{"id":91393,"date":"2024-05-11T10:16:16","date_gmt":"2024-05-11T04:46:16","guid":{"rendered":"https:\/\/www.practicemock.com\/blog\/?p=91393"},"modified":"2024-05-11T10:16:52","modified_gmt":"2024-05-11T04:46:52","slug":"the-hindu-editorial-vocabulary-11th-may-2024","status":"publish","type":"post","link":"https:\/\/www.practicemock.com\/blog\/the-hindu-editorial-vocabulary-11th-may-2024\/","title":{"rendered":"The Hindu Editorial Vocabulary 11th May 2024"},"content":{"rendered":"
Home<\/a><\/span> \u00bb Vocabulary<\/a><\/span> \u00bb The Hindu Editorial Vocabulary 11th May 2024<\/span><\/span><\/div>\n\n\n

Vocabulary Knowledge is important for candidates. In many government exams, questions are asked from the vocab section in English. Improve your communication by learning new words We prepared Hindu Editorial Vocabulary 11th May 2024 covers contextual meanings of difficult words. <\/p>\n\n\n\n

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The Hindu Editorial Vocabulary On AlphaFold 3<\/h2>\n\n\n\n

Proteins are long chains of amino-acid residues that fold into specific<\/strong> (relating to one thing and not others; particular<\/strong>) shapes. Properly folded proteins function normally whereas misfolded ones can lead to debilitating diseases. Since these chains are quite long, a given protein can actually fold into one of a very large number of shapes \u2014 yet it makes a beeline for a specific shape while avoiding all the others. How and why this happens constitute<\/strong> (to be or be considered as something<\/strong>) an important mystery in structural biology called the protein-folding problem. In 2018, five decades after it was mooted, a Google subsidiary named DeepMind developed a purpose-built AI tool to predict<\/strong> (to say that an event or action will happen in the future, especially as a result of knowledge or experience<\/strong>) the shapes into which different proteins could fold, called AlphaFold. The upgraded AlphaFold 2 followed two years later. Many scientists and technologists acknowledge that these two deep-learning systems have transformed human awareness of protein structures, a feat the machines demonstrated<\/strong> (to show or make something clear<\/strong>) in the biennial Critical Assessment of Protein Structure Prediction contest. Recently, DeepMind launched AlphaFold 3, which can reportedly predict the shapes with nearly 80% accuracy as well as model DNA, RNA, ligands, and modifications<\/strong> (a change to something, usually to improve it<\/strong>) to them. As with the first two AlphaFolds, no. 3 is great for being able to elucidate the folded proteins\u2019 structures in seconds rather than the years humans have required with advanced microscopic techniques.<\/p>\n\n\n\n

Not surprisingly, the excitement that followed the release of AlphaFold 3 has been unable to escape the hype and overblown expectations<\/strong> (the feeling that good things are going to happen in the future<\/strong>) that dogged the launches of its predecessors. These machines can predict protein structures with relatively high accuracy but they cannot say why they are folded that way; this is still the task of human scientists. How the AlphaFolds will catalyse drug discovery is also unclear. Many drugs fail to make it to the market from the laboratory because medical researchers are unable to anticipate<\/strong> (to imagine or expect that something will happen<\/strong>) all the interactions<\/strong> (an occasion when two or more people or things communicate with or react to each other<\/strong>) between the drugs\u2019 various components and various parts of the body. The protein-folding problem is important to crack but it will not magically improve drugs\u2019 chances in human clinical trials. It is a step in that direction. Finally, the free use of AlphaFold 3 is limited while its inner mechanisms are unavailable for public exploration or scrutiny, so far. While the motivation to innovate<\/strong> (to introduce changes and new ideas<\/strong>) of DeepMind is laudable, the cutting-edge value AlphaFold 3 presents to health care means the company should explore alternative revenue models in which the system is not trapped behind paywalls or exorbitant<\/strong> (of prices and demands) much too large<\/strong> prices \u2014 a fate that has already befallen scientific papers and medicines born of publicly funded research. Recall that the AlphaFolds\u2019 training data itself includes protein structures first elucidated by such research.<\/p>\n\n\n\n

Hindu Editorial Vocab Wordlist 11th May 2024<\/h2>\n\n\n\n

Keep a good command of vocabulary beneficial to improving scores in English in government exams. We bring a daily list of difficult words and their meanings in Hindu Editorial Vocabulary 11th May 2024.<\/p>\n\n\n\n