NIMBLE FOUNDATION BLOG – STAY SAFE!

Stress has been called an invisible disease, which not only effects the individual but also the organisation. It should never be ignored.  Learn how to spot your stress warning signals. Do not be afraid at all to talk to the concerned person, the physical as well as emotional well being can be very poorly affected. Routinely working very late also an indication that you remain under stress. If you do not have c5rodial relations with people around, this is also an indication of stress.

Poor sleep or lack of sleep, when you cannot sleep also indicates that you are under stress. It is necessary to observe and note down all the above signals of stress.

What are the causes of stress?

Stress can be due to any one or more reasons:

1. If you regularly maintain a heavy schedule of work, that will cause stress. You can never do more than one persons job.
2. If you are under pressure regarding the job, regarding the boss or any other reason such pressure will also lead to some amount of stress.
3. If you have financial difficulties and you are not able to reduce your expenses according ot your income that could be a cause of stress.

Following are the personality related problems that add to the stress.

1. Indecision – indecision is the bane of life. There are many people who face this malady which adds to the stress.
2. Laziness or procrastination may appear to be attractive but at a later time, you will find that they are the biggest creators of the invisible disease stress.
3. Your futile efforts if they are not aligned with there goals, you tend ot realise there futility and later it becomes a cause of stress.
4. It is said that you must act and never react. You reactions to a particular situation or a person, betrays the lack of emotions, which constitutes the root cause of stress.
5. Bad temper or anger and all such negative emotions or thoughts make you very stressful.
6. Further doubt, suspicion or jumping to the conclusion or being in doubt adds to the stressful life.
7. Last but not the least, not getting along with the people around you, whether at home, in office or in society leads to stress. With every intertatcion with that person  you feel stressful.

How to deal with this disease – Stress?

You must take the following actions as a matter of habit if you want to lead a stress free life:

1. Practice Assertiveness: Assertiveness means that you do not say yes, when you want to say no. You should  Discuss the problem, with your colleague, seniors, juniors and develop a consensus. This is very much applicable also for your people at home also.
2. If you are working for a large organisation in a leader’s rol4e, you need to develop a support system .
3. As a leader, increase your investment in your  own training in enhancing your skills and even more importantly enhance the skills of your staff.
4. Always write down our to do list, fix priorities and look at your list, many times a day.
5. Jot down your stress triggers and also note them down in your jounal, which must be written them daily.
6. Try to take a break from work or form study after every hour or so.
7. Do not ignore problem. Acknowledge them as they arise and try to resolve them.
8. Be productive and do not delay desired action. At the same time do not get into any hasty decisions or actions.
9. Do not dwell on any of your past mistake and be anxious on the bleak future, you must always perform your duty and focus on the present.
10. Never lave anything incomplete. Incomplete projects always lead to stress.
11. You should be active constructively.
12. Always spend sometime with nature.
13. Develop yogic breathing which will really help develop a very healthy life.

blog is written by Vikram Kakri.

If one has to single out one particular aspect of personality which is most important for the success and the happiness is the concept of “SELF DISCIPLINE”.

What is self – discipline?

It Is your personal ability to control your impulses, your emotions, reactions and the behaviours. The impulses are the things what you like to do and the triggers and temptations of doing that. It is irrespective of what you are supposed to do at that particular moment. Self-discipline teaches you to actually control these impulses. Often you are led away by these particular emotions and also we sometimes get into a fit of anger as a reaction to a person or a situation.  Self-discipline enables you to overcome these negative and harmful tendencies. Thus the self-discipline actually encourages you to forgo the short term gratification in favour of the long term satisfaction and gains.

 Self-discipline also very much inspires you to stay very much focused on all your goals. We know that your goals when pursued properly brings results in the form of success. It also helps you to stay in control of yourself and your reactions in any situations whether they are good or bad.

Why are we not self-disciplined?

One of the major causes for the lack of the self-discipline is our inability to do something again and again. Doing something again and again sometimes becomes monotonous and therefore we `sometimes drift away to all our favourable things.

Another major cause of lack or self-discipline is lack of strong desire & purpose. So without any compelling purpose, it actually becomes very difficult to stay on track.

Lack of focus is another very important reason which leads to very poor self-discipline. When we cannot concentrate on something even when we know that it Is very important, we are in dire need of correcting our perspective and improving our focus.

The nest reason for the lack of self-discipline is too many interruptions. Due to whatever reasons when we have a lot of interruptions in whatever we are doing, we cannot actually maintain our focus. We also sometimes loose our interest in the task at hand, which sometimes leads to self indiscipline.

Last but not the least, the habit of being very lazy actually adds to the lack of self-discipline. Often there are times that laziness leads to procrastination, which is even worse.

The following steps must be consistently taken to make yourself self-disciplined:

1. Develop a very strong desire of your work and also become proficient. The strong reason to pursue your duty will help you to find such reasons.
2. Whatever you begin, practice to your best ability and continue practicising until you excel in the job you are doing. This should be applicable to anything and everything that you take up.
3. Connect yourself with your best efforts and not with the results of your efforts. Sometimes the results come faster, sometimes they are delayed. Vow to yourself that you will never leave anything incomplete. Completion of the project that you take up must be your priority. You must hold yourself accountable for anything that is going wrong on this project.
4. Rely on the principle of inside out and not outside in, meaning that you rely on yourself, more than anything else. If you do not know something, it is your duty to learn all the necessary things about the work at hand. If there is a necessary learning required from a consultant or a teacher, you must go ahead and learn from there.
5. You should never play the victim card  or hold circumstances or people for your inabilities to do justice for your particular work. Develop and derive your mental strength. Also develop emotional intelligence to remain cool in all circumstances.
6. You need to avoid people with negative attitudes or those who try to harm your interest. Keep them at bay at any cost.
7. Believe in yourself and practice undergoing momentary hardships. It is often necessary to stretch yourself to meet deadlines. At the same time be compassionate with yourself.
8. Lastly you must honestly review your each day and assess whether it was good, bad, ugly, mundane, or just mediocre.  The daily assessment will surely help you to keep on improving. 

Reinforcement learning is a machine learning training method based on rewarding desired behaviors and/or punishing undesired ones. In general, a reinforcement learning agent is able to perceive and interpret its environment, take actions and learn through trial and error.

How does reinforcement learning work?

In reinforcement learning, developers devise a method of rewarding desired behaviors and punishing negative behaviors. This method assigns positive values to the desired actions to encourage the agent and negative values to undesired behaviors. This programs the agent to seek long-term and maximum overall reward to achieve an optimal solution.

These long-term goals help prevent the agent from stalling on lesser goals. With time, the agent learns to avoid the negative and seek the positive. This learning method has been adopted in artificial intelligence (AI) as a way of directing unsupervised machine learning through rewards and penalties.

Applications and examples of reinforcement learning

While reinforcement learning has been a topic of much interest in the field of AI, its widespread, real-world adoption and application remain limited. Noting this, however, research papers abound on theoretical applications, and there have been some successful use cases.

Current use cases include, but are not limited to, the following:

• gaming
• resource management
• personalized recommendations
• robotics

Gaming is likely the most common usage field for reinforcement learning. It is capable of achieving superhuman performance in numerous games. A common example involves the game Pac-Man.

A learning algorithm playing Pac-Man might have the ability to move in one of four possible directions, barring obstruction. From pixel data, an agent might be given a numeric reward for the result of a unit of travel: 0 for empty space, 1 for pellets, 2 for fruit, 3 for power pellets, 4 for ghost post-power pellets, 5 for collecting all pellets and completing a level, and a 5-point deduction for collision with a ghost. The agent starts from randomized play and moves to more sophisticated play, learning the goal of getting all pellets to complete the level. Given time, an agent might even learn tactics like conserving power pellets until needed for self-defense.

Reinforcement learning can operate in a situation as long as a clear reward can be applied. In enterprise resource management (ERM), reinforcement learning algorithms can allocate limited resources to different tasks as long as there is an overall goal it is trying to achieve. A goal in this circumstance would be to save time or conserve resources.

In robotics, reinforcement learning has found its way into limited tests. This type of machine learning can provide robots with the ability to learn tasks a human teacher cannot demonstrate, to adapt a learned skill to a new task or to achieve optimization despite a lack of analytic formulation available.

Reinforcement learning is also used in operations research, information theory, game theory, control theory, simulation-based optimization, multiagent systems, swarm intelligence, statistics and genetic algorithms.

Challenges of applying reinforcement learning

Reinforcement learning, while high in potential, can be difficult to deploy and remains limited in its application. One of the barriers for deployment of this type of machine learning is its reliance on exploration of the environment.

For example, if you were to deploy a robot that was reliant on reinforcement learning to navigate a complex physical environment, it will seek new states and take different actions as it moves. It is difficult to consistently take the best actions in a real-world environment, however, because of how frequently the environment changes.

The time required to ensure the learning is done properly through this method can limit its usefulness and be intensive on computing resources. As the training environment grows more complex, so too do demands on time and compute resources.

Supervised learning can deliver faster, more efficient results than reinforcement learning to companies if the proper amount of data is available, as it can be employed with fewer resources.

Common reinforcement learning algorithms

Rather than referring to a specific algorithm, the field of reinforcement learning is made up of several algorithms that take somewhat different approaches. The differences are mainly due to their strategies for exploring their environments.

• State-action-reward-state-action (SARSA). This reinforcement learning algorithm starts by giving the agent what’s known as a policy. The policy is essentially a probability that tells it the odds of certain actions resulting in rewards, or beneficial states.
• Q-learning. This approach to reinforcement learning takes the opposite approach. The agent receives no policy, meaning its exploration of its environment is more self-directed.
• Deep Q-Networks. These algorithms utilize neural networks in addition to reinforcement learning techniques. They utilize the self-directed environment exploration of reinforcement learning. Future actions are based on a random sample of past beneficial actions learned by the neural network.

How is reinforcement learning different from supervised and unsupervised learning?

Reinforcement learning is considered its own branch of machine learning, though it does have some similarities to other types of machine learning, which break down into the following four domains:

1. Supervised learning. In supervised learning, algorithms train on a body of labeled data. Supervised learning algorithms can only learn attributes that are specified in the data set. Common applications of supervised learning are image recognition models. These models receive a set of labeled images and learn to distinguish common attributes of predefined forms.
2. Unsupervised learning. In unsupervised learning, developers turn algorithms loose on fully unlabeled data. The algorithm learns by cataloging its own observations about data features without being told what to look for.
3. Semisupervised learning. This method takes a middle-ground approach. Developers enter a relatively small set of labeled training data, as well as a larger corpus of unlabeled data. The algorithm is then instructed to extrapolate what it learns from the labeled data to the unlabeled data and draw conclusions from the set as a whole.
4. Reinforcement learning. This takes a different approach altogether. It situates an agent in an environment with clear parameters defining beneficial activity and nonbeneficial activity and an overarching endgame to reach. It is similar in some ways to supervised learning in that developers must give algorithms clearly specified goals and define rewards and punishments. This means the level of explicit programming required is greater than in unsupervised learning. But, once these parameters are set, the algorithm operates on its own, making it much more self-directed than supervised learning algorithms. For this reason, people sometimes refer to reinforcement learning as a branch of semisupervised learning, but in truth, it is most often acknowledged as its own type of machine learning.

Blog is curated by Vikram Kakri.

Blog Link: https://www.techtarget.com/searchenterpriseai/definition/reinforcement-learning#:~:text=Reinforcement%20learning%20is%20a%20machine,learn%20through%20trial%20and%20error.

Definition: Planning is the fundamental management function, which involves deciding beforehand, what is to be done, when is it to be done, how it is to be done and who is going to do it. It is an intellectual process which lays down an organisation’s objectives and develops various courses of action, by which the organisation can achieve those objectives. It chalks out exactly, how to attain a specific goal.

Planning is nothing but thinking before the action takes place. It helps us to take a peep into the future and decide in advance the way to deal with the situations, which we are going to encounter in future. It involves logical thinking and rational decision making.

Characteristics of Planning

1. Managerial function: Planning is a first and foremost managerial function provides the base for other functions of the management, i.e. organising, staffing, directing and controlling, as they are performed within the periphery of the plans made.
2. Goal oriented: It focuses on defining the goals of the organisation, identifying alternative courses of action and deciding the appropriate action plan, which is to be undertaken for reaching the goals.
3. Pervasive: It is pervasive in the sense that it is present in all the segments and is required at all the levels of the organisation. Although the scope of planning varies at different levels and departments.
4. Continuous Process: Plans are made for a specific term, say for a month, quarter, year and so on. Once that period is over, new plans are drawn, considering the organisation’s present and future requirements and conditions. Therefore, it is an ongoing process, as the plans are framed, executed and followed by another plan.
5. Intellectual Process: It is a mental exercise at it involves the application of mind, to think, forecast, imagine intelligently and innovate etc.
6. Futuristic: In the process of planning we take a sneak peek of the future. It encompasses looking into the future, to analyse and predict it so that the organisation can face future challenges effectively.
7. Decision making: Decisions are made regarding the choice of alternative courses of action that can be undertaken to reach the goal. The alternative chosen should be best among all, with the least number of the negative and highest number of positive outcomes.

Planning is concerned with setting objectives, targets, and formulating plan to accomplish them. The activity helps managers analyse the present condition to identify the ways of attaining the desired position in future. It is both, the need of the organisation and the responsibility of managers.

Importance of Planning

• It helps managers to improve future performance, by establishing objectives and selecting a course of action, for the benefit of the organisation.
• It minimises risk and uncertainty, by looking ahead into the future.
• It facilitates the coordination of activities. Thus, reduces overlapping among activities and eliminates unproductive work.
• It states in advance, what should be done in future, so it provides direction for action.
• It uncovers and identifies future opportunities and threats.
• It sets out standards for controlling. It compares actual performance with the standard performance and efforts are made to correct the same.

Planning is present in all types of organisations, households, sectors, economies, etc. We need to plan because the future is highly uncertain and no one can predict the future with 100% accuracy, as the conditions can change anytime. Hence, planning is the basic requirement of any organization for the survival, growth and success.

Steps involved in Planning

By planning process, an organisation not only gets the insights of the future, but it also helps the organisation to shape its future. Effective planning involves simplicity of the plan, i.e. the plan should be clearly stated and easy to understand because if the plan is too much complicated it will create chaos among the members of the organisation. Further, the plan should fulfil all the requirements of the organisation.

blog is curated by Vikram.

As organizational learning professionals, we have received many questions over the years about what makes for a good organizational learning plan. We saw a lack of good resources, including publicly available organizational learning plans for others to learn from and adapt. This blog series is intended to fill that gap. In this series, we share our thoughts on what an organizational learning plan is, how to create one, and most importantly how to implement it so that what is included in the plan actually gets done.

An organizational learning plan outlines how an organization will create, acquire, analyze, share, and use learning. First some orientation:

• In this blog series, we are focusing on organizational learning plans within a relatively small organization (<200 staff). We think the information here will be relevant to larger organizations, but creating an organizational learning plan across an agency with hundreds or even thousands of employees is a different kind of effort. We are also steeped in the international development field, specifically working with USAID; therefore, our language and reference points match that experience.
• By “learning” we are referring to both operational learning and strategic learning. Operational learning focuses on how the work is being carried out and informs decisions about how we do our work in the day-to-day, while strategic learning uses data and insights to inform decision-making about longer-term strategies (for more on strategic learning, see this piece from the Center for Evaluation Innovation).

At its core, an organizational learning plan should answer some basic questions:

• What do we need to know in order to be effective and enlightened?
• How will we create, acquire, analyze, share, and use our knowledge?
• Who will do what to ensure we create, acquire, analyze, share, and use our knowledge?
• How will we resource and reinforce these practices within our organization?

We are using the words effective and enlightened on purpose.

• “Effective” typically means your organization learns things that help it fix immediate challenges. It asks, “are we doing things RIGHT?” This question is most closely associated with operational learning. It’s not always asking whether what you’re doing is even the right thing to do, it’s asking how can we do the thing we are doing better. This is also referred to as single loop learning. Single loop learning is like a thermostat that learns when it is too hot or too cold and turns the heat on or off. It receives information and can take corrective action to make adjustments.
• “Enlightened” means that your organization can determine whether it is doing the right things and therefore take action accordingly. It asks, “Are we doing the RIGHT THINGS?” This is also referred to as double loop learning and is more closely associated with strategic learning. Single loop is learning that keeps you on track to pre-set goals (e.g. keep the temperature at 75). Double loop is learning that allows space for reflecting on whether your goals are the right one (e.g. maybe I can stay warm by putting a sweater on).

For a more nuanced discussion of types of learning, see Dave Algoso’s excellent discussion on taxonomy of organizational learning.

Why does organizational learning matter?

Monalisa Salib already wrote a great piece on this, and we want to refer you there! She makes four main arguments for why learning matters:

• Continuous Improvement: “‘Learning matters because it empowers us all to make better development decisions and achieve greater impact.’” This is, hands down, the most important reason why learning matters.
• Efficiency: “If we come to realize, only years later, that we reinvented a wheel that already existed and failed to function, how much time, energy, and money could we have been saving and putting towards something with greater promise?”
• Engagement: “…wouldn’t we be a happier and more engaged workforce if we spent more time grappling with the tough questions and strengthening our discipline?”
• Humility: “If we recognize that there is so much we have yet to understand about the contexts in which we work, how change happens, and how best to go about achieving results, we see a clear need for institutionalizing curiosity in our organizations.”

Why do you need an organizational learning plan?

Bottom line: An organizational learning plan brings intentionality to learning. In the USAID world of collaborating, learning, and adapting (CLA), we talk about being systematic, intentional, and resourced. A learning plan enables organizations to be:

1. Intentional by outlining what you are going to do
2. Systematic by outlining how you are going to do it
3. Resourced by outlining what you need to make it happen

What is the difference between an organizational learning plan, a MEL plan, a CLA plan, another type of plan? Are these all the same thing?

There is a lot of confusion about the difference between an organizational learning plan, a Monitoring, Evaluation, and Learning (MEL) plan, a Collaboration, Learning, and Adapting (CLA) plan, a learning agenda, a knowledge management plan, and a continual improvement plan.

All of these plans might be the same thing depending on your industry. The point is that an organizational learning plan should tell you what you need to know, how you will learn, and what you do with that learning along the way in order to be the most enlightened and effective version of your team, program, or organization. MEL plans, CLA plans, learning agendas, and continual improvement plans can all achieve that purpose — sometimes it just comes down to what language you want to use (because it’s the way you talk in your organization — the language resonates). An aside: there are a plethora of great resources on learning agendas available. Start with this Learning Agenda resource page.

In the USAID world, certain plans are required by policy. If that’s the case (such as a MEL plan at the activity level or the Performance Management Plan (PMP) at the USAID strategy level), then ask yourself:

Is the plan we are coming up with going to describe what we need to know and learn along the way in order to be the most enlightened and effective version of our team or organization?

If not, then the contents of your plan need to change, regardless of what you’re calling it. You’ll need to think deeper about the purpose of the plan. A plan is not a list of indicators — it lays out your approaches for a constant state of becoming a better organization.

Note: whatever you do, don’t have multiple plans with similar purposes (a learning agenda and a MEL plan on the same program or team) that are managed by different people who do not coordinate. This is a recipe for disaster, as it will confuse your colleagues, overcomplicate the process, and act as a barrier instead of an enabler to collective learning on your team.

When are you “done” with the organizational learning plan?

You are never really “done” with an organizational learning plan, because you are never really done with learning. Think: “good enough to get started” and then implement and learn as you go! Our advice in this area is to be wary of falling in love with your plan or the act of planning. This can sometimes present as trying to perfect the plan or failing to test pieces of the plan before its ultimate finalization. That means you love your plan more than implementing the plan. The purpose of the plan is to take action so it’s a good idea to go for a minimum viable product. Even in large and complex organizational contexts, there is always a way to test and experiment.

Once implemented, revisit the plan and update it based on how well your learning practices are working and any changes to strategy that affect your learning priorities. Be careful to avoid what Monalisa calls “meta-L2 syndrome” — the state of learning about learning to the point of alienating your very pragmatic colleagues who may (rightfully) accuse you of navel-gazing.

What are some examples of learning activities?

Outside of After Action Reviews (AARs), what are other ways that individuals can learn together in their organizations? Take a look at the illustrative list below to get you thinking creatively for your organizational learning plan. These activities should be in service of your learning questions and match the level of effort your team is willing and able to put into learning.

1. Before Action Reviews — the forgotten cousin of the After Action Review! This is a great exercise before an activity, especially if a lot of time has passed since the AAR to solidify the learning and ensure it gets incorporated into the new activity.
2. Learning Book Clubs — reading something (a short article, blog, or book) and discussing it as a team. This allows your team to make meaning of what you read together and discuss important implications for your work.
3. Users Experience Fish Bowls — having team members reflect on a topic, for example, a learning question, and having the rest of the team observe from the outside. You can switch team members in and out. The purpose of this exercise is to learn through listening to others’ thought processes.
4. Outcome Harvesting Learning Journals — Encouraging staff to utilize outcome learning journals to document their perspectives on the outcomes they are observing.
5. Reflection Fridays — Dedicating time, perhaps the last Friday of every month, to reflect on what you are learning in service of your theory of change and broader strategy as a team.
6. Quarterly Review — a great methodology to discuss how things are going, reflect as a team on emerging lessons and challenges, and to strategize on how you can strengthen your effectiveness in the months to come. To increase engagement, try using fun and games.
7. What? So What? Now What? — A methodology that encourages participants to reflect together and share new insights. It is great for guiding decision making.
8. “How Might We…” Statements — A user-centered design technique that can be applied in teams to encourage generative learning. It helps us to pause and explore different solutions instead of just jumping to the most familiar one when presented with a problem.
9. Strategic Decision Making Process Flow — Ian David Moss created this flow to help break down decisions to more holistically account for what we know. In this post, he includes the “wrap around model” to draw out decision making into a multi-step process.
10. “I Like, I Wish, I Wonder” — A super simple methodology to guide learning group sessions focused on generating actionable insights.
11. Strategy Triage Tool — A simple five-square matrix useful for reflecting on strategic learning.
12. Six Hats Reflection Tool — A facilitated exercise that encourages teams to acknowledge their layered experiences together. This is a great tool for productively engaging and releasing emotions.

Blog is curated by Vikram Kakri.

DEFINITION OF INDIVIDUAL DIFFERENCES

According to the dictionary of education

1. Individual differences stand for the variation or deviations among individuals in regard to a single characteristic or number of characteristics.
2. It is stand for those differences which in their totality distinguish one individual from another. So, we can say that individual differences is the differences among humans that distinguish or separate them from one another and makes one as a single unique individual.

TYPES OF INDIVIDUAL DIFFERENCES

Following are the types of individual differences

Differences in Interest

Interest may refer as a motivating force that impels us to attend to a person, a thing, or an activity. So in educational field differences in interest means you observe some students like a particular subject, teacher, hobby or profession than other.

Difference in Attitude

Difference in attitude is psyche related to some thing. Few learners have positive attitude towards a specific topic, subject, and profession than other. The role of education in society is to develop positive attitude.https://cade346bc668ebf4d021f1e92419dbfd.safeframe.googlesyndication.com/safeframe/1-0-38/html/container.html

Also Read:   Educational Psychology Articles    Curriculum Development      Students Assessment & Evaluation

Difference in Values

Values are the things that are given importance by an individual. Some learners value materialist life style other moral or religious life style etc. So education must mould the mind of young generation to have a balance values between materialism and spiritualism.

Study Habits

It is clearly observable that some students markedly differ from other students in study habits. Some students are studious and study all the subjects with interest but other may not. Some study in isolation and some in group.

Difference in Psychomotor Skills

Psychomotor Skill is related to some skill acquisition. Some students differ in this area also. Some students like football, other cricket, etc. Some students easily learn operating a machine and some may not. A wise teacher should diagnose students’ psychomotor skills abilities and encourage them in that direction.

Difference in Self Concept

Difference in self concept is the totality of attitudes, judgment, and values of an individual relating to his behavior, abilities, and qualities. So some students have positive self concept than boost their confidence level and perform better against those who have negative self image.https://cade346bc668ebf4d021f1e92419dbfd.safeframe.googlesyndication.com/safeframe/1-0-38/html/container.html

CAUSES OF INDIVIDUAL DIFFERENCES

The followings are the main causes of individual differences:

1. Hereditary (Nature)

Individuals have various endowments, abilities, and capacities provided by hereditary. Which decide the path of progress and development of an individual.

1. Hereditary also put limits upon individuals’ growth and development in various dimensions.
2. Hereditary also contributes to sex, intelligence, and other specific abilities.

2. Environment (Nurture)

Environment also plays key role in individual differences. No person from birth to death gets the same environment. Individual differences occur on the basis of simulation received by individual from his or her internal and external environment. This may include family set up, peer group, economic statues, education etc. 

It is debatable that whether nature or nurture play vital or stronger role in development of an individual in specific direction. Both are strong contenders in order to distinguish one individual from other.

Blog is curated by Vikram Kakri.