Sleepy Classes IAS
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Key points:

โ€‹๐—ž๐—ฒ๐˜† ๐——๐—ฎ๐˜๐—ฎ ๐—ฎ๐—ป๐—ฑ ๐—ฆ๐—ฐ๐—ฎ๐—น๐—ฒ
Data centres currently consume about 1.5 percent of the worlds electricity producing 0.5 percent of emissions from fuel combustion Indian data centres account for two to three hundredths of our water demand while two thirds of United States (US) data centres built since 2022 sit in water stressed places.

โ€‹๐—ž๐—ฒ๐˜† ๐—–๐—ผ๐—ป๐—ฐ๐—ฒ๐—ฟ๐—ป๐˜€
High cooling demands and massive energy draw strain local grids and municipal supplies in water stressed regions like Visakhapatnam and Mumbai while incessant fan cooling creates noise pollution and civic friction such as in Thane.

โ€‹๐—ฃ๐—ผ๐—น๐—ถ๐—ฐ๐˜† ๐—ฆ๐—ผ๐—น๐˜‚๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ฃ๐—ฟ๐—ฒ๐—ฐ๐—ฒ๐—ฑ๐—ฒ๐—ป๐˜๐˜€
Karnatakas policy mandates annual water reporting and strict siting water and noise thresholds while global models successfully use closed loop air cooled chillers and zero water consumption designs.

โ€‹๐—ช๐—ฎ๐˜† ๐—™๐—ผ๐—ฟ๐˜„๐—ฎ๐—ฟ๐—ฑ
Link policy incentives to Power Usage Effectiveness (PUE) mandate pre construction basin water stress tests and enforce strict noise and emission caps.
โค4๐Ÿ‘1๐Ÿ”ฅ1
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Forwarded from Sociology Sleepy Classes
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Forwarded from Sociology Sleepy Classes
Absolutely honoured to be working with an immensely hardworking team ๐Ÿ™๐Ÿ™

Seeing really good results coming in from Haryanaโ€ฆ today Rank 1 messaged ๐Ÿ™๐Ÿ™

Immensely happy and grateful ๐Ÿ™๐Ÿ™
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Here is why multi lateral water governance is urgently needed:

โ€‹๐—–๐—ผ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ฒ๐—บ๐—ฒ
Climate induced cryospheric degradation in the [Hindu Kush Himalaya] threatens Asian water security compounding transboundary geopolitical risks.

โ€‹๐—ช๐—ฎ๐˜๐—ฒ๐—ฟ ๐—ง๐—ผ๐˜„๐—ฒ๐—ฟ
The region holds 5736 cubic kilometers of ice reserves feeding the Indus Ganges and Brahmaputra river systems.

โ€‹๐—”๐—ฐ๐—ฐ๐—ฒ๐—น๐—ฒ๐—ฟ๐—ฎ๐˜๐—ฒ๐—ฑ ๐— ๐—ฒ๐—น๐˜
Rapid glacier wastage since 2000 has heightened the risk of [Glacial Lake Outburst Floods] and dangerous landslides.

โ€‹๐—ง๐—ฟ๐—ฎ๐—ป๐˜€๐—ฏ๐—ผ๐˜‚๐—ป๐—ฑ๐—ฎ๐—ฟ๐˜† ๐—™๐—ฟ๐—ถ๐—ฐ๐˜๐—ถ๐—ผ๐—ป
Upstream dams on the Yarlung Zangpo by China risk flow timing while the [Indus Waters Treaty] faces disputes over hydropower projects.

โ€‹๐— ๐—ฎ๐—ท๐—ผ๐—ฟ ๐—›๐—ฎ๐˜‡๐—ฎ๐—ฟ๐—ฑ๐˜€
Erratic rainfall severe plastic and pharmaceutical pollution and inadequate river basin environmental safeguards threaten the ecosystem.

โ€‹๐—ช๐—ฎ๐˜† ๐—™๐—ผ๐—ฟ๐˜„๐—ฎ๐—ฟ๐—ฑ
Establish mandatory real time hydrological data exchange [Glacial Lake Outburst Flood] early warning systems and shift to basin wide climate resilient dam engineering.
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Here is how we can scale Artificial Intelligence (AI) using a public infrastructure approach:

โ€‹๐—–๐—ผ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ฒ๐—บ๐—ฒ
Economic gains from Artificial Intelligence (AI) in developing nations will come from broad downstream deployment and worker augmentation rather than building frontier models.

โ€‹๐—ž๐—ฒ๐˜† ๐—ฆ๐˜๐—ฎ๐˜๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—Ÿ๐—ฎ๐—ฏ๐—ผ๐—ฟ ๐—œ๐—บ๐—ฝ๐—ฎ๐—ฐ๐˜
Only 4.5 percent of jobs face automation risk compared to 14.2 percent in advanced economies while 16.2 percent can gain productivity making Artificial Intelligence (AI) complementary to labor.

โ€‹๐—–๐—ผ๐—ฟ๐—ฒ ๐—–๐—ต๐—ฎ๐—น๐—น๐—ฒ๐—ป๐—ด๐—ฒ๐˜€
High dependency on a few global hyperscalers for compute combined with gaps in baseline electricity connectivity local language data and digital skills.

โ€‹๐—ช๐—ฎ๐˜† ๐—™๐—ผ๐—ฟ๐˜„๐—ฎ๐—ฟ๐—ฑ
Apply [Digital Public Infrastructure] principles like the [Unified Payments Interface] to scale localized tools like Bharat VISTAAR.

โ€‹๐—œ๐—บ๐—ฝ๐—น๐—ฒ๐—บ๐—ฒ๐—ป๐˜๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ฅ๐˜‚๐—น๐—ฒ๐˜€
Design pilots for scale evaluate via real world evidence and institutionalize cross state learning.
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From crop diversification to dual use solar farms here is how we can rethink agricultural policy and boost rural prosperity:

โ€‹๐—–๐—ผ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ฒ๐—บ๐—ฒ
Raising farm incomes requires shifting from surplus cereals to pulses and oilseeds diversification subsidy rationalization and Agri Photovoltaics [Agri-PV]

โ€‹๐—ž๐—ฒ๐˜† ๐——๐—ฎ๐˜๐—ฎ
Average annual agricultural growth is 4 percent contrasting a high cereal surplus with a massive 40 billion dollar import bill for edible oils and pulses.

โ€‹๐—ช๐—ฎ๐˜๐—ฒ๐—ฟ ๐——๐—ฒ๐—ฝ๐—น๐—ฒ๐˜๐—ถ๐—ผ๐—ป
Paddy power and canal subsidies hit approximately Rs 40000 per hectare while groundwater drops 1.7 feet per year in Haryana.

โ€‹๐—ž๐—ฒ๐˜† ๐—ฅ๐—ฒ๐—ณ๐—ผ๐—ฟ๐—บ๐˜€
Shift paddy subsidies into a Rs 35000 per hectare direct incentive for cultivating pulses and oilseeds to save water and reduce import dependence.

โ€‹๐—”๐—ด๐—ฟ๐—ถ ๐—ฃ๐—ฉ ๐—ฎ๐—ป๐—ฑ ๐—ฃ๐—ผ๐—น๐—ถ๐—ฐ๐˜† ๐—ฃ๐˜‚๐˜€๐—ต
The Urjadata model installs elevated solar panels over crops to multiply incomes while a restructured [Pradhan Mantri Kisan Urja Suraksha evam Utthaan Mahabhiyan] or PM-KUSUM can integrate dual land use and grid feed in tariffs.
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Here is why expert committees are urgently demanding a moratorium on mega infrastructure:

โ€‹๐—–๐—ผ๐—ฟ๐—ฒ ๐—ง๐—ต๐—ฒ๐—บ๐—ฒ
Accelerating Himalayan cryospheric collapse demands an immediate moratorium on mega infrastructure elevation caps on construction and hazard averse development.

โ€‹๐—ž๐—ฒ๐˜† ๐—ฆ๐˜๐—ฎ๐˜๐˜€ ๐—ฎ๐—ป๐—ฑ ๐—ฉ๐˜‚๐—น๐—ป๐—ฒ๐—ฟ๐—ฎ๐—ฏ๐—ถ๐—น๐—ถ๐˜๐—ถ๐—ฒ๐˜€
The Indian Himalayan Region is warming at 0.3 degrees Celsius per decade twice the global average while [Hindu Kush Himalaya] ice loss has doubled since 2000.

โ€‹๐—ฃ๐—ฒ๐—ฟ๐—บ๐—ฎ๐—ณ๐—ฟ๐—ผ๐˜€๐˜ ๐—ง๐—ต๐—ฎ๐˜„
The loss of frozen geological cement causes catastrophic rock ice avalanches and flash floods such as in Bhote Koshi.

โ€‹๐—–๐—ฟ๐—ถ๐˜๐—ถ๐—ฐ๐—ฎ๐—น ๐—ฃ๐—ผ๐—น๐—ถ๐—ฐ๐˜† ๐—ฅ๐—ถ๐˜€๐—ธ๐˜€
High risk projects like the Chenab Beas link tunnel proceed despite expert warnings from the Avay Shukla and Ravi Chopra committees urging high altitude construction caps.

โ€‹๐—ช๐—ฎ๐˜† ๐—™๐—ผ๐—ฟ๐˜„๐—ฎ๐—ฟ๐—ฑ
Enforce elevation based bans on large infrastructure deploy high altitude satellite early warning networks and implement valley specific river flood zoning.
โค4๐Ÿ‘1๐Ÿ˜ฑ1
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According to the National Statistical Office (NSO), how much time per day do women in India spend on unpaid care and domestic work compared to men?
Anonymous Quiz
17%
Women: 127 mins | Men: 16 mins
41%
Women: 299 mins | Men: 97 mins
8%
Women: 67 mins | Men: 112 mins
34%
Women: 452 mins | Men: 46 mins
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