91st Constitutional Amendment Act, 2003
Why? Anti-defection law failed to curb bulk defections; 1/3 split exemption encouraged instability. Dinesh Goswami Committee (1990), Law Commission 170th Report (1999) & NCRWC (2002) sought reform.
Key reforms
• Split exemption (1/3) abolished —> only 2/3 merger protection remains.
• Defector barred from becoming Minister/remunerative political post during prescribed disqualification period.
• CoM ceiling: Centre —> 15% of Lok Sabha strength; State —> 15% of Assembly strength, minimum 12 ministers.
• Thus, sought to curb defection + office inducements + jumbo ministries.
Conclusion : 91st Amendment strengthened political stability by closing the “split” loophole and restricting the use of ministerial office as a reward for defection.
Source: Laxmikanth
#GS2mains
Why? Anti-defection law failed to curb bulk defections; 1/3 split exemption encouraged instability. Dinesh Goswami Committee (1990), Law Commission 170th Report (1999) & NCRWC (2002) sought reform.
Key reforms
• Split exemption (1/3) abolished —> only 2/3 merger protection remains.
• Defector barred from becoming Minister/remunerative political post during prescribed disqualification period.
• CoM ceiling: Centre —> 15% of Lok Sabha strength; State —> 15% of Assembly strength, minimum 12 ministers.
• Thus, sought to curb defection + office inducements + jumbo ministries.
Conclusion : 91st Amendment strengthened political stability by closing the “split” loophole and restricting the use of ministerial office as a reward for defection.
Source: Laxmikanth
#GS2mains
Terms from this News
- Gale: sustained strong wind, roughly 62–88 km/h.
- Squall: sudden sharp rise in wind speed, lasting at least about a minute.
- Gust: very brief, momentary increase in wind speed.
Note:- Gust ≠ Squall ≠ Gale —> Gust = momentary peak; Squall = sudden sustained increase ≥1 min; Gale = sustained wind-speed category (~62–88 km/h).
#BIHARspecial
#GEOGRAPHY
- Gale: sustained strong wind, roughly 62–88 km/h.
- Squall: sudden sharp rise in wind speed, lasting at least about a minute.
- Gust: very brief, momentary increase in wind speed.
Note:- Gust ≠ Squall ≠ Gale —> Gust = momentary peak; Squall = sudden sustained increase ≥1 min; Gale = sustained wind-speed category (~62–88 km/h).
#BIHARspecial
#GEOGRAPHY
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Bihar Victim Rights Centre (VRC)
1. Bihar’s first Victim Rights Centre (VRC) will be inaugurated at the Bihar State Legal Services Authority (BSLSA), Patna.
2. It will be India’s second such VRC after Kerala.
3. The VRC is being launched on a pilot basis in Patna.
4. It will act as a single-point/one-stop support centre for crime victims:-covering legal, medical, financial and other assistance through coordination with existing agencies.
5. A transgender helpline will also be launched alongside the VRC.
6. Based on its first-year performance, the model may be replicated in other districts through District Legal Services Authorities (DLSAs).
#BIHARspecial
1. Bihar’s first Victim Rights Centre (VRC) will be inaugurated at the Bihar State Legal Services Authority (BSLSA), Patna.
2. It will be India’s second such VRC after Kerala.
3. The VRC is being launched on a pilot basis in Patna.
4. It will act as a single-point/one-stop support centre for crime victims:-covering legal, medical, financial and other assistance through coordination with existing agencies.
5. A transgender helpline will also be launched alongside the VRC.
6. Based on its first-year performance, the model may be replicated in other districts through District Legal Services Authorities (DLSAs).
#BIHARspecial
Monsoon Prediction in a Warming Climate
Core issue: Indian monsoon is a complex coupled land–ocean–atmosphere system. Climate change is altering these interactions, increasing uncertainty in timing, spatial distribution and intensity of rainfall.
Why monsoon prediction is difficult
1. Multiple drivers act together: land–ocean temperature contrast, Pacific/Indian Ocean SSTs, Himalayan winds, aerosols and convection.
2. Global climate models work at coarse scales; small errors in temperature/cloud representation can produce large rainfall errors.
3. Models have struggled to reproduce the observed ~5–10% decline in monsoon rainfall during 1950–2000, partly due to competing effects of GHGs and aerosols.
4. Localised cloud processes and kilometre-scale convection remain difficult to simulate.
How AI can improve forecasts(use of tech/AI in weather forecasting)
1. AI can learn atmospheric evolution from huge volumes of satellite + ground observations.
2. AI weather models can outperform conventional forecasts for several parameters and run rapidly on GPUs.
3. Useful for predicting active/break phases, heat waves and regional rainfall, aiding farm decisions.
4. India can increasingly develop/adapt such models domestically using its large observation network, scientific talent and computing capacity.
But AI is not sufficient(limitations)
• Future climate may lie outside historical training data —> AI can face out-of-distribution uncertainty.
• Hence, need hybrid AI + physics-based climate models, not replacement of physical modelling.
Climate-change signal
• Warmer atmosphere holds more moisture —> heavier rainfall extremes.
• Article estimates that with 2–3°C warming, rare intense rainfall events could become roughly 15–20% more intense.
• Major uncertainties remain regarding monsoon onset, active-break cycles and regional distribution.
Way Forward
• Expand radar, rain-gauge and ocean-buoy observations.
• Develop high-resolution regional and hybrid AI–physics models.
• Improve last-mile delivery through farmer advisories and disaster-warning systems.
• Build infrastructure with adaptive safety margins: drainage/reservoir design should account for stronger future extremes.
• Climate planning should be robust to uncertainty rather than dependent on a single precise forecast.
#GS2mains
#AI
Core issue: Indian monsoon is a complex coupled land–ocean–atmosphere system. Climate change is altering these interactions, increasing uncertainty in timing, spatial distribution and intensity of rainfall.
Why monsoon prediction is difficult
1. Multiple drivers act together: land–ocean temperature contrast, Pacific/Indian Ocean SSTs, Himalayan winds, aerosols and convection.
2. Global climate models work at coarse scales; small errors in temperature/cloud representation can produce large rainfall errors.
3. Models have struggled to reproduce the observed ~5–10% decline in monsoon rainfall during 1950–2000, partly due to competing effects of GHGs and aerosols.
4. Localised cloud processes and kilometre-scale convection remain difficult to simulate.
How AI can improve forecasts(use of tech/AI in weather forecasting)
1. AI can learn atmospheric evolution from huge volumes of satellite + ground observations.
2. AI weather models can outperform conventional forecasts for several parameters and run rapidly on GPUs.
3. Useful for predicting active/break phases, heat waves and regional rainfall, aiding farm decisions.
4. India can increasingly develop/adapt such models domestically using its large observation network, scientific talent and computing capacity.
But AI is not sufficient(limitations)
• Future climate may lie outside historical training data —> AI can face out-of-distribution uncertainty.
• Hence, need hybrid AI + physics-based climate models, not replacement of physical modelling.
Climate-change signal
• Warmer atmosphere holds more moisture —> heavier rainfall extremes.
• Article estimates that with 2–3°C warming, rare intense rainfall events could become roughly 15–20% more intense.
• Major uncertainties remain regarding monsoon onset, active-break cycles and regional distribution.
Way Forward
• Expand radar, rain-gauge and ocean-buoy observations.
• Develop high-resolution regional and hybrid AI–physics models.
• Improve last-mile delivery through farmer advisories and disaster-warning systems.
• Build infrastructure with adaptive safety margins: drainage/reservoir design should account for stronger future extremes.
• Climate planning should be robust to uncertainty rather than dependent on a single precise forecast.
#GS2mains
#AI
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Sanjay Gandhi Biological Park (Patna Zoo) houses 10 one-horned rhinoceroses- the highest among Indian zoos for the 10th consecutive year; it began rhino breeding in 1988 and has recorded 40 calves with 100% survival of zoo-born calves.
#BIHARspecial
#BIHARspecial
Senior IAS officer Mandeep K Bhandari was appointed as the chairman of the Central Board of Secondary Education (CBSE) after the Centre carried out a bureaucratic reshuffle
#CA2026
#APPOINTMENT
#CA2026
#APPOINTMENT
Digi Yatra: Facial-recognition based contactless airport travel system; international departure trials from Oct 2026 will use e-passports/NFC, while immigration checks will continue separately.
#CA2026
#CA2026
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e-Methanol Plant in Deendayal Port Authority , Kandla
e-Methanol (electronic methanol or synthetic methanol) is a low-carbon, synthetic liquid fuel (CH_3OH) produced by combining green hydrogen with captured carbon dioxide (CO_2) using renewable energy.
#CA2026
e-Methanol (electronic methanol or synthetic methanol) is a low-carbon, synthetic liquid fuel (CH_3OH) produced by combining green hydrogen with captured carbon dioxide (CO_2) using renewable energy.
#CA2026
India is piloting the newly established BRICS Network of Centres of Excellence (CoEs) in Mental Health. The National Institute of Mental Health and Neurosciences (NIMHANS) serves as the coordinating nodal centre responsible for framing the governance protocol.
#CA2026
#CA2026
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IIT Delhi has designed India’s first demonstrable, indigenous programmable micro-Graphics Processing Unit (GPU) aimed at low-cost embedded systems.
Implemented on a Spartan-7 Field Programmable Gate Array (FPGA) using Register Transfer Language (RTL) rather than a standalone dedicated silicon chip.
#CA2026
Implemented on a Spartan-7 Field Programmable Gate Array (FPGA) using Register Transfer Language (RTL) rather than a standalone dedicated silicon chip.
#CA2026
Bihar State CIC: DGP Vinay Kumar (1991-batch IPS) is under consideration for State Chief Information Commissioner; under RTI Act, 2005 (Sec. 15), the Governor appoints the State CIC on recommendation of a committee comprising CM + Leader of Opposition + a Cabinet Minister nominated by CM.
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#APPOINTMENT
#BIHARspecial
#APPOINTMENT
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