating

data from diﬀerent tissue types and utilizing machine

learning methods, Horvath’s clocks oﬀer valuable in-

sights into the impact of lifestyle interventions on epi-

genetic aging.

The Horvath clock isn’t perfect. It’s primarily de-

signed for blood-based analysis, and methylation pat-

terns can vary slightly across diﬀerent tissues. How-

ever, its groundbreaking approach has paved the way

for further development of epigenetic clocks, opening

doors for exciting possibilities in aging research, dis-

ease risk assessment, and the evaluation of interven-

tions aimed at promoting healthy longevity.

2.2 Hannum Clock

The Hannum clock, developed in 2013, is based

on analyzing the methylation levels at 71 speciﬁc sites

(CpG sites) on your DNA in blood cells. Researchers

used a large dataset of blood samples with known

chronological ages. By analyzing the methylation pat-

terns at the 71 identiﬁed CpG sites in each sample, they

were able to establish a statistical relationship between

the methylation proﬁle and chronological age. This re-

lationship formed the foundation of the Hannum clock

– a mathematical model that can predict biological age

based on the methylation pattern at these speciﬁc CpG

sites in a new blood sample.

The Hannum clock shows promise in estimating

biological age based on blood samples. However,

the clock is speciﬁcally designed for blood analysis.

This means accuracy in other tissues may be limited.

Lifestyle choices can also inﬂuence DNA methylation,

potentially causing the clock to reﬂect an accelerated

or decelerated biological age compared to your chrono-

logical age.

2.3 Weidner Clock

The Weidner clock, developed a year after the

Hannum clock in 2014, is another innovative tool in the

ﬁeld of epigenetics. Similar to Hannum’s invention, it

estimates biological age through DNA methylation, but

with a key diﬀerence: simplicity.

Unlike the Hannum clock’s analysis of 71 CpG

sites, the Weidner clock takes a minimalist approach.

It focuses on just three meticulously chosen CpG sites

within speciﬁc genes:

ITGA2B (integrin, alpha 2b): This gene plays

a role in cell adhesion and signaling.

ASPA (aspartoacylase): This gene encodes an

enzyme involved in amino acid metabolism.

PDE4C (phosphodiesterase 4C, cAMP speciﬁc):This

gene helps regulate a cellular signaling molecule.

Researchers identiﬁed these three CpG sites be-

cause they exhibit strong and consistent age-related

methylation changes in blood cells. The Weidner clock,

despite its simplicity, has shown surprising accuracy in

estimating biological age from blood samples. How-

ever, its focus on just three CpG sites comes with a

trade-oﬀ. Compared to the Hannum clock, it might be

slightly less accurate. One key advantage of the Weid-

ner clock lies in its cost-eﬀectiveness. Analyzing only

three CpG sites requires a simpler and less expensive

technology called pyrosequencing, making it a more

accessible tool for wider applications.

2.4 Levin clock (DNAm PhenoAge)

The Levin clock, also known as DNAm Phe-

noAge, is an epigenetic clock developed by Morgan

Levine from the Yale Center for Research on Aging in

2018. It is based on 513 CpG sites and aims to predict

variables related to physiological dysregulation, dis-

ease susceptibility, disability risk, and mortality among

individuals of the same age group.

While previous clocks like Hannum relied solely

on DNA methylation patterns, and Weidner focused on

a minimal set of CpG sites, DNAm PhenoAge takes a

multi-faceted approach. It incorporates DNA methy-

lation data alongside other factors known to inﬂuence

biological aging. This includes speciﬁc blood test re-

sults that reﬂect overall health status, such as albumin

and glucose levels. It might also take into account cell

counts, particularly the percentage of lymphocytes, a

type of white blood cell that provides clues about im-

2.5 Lu clock (GrimAge Clock)

mune function, which often declines with age. By

integrating this broader range of data points, DNAm

PhenoAge strives to provide a more holistic and nu-

anced assessment of biological age.

Studies suggest that DNAm PhenoAge oﬀers su-

perior accuracy compared to its predecessors in pre-

dicting various age-related outcomes. This includes

mortality risk, an individual’s physical capabilities, and

even healthspan, which refers to the duration of good

health in a person’s life. These advancements hold

promise for several potential applications. In personal-

ized medicine, doctors could leverage this information

to tailor preventive healthcare strategies based on an

individual’s biological age in relation to their chrono-

logical age. Researchers could also utilize DNAm Phe-

noAge in clinical trials to assess the eﬀectiveness of

anti-aging therapies by monitoring changes in biolog-

ical age. Furthermore, this clock can contribute sig-

niﬁcantly to a deeper understanding of the biological

processes underlying aging itself.

While DNAm PhenoAge stands out for its com-

prehensiveness, it’s important to acknowledge limita-

tions. The technology used to analyze the combined

data points might be more expensive and less readily

available compared to simpler clocks. Additionally,

like other epigenetic clocks, DNAm PhenoAge is pri-

marily optimized for blood samples. Its accuracy in

other tissues needs further investigation.

2.5 Lu clock (GrimAge Clock)

The GrimAge Clock, also known as the Lu clock,

is an epigenetic clock developed by Steve Horvath in

collaboration with Daniel W. Belsky, Ian Deary, and

others. It was introduced in 2019 as an advancement

in the ﬁeld of epigenetic aging research.

The GrimAge Clock is notable for its focus on

age-related mortality risk and its incorporation of DNA

methylation-based biomarkers associated with various

age-related health outcomes. Unlike other epigenetic

clocks that primarily estimate chronological age, the

GrimAge Clock aims to estimate biological age with

a particular emphasis on predicting mortality risk and

age-related diseases.

The development of the GrimAge Clock involved

the identiﬁcation of DNA methylation patterns associ-

ated not only with chronological age but also with mor-

tality risk and various age-related health conditions,

such as cardiovascular disease, cancer, and Alzheimer’s

disease. This was achieved by analyzing large-scale

DNA methylation datasets from diverse populations.

The GrimAge Clock is unique in that it incor-

porates DNA methylation-based biomarkers known as

”epigenetic aging signatures” that are associated with

smoking behavior, inﬂammation, and other factors im-

plicated in aging-related processes. By including these

additional biomarkers, the GrimAge Clock provides a

more comprehensive assessment of biological age and

mortality risk compared to other epigenetic clocks.

2.6 Conclusion

In conclusion, the ﬁeld of epigenetic clocks has

emerged as a powerful tool for understanding biological

aging. Pioneering clocks like the Horvarth clock and

Hannum clock (2013) laid the groundwork by analyz-

ing DNA methylation patterns to estimate biological

age. The Weidner clock (2014) followed, oﬀering a

simpler yet accurate approach. Building upon these,

DNAm PhenoAge (Levin clock, 2015) incorporated

additional factors like chronological age and blood test

results for a more comprehensive assessment. Finally,

the GrimAge clock (2018) stands out for its unique fo-

cus on predicting mortality risk based on speciﬁc DNA

methylation patterns.

Despite their diﬀerences, these clocks all oﬀer

valuable insights into the biological aging process.

They hold promise for personalized medicine approaches

that consider an individual’s biological age, potentially

leading to more targeted preventive healthcare strate-

gies and interventions. As research progresses, epi-

genetic clocks like the Lu DNAmTL clock, exploring

speciﬁc aspects of aging like telomere function, might

further reﬁne our understanding of how our bodies age

at a cellular level. While limitations exist, particularly

regarding tissue speciﬁcity and the inﬂuence of fac-

tors beyond aging, epigenetic clocks represent a sig-

niﬁcant leap forward in the ﬁght against age-related

2.6 Conclusion

health challenges. The future holds immense potential

for harnessing the power of these clocks to promote

healthy aging and improve overall longevity.

References

Epigenetic clock: A promising biomarker and

practical tool in aging

Epigenetic Clocks: In Aging-Related and Com-

plex Diseases

Epigenetic clock: a promising mirror of ageing

DNA methylation age of human tissues and cell

types

Genome-wide Methylation Proﬁles Reveal Quan-

titative Views of Human Aging Rates

Aging of blood can be tracked by DNA methy-

lation changes at just three CpG sites

DNA methylation GrimAge strongly predicts lifes-

pan and healthspan

About the Author

Jinsu Ann Mathew is a research scholar

in Natural Language Processing and Chemical Infor-

matics. Her interests include applying basic scientiﬁc

research on computational linguistics, practical appli-

cations of human language technology, and interdis-

ciplinary work in computational physics.

About airis4D

Artiﬁcial Intelligence Research and Intelligent Systems (airis4D) is an AI and Bio-sciences Research Centre.

The Centre aims to create new knowledge in the ﬁeld of Space Science, Astronomy, Robotics, Agri Science,

Industry, and Biodiversity to bring Progress and Plenitude to the People and the Planet.

Vision

Humanity is in the 4th Industrial Revolution era, which operates on a cyber-physical production system. Cutting-

edge research and development in science and technology to create new knowledge and skills become the key to

the new world economy. Most of the resources for this goal can be harnessed by integrating biological systems

with intelligent computing systems oﬀered by AI. The future survival of humans, animals, and the ecosystem

depends on how eﬃciently the realities and resources are responsibly used for abundance and wellness. Artiﬁcial

intelligence Research and Intelligent Systems pursue this vision and look for the best actions that ensure an

abundant environment and ecosystem for the planet and the people.

Mission Statement

The 4D in airis4D represents the mission to Dream, Design, Develop, and Deploy Knowledge with the ﬁre of

commitment and dedication towards humanity and the ecosystem.

Dream

To promote the unlimited human potential to dream the impossible.

Design

To nurture the human capacity to articulate a dream and logically realise it.

Develop

To assist the talents to materialise a design into a product, a service, a knowledge that beneﬁts the community

and the planet.

Deploy

To realise and educate humanity that a knowledge that is not deployed makes no diﬀerence by its absence.

Campus

Situated in a lush green village campus in Thelliyoor, Kerala, India, airis4D was established under the auspicious

of SEED Foundation (Susthiratha, Environment, Education Development Foundation) a not-for-proﬁt company

for promoting Education, Research. Engineering, Biology, Development, etc.

The whole campus is powered by Solar power and has a rain harvesting facility to provide suﬃcient water supply

for up to three months of drought. The computing facility in the campus is accessible from anywhere through a

dedicated optical ﬁbre internet connectivity 24×7.

There is a freshwater stream that originates from the nearby hills and ﬂows through the middle of the campus.

The campus is a noted habitat for the biodiversity of tropical Fauna and Flora. airis4D carry out periodic and

systematic water quality and species diversity surveys in the region to ensure its richness. It is our pride that

the site has consistently been environment-friendly and rich in biodiversity. airis4D is also growing fruit plants

that can feed birds and provide water bodies to survive the drought.