Was the Environment Healing During the Pandemic?

While the outbreak of the Covid 19 pandemic prompted lockdowns in many countries all over the world, the resultant decrease in emissions may have improved the health of our planet. Incidents where endangered animals have been spotted in certain areas were all around social media.

Photo by Anna Shvets on Pexels.com

The worldwide disruption caused by this has resulted in great impacts on the environment and the climate. Also, the considerable decline in travel has caused many regions to experience a large drop in air pollution. Carbon emission rates have reduced across countries significantly. There have been many instances where considerable changes in environmental conditions were observed. In China, lockdowns and similar measures have resulted in a 25 percent reduction in carbon emissions and 50 per cent reduction in nitrogen oxides emissions. One scientist estimated that this may have saved at least 77,000 lives over the course of two months. When compared with indexes of last year, pollution levels in New York have decreased almost by 50% this year. Satellite images have shown that Nitrogen dioxide emissions have started to decrease in Northern Italy, Spain and United Kingdom.

As most people had to stay at home due to lockdown and travel restrictions, many animals have been spotted in several cities. Sea turtles were spotted laying eggs on beaches they once avoided. This was found in coasts of the Bay of Bengal due to the lowered levels of pollution and human intervention. In the United States, dangerous vehicle collisions with animals such as deer, elk, moose, bears, mountain lions were very common. These incidents have reduced greatly and the rates fell by 58% during March and April. Endangered animals were visible in urban cities. A group of Nilgai deer were spotted on the roads of Noida near New Delhi. Dolphins which were seen in the Ganges many years ago, were also spotted in the river during the lockdowns. Several migratory birds were spotted across cities.

Gabon, an African country, had decided to ban the human consumption of certain animals like, bats and pangolins. This was done to reduce the spread of zoonotic diseases because the novel coronavirus is thought to have transmitted to humans through these animals.

According to a study published in May 2020, it was found that the rate of daily global carbon emissions during the lockdown in early April fell by 17%. This could possibly lead to an annual carbon emissions decline of up to 7%, which would be the biggest drop in emissions since World War II according to the study. Researchers suggest that these decreases are mainly due to the reduction of transportation usage and industrial activities. It is true that rebounding and returning to our previous routine and lives could diminish these reductions due to the more limited industrial activities. Due to the reduction in flights, air pollution levels have also dropped significantly.

Temporary changes have affected the environmental conditions. However, whether this pandemic will have a lasting impact on the environment is yet to be known. None of us would have wanted to lower emissions in this way, but it has shown us what we can do together in times of need. Covid-19 has shown us the importance of lives, health services, jobs and mental health. It has also shown us the difference that people and communities can make when they work together – this has given us hope that we can show the same zeal while dealing with climate change and saving our planet.

Unemployment in India

The unemployment rate in India jumped to 29% since the country went into lockdown from March 2020, says the report of CMIE – Centre For Monitoring Indian Economy. The lockdown to contain the coronavirus outbreak has forced many industries to shut down thus increasing unemployment across the country.

The unemployment rate in India rose to 7.2 percent in February 2019, the highest since September 2016, and also up from 5.9 percent in February 2018, according to the latest data compiled by the Centre for Monitoring Indian Economy (CMIE).

What is Unemployment?

Unemployment occurs when a person who is actively searching for employment is unable to find work. Unemployment is often used as a measure of the health of the economy. The most frequent measure of unemployment is the unemployment rate, which is the number of unemployed people divided by the number of people in the labor force.

National Sample Survey Organization (NSSO) defines employment and unemployment on the following activity statuses of an individual:

  • Working (engaged in an economic activity) i.e. ‘Employed’.
  • Seeking or available for work i.e. ‘Unemployed’.
  • Neither seeking nor available for work.

The first two constitutes labour force and unemployment rate is the percent of the labour force that is without work.

Unemployment rate = (Unemployed Workers / Total labour force) × 100

Types of Unemployment in India

  • Disguised Unemployment:
    • It is a phenomenon wherein more people are employed than actually needed.
    • It is primarily traced in the agricultural and the unorganised sectors of India.
  • Seasonal Unemployment:
    • It is an unemployment that occurs during certain seasons of the year.
    • Agricultural labourers in India rarely have work throughout the year.
  • Structural Unemployment:
    • It is a category of unemployment arising from the mismatch between the jobs available in the market and the skills of the available workers in the market.
    • Many people in India do not get job due to lack of requisite skills and due to poor education level, it becomes difficult to train them.
  • Cyclical Unemployment:
    • It is result of the business cycle, where unemployment rises during recessions and declines with economic growth.
    • Cyclical unemployment figures in India are negligible. It is a phenomenon that is mostly found in capitalist economies.
  • Technological Unemployment:
    • It is loss of jobs due to changes in technology.
    • In 2016, World Bank data predicted that the proportion of jobs threatened by automation in India is 69% year-on-year.
  • Frictional Unemployment:
    • The Frictional Unemployment also called as Search Unemployment, refers to the time lag between the jobs when an individual is searching for a new job or is switching between the jobs.
    • In other words, an employee requires time for searching a new job or shifting from the existing to a new job, this inevitable time delay causes the frictional unemployment. It is often considered as a voluntary unemployment because it is not caused due to the shortage of job, but in fact, the workers themselves quit their jobs in search of better opportunities.
  • Vulnerable Employment:
    • This means, people working informally, without proper job contracts and thus sans any legal protection. These persons are deemed ‘unemployed’ since records of their work are never maintained.
    • It is one of the main types of unemployment in India.

Related Terms

  • Unemployment trap is a situation when unemployment benefits discourage the unemployed to go to work. People find the opportunity cost of going to work too high when one can simply enjoy the benefits by doing nothing.
    • Description: While the purpose of social security and welfare systems is to provide relief to the unemployed, they end up providing them with an incentive not to return to work. An unemployment trap arises when opportunity cost of going to work is higher than the income received, discouraging people from returning to work and being productive.
  • Harmonised unemployment rates define the unemployed as people of working age who are without work, are available for work, and have taken specific steps to find work. The uniform application of this definition results in estimates of unemployment rates that are more internationally comparable than estimates based on national definitions of unemployment.
    • This indicator is measured in numbers of unemployed people as a percentage of the labour force and it is seasonally adjusted. The labour force is defined as the total number of unemployed people plus those in civilian employment.

Measurement of Unemployment in India

National Sample Survey Office (NSSO), an organization under Ministry of Statistics and Programme Implementation (MoSPI) measures unemployment in India on following approaches:

  • Usual Status Approach: This approach estimates only those persons as unemployed who had no gainful work for a major time during the 365 days preceding the date of survey.
  • Weekly Status Approach: This approach records only those persons as unemployed who did not have gainful work even for an hour on any day of the week preceding the date of survey.
  • Daily Status Approach: Under this approach, unemployment status of a person is measured for each day in a reference week. A person having no gainful work even for 1 hour in a day is described as unemployed for that day.

Unemployment stats (based on findings from CMIE’s latest data):

  • The unemployment rate in India rose to 7.2 percent in February 2019, the highest since September 2016, and up from 5.9 percent in February 2018.
  • The total number of employed persons in February 2019 is estimated at 400 million against 406 million in the year-ago period and 407.5 million employed in February 2017.
  • The labour participation rate fell from 43.2% in January 2019 to 42.7% in February 2019.
    • Labour Participation Rate defines that section of working population in the economy which is currently employed or seeking employment.

Causes of Unemployment

  • Large population.
  • Low or no educational levels and vocational skills of working population.
  • Inadequate state support, legal complexities and low infrastructural, financial and market linkages to small/ cottage industries or small businesses, making such enterprises unviable with cost and compliance overruns.
  • Huge workforce associated with informal sector due to lack of required education/ skills, which is not captured in any employment data. For ex: domestic helpers, construction workers etc.
  • The syllabus taught in schools and colleges, being not as per the current requirements of the industries. This is the main cause of structural unemployment.
  • Inadequate growth of infrastructure and low investments in manufacturing sector, hence restricting employment potential of secondary sector.
  • Low productivity in agriculture sector combined with lack of alternative opportunities for agricultural worker which makes transition from primary to secondary and tertiary sectors difficult.
  • Regressive social norms that deter women from taking/continuing employment.

Impact

  • The problem of unemployment gives rise to the problem of poverty.
  • Young people after a long time of unemployment indulge in illegal and wrong activities for earning money. This also leads to increase in crime in the country.
  • Unemployed persons can easily be enticed by antisocial elements. This makes them lose faith in democratic values of the country.
  • It is often seen that unemployed people end up getting addicted to drugs and alcohol or attempts suicide, leading losses to the human resources of the country.
  • It also affects economy of the country as the workforce that could have been gainfully employed to generate resources actually gets dependent on the remaining working population, thus escalating socioeconomic costs for the State. For instance, 1 percent increase in unemployment reduces the GDP by 2 percent

Steps Taken by Government

  • Integrated Rural Development Programme (IRDP) was launched in 1980 to create full employment opportunities in rural areas.
  • Training of Rural Youth for Self-Employment (TRYSEM): This scheme was started in 1979 with objective to help unemployed rural youth between the age of 18 and 35 years to acquire skills for self-employment. Priority was given to SC/ST Youth and Women.
  • RSETI/RUDSETI: With the aim of mitigating the unemployment problem among the youth, a new initiative was tried jointly by Sri Dharmasthala Manjunatheshwara Educational Trust, Syndicate Bank and Canara Bank in 1982 which was the setting up of the “RURAL DEVELOPMENT AND SELF EMPLOYMENT TRAINING INSTITUTE” with its acronym RUDSETI near Dharmasthala in Karnataka. Rural Self Employment Training Institutes/ RSETIs are now managed by Banks with active co-operation from the Government of India and State Government.
  • By merging the two erstwhile wage employment programme – National Rural Employment programme (NREP) and Rural Landless Employment Guarantee Programme (RLEGP) the Jawahar Rozgar Yojana (JRY) was started with effect from April, 1, 1989 on 80:20 cost sharing basis between the centre and the States.
  • Mahatma Gandhi National Rural Employment Guarantee Act (MNREGA):
    • It is an employment scheme that was launched in 2005 to provide social security by guaranteeing a minimum of 100 days paid work per year to all the families whose adult members opt for unskilled labour-intensive work.
    • This act provides Right to Work to people.
  • Pradhan Mantri Kaushal Vikas Yojana (PMKVY), launched in 2015 has an objective of enabling a large number of Indian youth to take up industry-relevant skill training that will help them in securing a better livelihood.
  • Start Up India Scheme, launched in 2016 aims at developing an ecosystem that promotes and nurtures entrepreneurship across the country.
  • Stand Up India Scheme, launched in 2016 aims to facilitate bank loans between Rs 10 lakh and Rs. 1 crore to at least one SC or ST borrower and at least one women borrower per bank branch for setting up a greenfield enterprise.

Way Forward

  • There are number of labour intensive manufacturing sectors in India such as food processing, leather and footwear, wood manufacturers and furniture, textiles and apparel and garments. Special packages, individually designed for each industry are needed to create jobs.
  • Public investment in sectors like health, education, police and judiciary can create many government jobs.
  • Decentralisation of Industrial activities is necessary so that people of every region get employment.
  • Development of the rural areas will help mitigate the migration of the rural people to the urban areas thus decreasing the pressure on the urban area jobs.
  • Entrepreneurs generate employments to many in a country; therefore government needs to encourage entrepreneurship among the youth.
  • Concrete measures aimed at removing the social barriers for women’s entry and their continuous participation in the job market is needed.
  • Government needs to keep a strict watch on the education system and should try to implement new ways to generate skilled labour force.
  • Effective implementation of present programs like Make in India, Skill India, Start up and Stand-Up India.
  • There is a need for National Employment Policy (NEP) that would encompass a set of multidimensional interventions covering a whole range of social and economic issues affecting many policy spheres and not just the areas of labour and employment. The policy would be a critical tool to contribute significantly to achieve the goals of the 2030 Agenda for Sustainable Development.
  • The underlying principles for the National Employment Policy may include
    • enhancing human capital through skill development;
    • creating sufficient number of decent quality jobs for all citizens in the formal and informal sectors to absorb those who are available and willing to work;
    • strengthening social cohesion and equity in the labour market;
    • coherence and convergence in various initiatives taken by the government;
    • supporting the private sector to become the major investor in productive enterprises;
    • supporting self-employed persons by strengthening their capabilities to improve their earnings;
    • ensuring employees’ basic rights and developing an education training and skill development system aligned with the changing requirements of the labour market.

The future of Machine Learning

Machine learning is a trendy topic in this age of Artificial Intelligence. The fields of computer vision and Natural Language Processing (NLP) are making breakthroughs that no one could’ve predicted. We see both of them in our lives more and more, facial recognition in your smartphones, language translation software, self-driving cars and so on. What might seem sci-fi is becoming a reality, and it is only a matter of time before we attain Artificial General Intelligence.

In this article, I will be covering Jeff Dean’s keynote on the advancements of computer vision and language models and how ML will progress towards the future from the perspective of model building.

The field of Machine learning is experiencing exponential growth today, especially in the subject of computer vision. Today, the error rate in humans is only 3% in computer vision. This means computers are already better at recognizing and analyzing images than humans. What an amazing feat! Decades ago, computers were hunks of machinery the size of a room; today, they can perceive the world around us in ways that we never thought possible.

The progress we’ve made from 26% error in 2011 to 3% error in 2016 is hugely impactful. The way I like to think is, computers have now evolved eyes that work. — Jeff Dean

Now this achievement — made possible with advancements in machine learning — isn’t just a celebration for computer geeks and AI experts, it has real-world applications that save lives and make the world a better place. Before I blab about a life-saving application of computer vision, let me illustrate to you the power of computer vision.

Let’s say I give you 10,000 pictures of dogs and I ask you to classify them into their respective species, are you able to do that? Well, you can, but you have to be a dog expert and it’ll take days by the time you’re done. But for a computer (with a GPU), this takes mere minutes. This incredible capability of computer vision opens up a profusion of applications.

Application of computer vision

One quintessential application for computer vision given by Jeff Dean is in diabetic retinopathy — which is a diabetes complication that affects the eye. Now to diagnose it, an extensive eye exam is required. In third-world countries and rural villages where there is a paucity of doctors, a machine learning model that uses computer vision to make a diagnosis will be extremely beneficial. As with all medical imaging fields, this computer vision can also be a second opinion for the domain experts, ensuring the credibility of their diagnosis. Generally, the purpose of computer vision in the medical field is to replicate the expertise of specialists and deploy it in places where people need it the most.


NLP and Transformers

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 Language models are algorithms that help machines understand the text and perform all kinds of operations such as translating text. According to Jeff Dean, a lot of progress has been made in language models.

Today, computers can understand paragraphs of text at a much deeper level than they could before. Even though they aren’t at the level of reading an entire book and understanding it the way we humans do, the ability to understand a few paragraphs of text is fundamental to things such as improving the Google search system.

The BERT model, the latest Natural Language Processing (NLP) model that Google announced has been put to use in their search ranking algorithms, This helped enhance the search results for myriads of different kinds of queries that were previously very difficult. In other words, the search system can now better understand different kinds of searches done by users and help provide better and more accurate answers.

“Deep learning and machine learning architectures are going to change a lot in the next few years. You can see a lot of this already, where now with NLP, the only game in town basically is Transformer networks,” — Yann LeCun

These Transformer-based models for translation are showing spectacular gains in the BLEU score, which is a measurement of translation quality. So, Machine Learning architectures that utilize transformers such as BERT are increasing in popularity and functionality.


The problem with ML today

In the keynote, the Google Senior Fellow mentioned atomic models that Machine Learning developers use today to perform all kinds of unit tasks. He believes these models are inefficient and computationally expensive, and more effort is required to achieve good results in those tasks.

To elaborate, in the ML world today, experts find a problem that they want to solve and they focus on finding the right dataset to train the model and perform that particular task. Dean argues that by doing so, they basically start from zero — they initialize the parameter of the model with random floating points and then try to learn about everything that tasks from the dataset.

To elaborate on this matter, he gives an excellent comparison that goes like this:

“It’s akin to when you want to learn something new, you forget all your education and you go back to being an infant, and now you try to learn everything about this task”

He compares this methodology with humans becoming infants every time we want to learn something new and taking a brain out and putting in a different one in. Not only is this method computationally expensive, but more effort is also required to achieve good outcomes in those tasks. And Jeff Dean proposes a solution.

Epitome

Computer vision and NLP will continue to play a significant role in our lives. But there are adverse implications to this advancement as well, such as China using facial recognition to implement a rating system on the people (straight out of an episode from the TV show black mirror) and the proliferation of fake news. We must progress in Machine Learning while taking into account of algorithmic biases and ethics that remind us of our place, a creation of God and not creators.

As for the uber model, there is much evidence proving we are inching closer and closer towards it. For example, transfer learning — a way of reusing the model for a different purpose achieves good results with fewer data and multi-task learning — a model that operates at small scales of five or six related things all tend to make things work well.

Thus, it’s logical to say that the realization of an uber model is plausible by extending those ideas — transfer learning and multi-task learning — out and developing on them, it’s only a matter of when and not how.

Thanks for reading my excerpt on the future of ML and my synopsis of Jeff Dean’s keynote. I hope you got a glimpse of what is to come in Machine Learning and AI.

Blue holes

Black holes… sounds pretty cool, and scary. They have baffled scientists for long. But there are many places beneath the ocean that are still baffling scientists and researchers since we have not explored even 5% of the oceans. One of these places is the “blue hole”. Sounds descriptive and uncreative as well but they got this same because apparently, they are blue. Blue holes are basically sinkholes or caverns in the ocean. They are a geological phenomenon that occurs when carbonate bedrock is composed of limestone erodes and collapses below the level of surrounding rock. Many researchers believe that blue holes are formed when water floods a previously cavernous region. At the end of the Ice Age, for instance, rising sea levels flooded caves that had been carved out by environmental factors like acidic rain, Discovery reports. The process can take more than 100,000 years. And since the water in the hole is so much deeper than the surrounding water, it looks like a much deeper blue. Hence the descriptive if a bit uncreative name.  Blue holes take the mysteries of the deep sea even deeper. The massive holes can be hundreds of feet deep, which causes them to appear a darker blue, compared to more shallow surroundings. A blue hole is an oasis in an otherwise barren seafloor. The natural phenomena are biodiversity hotspots teeming with plants and animals, including sea turtles, sharks, corals, mollusks, and sponges. Analyses of water samples taken during the Amberjack Hole exploration have shown that isotopes of radium and radon are present in the water. Their water circulation is poor, and they are commonly anoxic below a certain depth; this environment is unfavorable for most sea life, but nonetheless can support large numbers of bacteria. Most blue holes contain freshwater and saltwater. The halocline is the point in these blue holes where the freshwater meets the saltwater and where a corrosive reaction takes place that eats away at the rock. Over time this can create side passages, or horizontal “arms”, that extend from the vertical cave. These side passages can be quite long e.g., over 600 meters (2,000 ft) in the case of the Sawmill Sink in the Bahamas. Well-known examples can be found in the South China Sea (Dragon Hole), Belize (Great Blue Hole), the Bahamas (Dean’s Blue Hole), Guam, Australia (in the Great Barrier Reef), Egypt (in the Red Sea), and Florida (Green Banana). Exploring blue holes requires an extremely high level of expertise in the diving field, hence the fact that very few divers have ever attempted it. In 2009, however, a team of scientists set out to study seven of these blue holes in the Bahamas.   Through over 150 dives, the scientists, led by Keith Tinker, investigated bacteria able to live in anoxic environments. This allowed them to make connections to fields such as astrobiology where organisms thrive without oxygen or sunlight. In 2018, another group of scientists set out to explore the Great Blue Hole of Belize using two submarines of the latest technology. One of the major scientific contributions to the result of this expedition was the first 3-D map of its interior. The researchers captured features such as stalactites, the hydrogen sulfide layer, and other details that cannot usually be seen by the naked human eye.
Nature is filled with surprises, but we must be careful with what we play. Last time someone ate a bat, and the whole world is now repaying now.

Sushant Singh Rajput hired a special team to achieve his list of dreams. Details inside

Sushant Singh Rajput had a list of 150 dreams and hired a special PRO team to achieve them. His flatmate, Samuel Haokip, was a part of this team and also used to help Sushant with his legal matters as well as handling finances. Sushant Singh Rajput wanted 5-6 people who could help him achieve his list of dreams

a man looking at the camera: Sushant Singh Rajput had a special team of people to help him achieve his dreams.

Following were the members of Sushant Singh Rajput’s PRO team:

Samuel Haokip

Samuel Haokip met Sushant Singh Rajput through common friends. Sushant was looking for someone who has knowledge of law, which is why Haokip, who is a lawyer, became a part of his team.

Samuel Haokip lived with Sushant Singh Rajput for almost a year and left his house in July 2019, since he got a job in a law firm. It was Sushant Singh Rajput’s sister, Priyanka and her husband, Siddharth, who helped Samuel in finding the job. He left Mumbai and shifted to Delhi in order to continue with his law practice. He used to majorly focus on the actor’s film contracts, negotiating with producers, drafting contracts for house helps,and used to manage other people who used to work for Sushant.

Kushal Zaveri

He was with Sushant Singh Rajput since the actor’s television days. In a telephonic interview with Aaj Tak, he had shared that he was with the late actor during the shooting of Dil Bechara as well. However, he went to Goa for a personal project in 2018 and his contact with the actor decreased.

Siddharth Gupta

He is Vikas Gupta’s brother and was also Sushant Singh Rajput’s roommate for some time.

Abbas

He worked as the editor in the PRO team.

Gradually, all members got busy with their work and left Sushant Singh Rajput’s PRO team. Samuel Haokip was the last one left.

Sushant then reached out to one of his friends as he wanted to hire more people. It was here that Siddharth Pithani entered the picture, upon a friend’s recommendation. Samuel Haokip trained Siddharth Pithani and it was in April 2019 that Rhea Chakraborty entered the actor’s life.

Earlier, only Samuel Haokip and Sushant Singh Rajput were staying together along with the house helps, the cook, Keshav and housekeeper, Neeraj. Gradually, Rhea, as well as Siddharth Pithani, also started living there. Sushant had also called Dipesh Sawant, a friend of Abbas, to stay with him.

South Korea closes nightclubs, beaches as Covid-19 cases surge

South Korea ramped up coronavirus restrictions on Sunday to try to contain a growing outbreak, as many countries around the world battled worrying surges in infections.

The pandemic has killed more than 800,000 people globally, and continues to unleash destruction with areas such as Western Europe detecting spikes in infections not seen for many months.

Infections have soared past 23 million globally, and some countries are still facing their first waves — such as India, which crossed three million cases on Sunday.

South Korea, which had largely brought its outbreak under control, tightened curbs to try to contain a new, growing cluster of cases.

“The situation is very grave and serious as we are on the brink of a nationwide pandemic,” warned Jung Eun-kyeong, chief of the Korea Centers for Disease Control and Prevention.

Nightclubs, karaoke bars and beaches have been closed, with tight restrictions on large gatherings and religious services, after hundreds of infections were linked to Protestant churches.

Face masks will be mandatory in the capital Seoul’s public areas from midnight.

Lockdowns, social distancing and face masks are among the few options available to governments with no effective treatment or vaccine available yet.

India, which imposed one of the world’s strictest lockdowns, has relaxed it over recent weeks to help ease the pressure on its reeling economy.

But that has also led to a sharp rise in cases, taking its total past three million.

“We are seeing the virus spread across India,” said K Srinath Reddy from the NGO Public Health Foundation of India.

The World Health Organization, however, said Friday that the world should be able to rein in the disease in less than two years.

‘Don’t feel invincible’

Italy — once the European epicentre of the virus — said Saturday it had registered more than 1,000 new infections in the past 24 hours, the highest level since the end of a punishing lockdown in May.

The story is similar across Spain, Germany and France.

The Rome region also said it had recorded a record number of cases in the past 24 hours, a rise health officials blamed on people returning from holiday.

Most of those infected are young people who are not showing symptoms, the Italian capital’s health official Alessio D’Amato said, warning them to stay at home.

“Don’t feel invincible,” he urged them.

The virus lockdowns and social distancing measures have unleashed vast economic destruction and impacted all types of social activities, including sports games and concerts.

In Germany, a university has launched a series of pop concerts under coronavirus conditions, hoping the mass experiment with 2,000 people can determine whether large events can safely resume.

But with no vaccine yet, economies in hard-hit regions like Latin America are struggling to contain the staggering costs of the pandemic — with a rise not only in poverty but political turmoil and crime too.

US election crisis

The United States remains the worst-hit country in the world, with nearly 5.7 million infections and deaths approaching 180,000.

The run-up to the presidential election has been dominated by the coronavirus, with President Donald Trump facing intense criticism for his handling of the crisis.

The pandemic is set to impact the electoral exercise itself, with Americans expected to vote by mail in massive numbers instead of visiting polling centres.

But that has caused another political standoff, with the postal service warning most states it could not guarantee on-time delivery of mail-in ballots.

Trump — trailing his challenger Joe Biden in polls — has opposed more funding for the cash-strapped US Postal Service, acknowledging it would be used to help process ballots.

He has repeatedly and baselessly linked mail-in voting to election fraud.

Biden’s fellow Democrats in the US House of Representatives approved a $25 billion infusion for the USPS on Saturday, but it is likely to die in the Senate — which is controlled by the Republicans.

Claims over coronavirus vaccine availability in India false, will confirm once trial results are out: SII

The claim by certain media houses that Oxford-AstraZeneca coronavirus vaccine candidate COVISHIELD will be available in India in the next 73 days are “completely false and conjectural”, the Serum Institute of India (SII), the Indian partner of the AstraZeneca clarified on Sunday.

a close up of a bottle© Provided by Jagran EnglishThe SII said that the official confirmation on COVISHIELD’s availability in India will be confirmed only after the vaccine is proven immunogenic and efficacious in human trials which are currently underway across the country.

“The current claims over COVISHIELD’s availability in the media are completely false and conjectural. Presently, the government has granted us permission to only manufacture the vaccine and stockpile it for future use,” a statement from the Serum Institute of India shared by news agency ANI read. 

The statement further stated that the phase-3 trials for Oxford-AstraZeneca vaccine candidate are currently underway and the vaccine will be commercialised in India only after successful trials and necessary regulatory approvals.

“COVISHIELD will be commercialized once trials are proven successful & requisite regulatory approvals are in place. Phase-3 trials for Oxford-AstraZeneca vaccine are underway. Only once the vaccine is proven immunogenic & efficacious, SII will confirm its availability officially,” it said.

The clarification from the SII came after a report published by Business Today claimed that the Oxford University-Astra-Zeneca vaccine candidate will be commercialised in 73 days. The website cited a top official from the SII as there source of information.

“The government has given us a ‘special manufacturing priority license’ and fast-tracked the trial protocol processes to get the trials completed in 58 days. By this, the first dosing is happening from today in the final phase (Phase III) and the second dosing will happen after 29 days.

“The final trial data will be out in another 15 days from the second dosing. By that time, we are planning to commercialise Covishield,” an SII official was quoted as saying by the website in its report.  

4 Tips for Effective IELTS Preparation

To migrate or study in English speaking nations, one needs to give an IELTS test. The International English Language Testing System (IELTS) assesses the person’s ability to speak, write, listen, and read in English. The test is designed to understand how you will use English in your daily life such as in university, workplace, or other social situations.

Before providing the tips on how to do the preparation, here is the breakdown of the types of IELTS test. There are two types: Academic and General. The IELTS Academic test is for those willing to pursue undergraduate or post-graduation or join a professional organization in an English-speaking nation. Second, the IELTS General Training test is for those who want to train or study at below degree level, to work, or to emigrate.

The formats of these two tests are a bit different, but the test assessment will still be on four skills: Reading, Listening, Writing, and Speaking.

Reading Test: This will include a wide range of reading skills such as attention to detail, a general sense of the passage, meaning derived from it, understanding of writer’s opinions, attitudes, and how will you understand the development of the argument.

Listening Test: It assesses how well you recognize opinions, attitudes, the purpose of the speaker, and also factual information and general ideas.

Writing Test: The Writing test is designed to measure the wide range of writing skills including grammar, vocabulary, how you can write responses, organize ideas, and recognize mistakes.

Speaking Test: The IELTS Speaking Test assesses how fluently and accurately you communicate in English. You can be asked to speak on various topics and express your opinions.

Getting back on how to crack the IELTS exam, just like any other test IELTS to needs some preparation. These four tips can help you ace the IELTS exam.

  • First and foremost, Read! Read! Read! Whether it’s a book, newspaper, magazine, or any written material. While reading, always have a credible English-English dictionary with you. This way you will work out the meanings of the new words making sure you don’t translate back to your language. You can also read an English newspaper every morning and listen to English news channels. It will enhance your reading and listening skills as well as keep you updated about the happenings in the world. Sounds good?
  • Improve your vocabulary! The more words you are exposed to, better will be your vocabulary. Jot down the words you have heard recently or you don’t know and highlight them with a marker. Check out its meaning in the dictionary and then start putting these words into daily speech. Using new words frequently will help in making your English fluent. As a fact, it takes from 10 to 20 repetitions to make a word part of your daily speech. Do see its pronunciation online if not sure. Speak those words while talking to your parents, friends, or somebody on call. This will increase your confidence and you will be well versed on the day of your exam.
  • Listen to English radio, shows, or news channels. After that try to write them down and analyze. Also with that, separately write words or sentences that were appealing to you. Use them while you write essays or speak. Don’t watch videos online since you can pause or rewind them. This won’t help as it will break your flow of listening. Hear it once only. After you are done repeat whatever you recall from the show, use stress and intonation appropriately. Make sure you record it so that you can find out your mistakes and improve accordingly.
  • So far whatever words you have learned, phrase them into sentences and then into paragraphs. While writing always set a timer. This will keep you at pace and improve your speed during the exam. Check for comma mistakes, full stop, and grammar. See-through the sample papers and find out what is the word limit given in the writing paper. Accordingly, write if say the set limit is 200 words don’t write just 150 words. This will lead to losing marks. Generally, a person is ok reading, speaking, and listening but they have a hard time writing, in that case, while practicing start with your favorite topic. Start with as basic as possible. Suppose you like chocolate ice cream, write on that. Sooner or later, you will get used to and can start with difficult topics. When you plan your essay, always have some spare time in the end to check your work.

Taking the IELTS test can be stressful so don’t forget to put these helpful tips. It will equip you to be ready for the exam. Commit and practice thoroughly. With this, you’ll feel more confident and be able to tackle the test and get the desired score.