Day 4, Oct 8, 2020

GS Paper 3:

Topic:- Advancements in Science & Technology

1.What is Crispr-Cas9 tool? Discuss its applications in medicine?

CRISPR – Cas9 is an assembly of a DNA cutting (CAS9) protein and a RNA strand – Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR) which is used as gene scissors.

• The Cas9 system identify specific gene locations in a DNA and attaches itself to it. The CRISPR unwind and snip the DNA strand.

• The complex was discovered in bacteria as an immune mechanism against virus invading them.

• Emmanuelle Charpentier of France and Jennifer Doudna of US were awarded Chemistry Nobel for discovery and developing it as a genetic engineering tool.

• Potential uses for this genetic engineering tool are many like medical gene therapy, basic science studies, agricultural gene manipulations toward quantitative and qualitative improvement of crops, conservation of endangered species, engineering biofuel potential organisms, etc.

• At the same time ethical usage of such technology also needs to be ensured in order prevent adventurist or mala-fide misuse.

Applications in medicine:

• Prevention of congenital disorders – they are transmitted from parents to offspring by gene – the defective genes may be modified to address the problem.

• Cancer treatment – CRISPR – Cas9 can correct the genetic sequence errors resulting from mutations and resultant cancer may be treated effectively.

• Disease modelling – CRISPR – Cas9 aid in developing genetically modified animals/cells which are used for recreating human diseases and better drug development tests.

• HIV Treatment – Scientists contemplate cure for HIV using CRISPR – Cas9 molecules and altering the immune response to the virus.

• Biomolecules production – insulin like molecules synthesis are to become easier due to role of CRISPR – Cas9 tool.


Thus, CRISPR – Cas9 discovery had opened a wide gamut of opportunities in medical genetic engineering and gene therapy fields.

GS Paper 3:-

Topic:- Disaster Management

2. “ A higher lead time can significantly reduce the vulnerability during the time of floods”. Discuss the feasible technological interventions that can aid in planning and handling of disasters due to floods?


In India during flood events,the end users (district administration, municipalities and disaster management authorities) receive forecasts about floods and have to act quickly. If the flow of information during disaster management and especially during the time of floods can be sped up, this can significantly add to the response of the administration to plan swift re-location and safety arrangements.

The length of time from issuance of the forecast and occurrence of a flood event termed as “lead time” is the most crucial aspect of any flood forecast to enable risk-based decision-making and undertake cost-effective rescue missions by end user agencies.

The following technological interventions can greatly come to the aid of the authorites in reducing the vulnerabilites during floods.

Shift towards Ensemble forecasting

Ensemble forecast”) provides a lead time of 7-10 days ahead, with probabilities assigned to different scenarios of water levels and regions of inundation. The United States, the European Union and Japan have already shifted towards “Ensemble flood forecasting” alongwith “Inundation modelling”. India has only recently shifted towards “Deterministic forecast” (i.e. “Rising” or “Falling” type forecast per model run). It would be in India’s interest to shift towards ensemble forecasting so as to reduce the “lead time” .

Doppler weather radars vs point scale rainfall data

Compared to point scale rainfall data from rain gauges, Doppler weather radars can measure the likely rainfall directly (known as Quantitative Precipitation Estimation or QPE) from the cloud reflectivity over a large area; thus the lead time can be extended by up to three days.The United States which is estimated to have a land area thrice that of India, has about 160 next generation S-band Doppler weather radars (NEXRAD) with a range of 250-300 km. India will need at least an 80-100 S-band dense radar network to cover its entire territory for advance forecasting and this can reduce the lead time significantly

Artificial Intelligence

Google AI has adopted the hydrological data and forecast models derived for diverse river basins across the world for training AI to issue flood alerts in India. This bypasses the data deficiencies and shortcomings of forecasts based on statistical methods. India can leverage the use of its “Mihir” and “Pratyush” super computers and put it to use to forecast floods in advance using AI algorithms.


It would be in India’s interest to adpot the adove technology interventions so as to reduce the loss of live and property during floods. A robust disaster management mechanism thus ensured would go a long way in strengthening the National Disaster Management Framework in India.

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