The survey taken up by team created out of IIT Guwahati collaboration with Duke-NUS Medical School has used data science models to analyse and predict the total number of infected people for different states in India in the next 30 days.

They have interpreted the results jointly from all models rather than individually. The team comprised Dr. Palash Ghosh, Assistant Professor, Department of Mathematics, IIT Guwahati, and his Ph.D. scholar, Mr. Rik Ghosh and Dr. Bibhas Chakraborty, Associate Professor, Duke-NUS Medical School, Singapore.

The team formed out of IIT Guwahati collaboration labeled a state as severe if a non-decreasing trend in DIR values is observed over the last two weeks along with a near exponential growth in active infected cases; as moderate if an almost decreasing trend in DIR values is observed over the last two weeks along with neither increasing nor decreasing growth in active infected cases; and as controlled if a decreasing trend in the last two weeks’ DIR values is observed along with a decreasing growth in active infected cases.

The team formed out of IIT Guwahati collaboration have found in their analysis that the logistic model under-predicts the next 30-day prediction, whereas the exponential model over-predicts the same, reflecting the worst-case scenario.

They argued that, despite the nation-wide lockdown, people are still out of home for essential businesses, which can contribute to the spreading of the virus.

The maximum value of DIR in the last two weeks can capture how severely the COVID-19 is spreading in recent times.

Note that the DIR value of 0.10 cannot be interpreted in a similar way for two different States, say, with 500 and 5000 active cases, respectively.

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For the first State, we see 500 x 0.10 = 50 new cases and for the second State, we observe 5000 x 0.10 = 500 new cases.

In an attempt to capture these various subtleties in a realistic prediction, they propose a combination of the logistic and the exponential predictions using the maximum value of DIR over the last two weeks as a weighting factor.

Given the situation in entire India, the team formed out of IIT Guwahati collaboration recommends this composite prediction to be used for assessment purposes for each State.

States that are in severe category need to do much more in terms of the preventive measures immediately to combat the COVID-19 pandemic, says the study taken up by the team formed out of IIT Guwahati collaboration with Singapore based organisation.

Speaking more about the data-driven state-wise assessment of COVID-19 situation in India taken up by IIT Guwahati collaboration Dr. Palash Ghosh, Assistant Professor, Department of Mathematics, IIT Guwahati said India is a vast country with a geographic area of 3,287,240 square kilometres and a total population of about 1.3 billion.

‘Most of the Indian States are quite large in geographic area and population. While analyzing the novel coronavirus infection data, considering our entire country to be on the same page may not reveal the right picture.’

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This is so because the first infection, new infection-rate, progression over time, and preventive measures taken by various State governments and the common public for each State are different.

We need to address each State separately. It will enable the government(s) to utilize the limited available resources optimally, he said.

IIT Guwahati director Professor T.G.Sitharam said a joint interpretation from several data science models is essential to have a better perspective about the current situation and the future prediction to control this pandemic.

The idea of State-wise analysis is a vital step for better management of the COVID-19 condition in India.

Designed to monitor the freshness of seafood in real-time by responding to pH changes, the film offers a practical solution for improving food safety and reducing waste.

This film detects the release of volatile amines, compounds typically associated with spoilage, and indicates food quality through visible color changes, say sources from NIT Rourkela.

These natural components make the film biodegradable, safe, and responsive, aligning with sustainability goals and offering a non-invasive way to assess seafood freshness.

Findings

The findings of this research have been published in the journal Food Packaging and Shelf Life in a paper co-authored by Prof. Preetam Sarkar (as the lead corresponding author), along with his research scholars, Mr. Rahul Thakur, Miss Harshi Singhi, Mr. Vedsagar Rajesh Suryavanshi, and Dr. Ravichandran Santhosh.

Other co-authors in this work include Dr. Khalid Gul from NIT Rourkela, Dr. Swarup Roy from Lovely Professional University, Dr. Srinivas Janaswamy from South Dakota State University, Brookings, USA and Dr. Kirtiraj K. Gaikwad from IIT Roorkee.

Fishing

India is the world’s second-largest fish-producing nation, contributing approximately 8% of global fish production, say NIT Rourkela researchers.

It also holds the distinction of being the top five producer of shrimp globally, with frozen shrimp being the top export commodity.

Given the scale and importance of seafood production, innovations that ensure freshness and reduce spoilage are of immense value, say NIT Rourkela researchers.

In this context, intelligent packaging systems, which preserve food while monitoring its quality, are rapidly gaining global interest.

Unlike conventional packaging that serves merely as a protective barrier, the intelligent packaging film developed by NIT Rourkela team offers visual cues about the product’s condition, making it a promising solution for enhancing food safety and reducing waste.

The beetroot peel extract was prepared separately, and then combined with the starch, gum tragacanth, and a small amount of glycerol to cast the films.

These were dried and tested for their pH-sensitivity and effectiveness in monitoring seafood freshness, said Prof Preetam of NIT Rourkela.

Pigments

Beetroot peels contain betalains, a group of pigments known for their bright colours and pH sensitivity, say NIT Rourkela researchers.

These pigments also offer antioxidant and antimicrobial benefits, making them suitable for food-related applications.

Incorporating these natural compounds into the starch-based film creates a biodegradable, safe, and responsive packaging material.

When the seafood begins to spoil and pH levels rise, the film changes colour, providing a clear visual indicator of freshness.

Starch

The choice of Kodo millet starch and gum tragacanth contributes to the film’s biodegradable and eco-friendly profile.

Kodo millet is an underutilised grain with excellent film-forming properties, while gum tragacanth enhances the mechanical strength and flexibility of the material.

The researchers believe that using such agricultural by-products not only supports sustainability but also adds value to food processing waste, such as beetroot peels.

At the laboratory scale, the cost of producing the film was estimated approximately Rs. 900 per kilogram.

When scaled up for industrial production, the cost is projected to range between Rs. 400 and Rs. 600 per kilogram, making it a potentially viable option for commercial use.

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