About Mission for Aatmanirbharta in Pulses:           

• It is aimed at boosting domestic production and achieving self-sufficiency (Aatmanirbharta) in pulses.
• Time Period: The Mission will be implemented over a six-year period, from 2025-26 to 2030-31.
• It aims to achieve self-sufficiency in pulses by significantly enhancing domestic production, reducing import dependence, and sustainably improving farmers’ incomes.
• The Mission plans to expand the area under pulses cultivation by an additional 35 lakh hectares, targeting rice fallows and other suitable lands, while promoting intercropping and crop diversification.
• Key Features of Mission for Aatmanirbharta in Pulses:
  • Comprehensive strategy: The mission covers research, seed systems, area expansion, procurement, and price stability.
  • Focus on quality seeds: A key focus will be the development and dissemination of high-yielding, pest-resistant, and climate-resilient pulses varieties, supported by a robust seed system.
  • Seed Production: To ensure availability of premium quality seeds, states will prepare five-year rolling seed production plans.
    • The breeder seed production will be supervised by the Indian Council of Agricultural Research (ICAR).
  • Capacity building: Structured training programmes for farmers and seed growers to promote sustainable techniques and modern technologies.
  • Post-harvest infrastructure: To strengthen markets and value chains, the Mission will help develop processing units, thereby reducing crop losses, improving value addition.
  • Cluster-Based Approach: Tailoring interventions to the specific needs of each cluster to enhance productivity, and promote geographic diversification of pulse production.
  • Procurement: Assured maximum procurement of Tur, Urad, and Masoor under Price Support Scheme (PSS) of PM-AASHA.
  • NAFED and NCCF will undertake 100% procurement in participating states for the next four years from farmers who register with these agencies and enter into agreements. 

About Chocolate Mahseer:

• Chocolate Mahseer or copper mahseer (Neolissochilus hexagonolepis) is a freshwater fish species.
• The fish species belonging to the genus Tor and Neolissocheilus under the family Cyprinidae are popularly known as ‘Mahseer’.
• It is known by the local name kha saw in Meghalaya.
• It was officially designated as state fish of Meghalaya and Sikkim.
• Distribution: It thrives in nearly all the major rivers and hill-streams of Meghalaya, Assam, Arunachal Pradesh, Sikkim, Manipur, Nagaland, Mizoram, and Tripura.
• Habitat: The species inhabits clear, fast flowing streams and rivers with stony, pebbly or rocky bottoms. It is considered an indicator of healthy river ecosystems.
• Threats: Its populations are in decline due to habitat degradation, overfishing and environmental changes
• Conservation Status
  • IUCN Red List: Near Threatened

About Exercise INDRA 2026:

• It is a bilateral exercise conducted between the Indian Navy and the Russian Federation Navy (RuFN).
• Since its inception in 2003, Exercise Indra has epitomised the long-term strategic relationship between the Indian and Russian navies.
• Phases: It will comprise engagements during the harbour phase followed by coordinated operational activities at sea.
• Focus: The exercise will include a range of professional interactions and maritime evolutions aimed at enhancing mutual understanding, operational coordination and interoperability between the participating navies.
• Participation: The participation of INS Sahyadri is in consonance with the Government of India’s vision of MAHASAGAR (Mutual and Holistic Advancement for Security and Growth Across Regions).

Why in news?

• The US has for years pressured India over its purchases of Russian crude oil, imposing penal tariffs and passing laws threatening up to 100% tariffs on major buyers of Russian energy.
• Washington’s argument: such purchases effectively fund Russia’s war in Ukraine.
• In a striking reversal, President Donald Trump has now announced a deal allowing Russia to supply diesel to the US and global markets — exposing a glaring contradiction in US policy, and strengthening India’s case for continuing its own energy choices.

What’s in Today’s Article?

• Why the US Needs Russian Diesel Now?
• Details of the Deal
• India’s Russian Oil Dependence
• The Core Contradiction — and India’s Opening

Why the US Needs Russian Diesel Now?

• Diesel’s Economic Importance: It powers long-haul trucking, agriculture, and construction — making price spikes politically sensitive and inflationary.
• The Immediate Trigger: Diesel prices in the US and Europe have surged, driven by constrained fuel movement through the Strait of Hormuz and attacks on Russia’s oil and gas infrastructure.
  • US diesel prices hit record levels of ~$6.5/gallon.
  • With US midterm elections approaching, the Trump administration faces pressure to show action on fuel prices.
• Sequence of Events
  • Trump had pressured Europe to release diesel stockpiles and even threatened a US diesel export ban.
  • Last week, the G7 agreed to release 100 million barrels of crude and petroleum products (including diesel) from emergency reserves.
  • Trump then reversed his export-restriction stance and announced the Russia diesel deal.

Details of the Deal

• According to Trump:
  • Russia will immediately supply 300,000+ tonnes of diesel to the US and other countries.
  • 500,000 tonnes more in November.
  • One million tonnes shortly after.
  • A further three million tonnes “within a short period”, depending on Russia’s refinery conditions.
  • The US issued a general licence, temporarily authorising transactions for Russian-origin diesel sale, delivery, and import until April 7 next year.
• Will it actually bring prices down? Experts are doubtful:
  • The additional volumes are far smaller than the global diesel supply disruption.
  • Constraints remain: Russia’s own export restrictions, Ukrainian drone strikes on its refineries, and tanker shortages.
  • The deal may ease short-term anxiety but is not a lasting fix.

India’s Russian Oil Dependence

• Russian oil made up nearly half of India’s oil imports in August 2026. This was not always the case.
• Much of the West began shunning Russian oil after its February 2022 invasion of Ukraine. This prompted Moscow to offer discounted crude, which India purchased.
• Imports fell after the US sanctioned Rosneft and Lukoil, as India sought a trade deal with the US (including scrapping a 25% penal tariff).
• By February 2026, India’s Russian crude imports had halved from its 2025 peak of over 2 million bpd — yet Russia still remained India’s largest crude source, at about one-fifth of total imports.
• Imports rose again as the West Asia conflict squeezed Strait of Hormuz supplies; the US even issued sanctions waivers to keep markets supplied.
• The legal squeeze: In September 2026, Trump signed the “Lindsey O. Graham Sanctioning Russia and Iran Act of 2026”, enabling up to 100% tariffs on countries (including India and China) buying Russian oil/gas — though the law lets the US President waive its provisions.

The Core Contradiction — and India’s Opening

• Trump’s diesel deal generates revenue for Moscow, exactly as India’s crude purchases do — undercutting Washington’s own stated rationale for punishing India.
• This gives India a strong diplomatic argument. India can cite this deal directly in consultations with the US over Russian oil sanctions and push for waivers under the Graham Act.
• The US’s likely counter-argument: It may frame its diesel licence as a response to exceptional market conditions, not a departure from its general Russia policy.
• But India can push back — as the world’s third-largest crude importer, with import dependency over 88%, India’s energy security needs are no less real than America’s.

Conclusion

Trump’s Russian diesel deal lays bare an uncomfortable truth: US sanctions on Russian energy have been applied selectively, bending whenever domestic political and economic pressures demand it. For India, this is more than an irony to point out — it is a concrete diplomatic lever.

As a nation far more dependent on energy imports than the US, India can now press Washington to judge its Russian oil purchases by the same standard it applies to itself: pragmatic necessity, not punitive politics.

Why in news?

While artificial intelligence (AI) dominates current cybersecurity concerns, a far bigger, longer-term threat is quietly emerging for the banking sector: quantum computing.

Financial institutions and regulators worldwide, including in India, have already begun preparing for this threat — years before it is expected to fully materialise.

What’s in Today’s Article?

• Current Cybersecurity Push in Indian Banking
• About Quantum Computing
• Why This Threatens Bank Encryption?
• Why Banks Can’t Wait?
• India’s Quantum-Safe Roadmap

Current Cybersecurity Push in Indian Banking

• Before quantum enters the picture, regulators have already stepped up conventional cyber preparedness:
  • The Reserve Bank of India (RBI) issued a new cybersecurity and technology-resilience framework for commercial banks in July 2026, covering IT governance, cyber-risk management, and incident response.
  • The Securities and Exchange Board of India (SEBI) introduced an IT Resilience Index in August 2026 for market infrastructure institutions, to measure robustness of critical IT systems and spot weaknesses early.

About Quantum Computing

• Traditional computers store data as a bit (value 0 or 1). Quantum computers use a qubit (quantum bit), which can exist as a combination of 0 and 1 — a property called superposition.
• Qubits also exhibit entanglement, where states of different qubits become closely correlated.
• Quantum algorithms exploit these properties to amplify correct answers and suppress wrong ones, giving quantum computers a massive computational edge for certain problems.
• It can solve in minutes or hours what classical computers would take millennia to complete.

Why This Threatens Bank Encryption?

• Modern cryptography relies on mathematical problems that are extremely hard for classical computers to solve. Some widely used public-key systems are:
  • RSA (Rivest–Shamir–Adleman): relies on difficulty of factoring large numbers.
  • Elliptic-curve cryptography: relies on difficulty of discrete-logarithm problems.
• India’s financial ecosystem is deeply digitised through UPI, Aadhaar, RTGS, and NEFT — all underpinned by such cryptography.
• The threat isn’t that quantum computers would directly hack a payment system. Instead, they could undermine the cryptographic building blocks used for authentication, secure communication, key exchange, and digital signatures across digital infrastructure.
• Experts explained: by 2029–2030, quantum computers could become powerful enough to decrypt historical encrypted data — a point often called the quantum deadline.

Why Banks Can’t Wait?

• The key reason for acting now is a threat called “Harvest Now, Decrypt Later” (HNDL):
  • Attackers can intercept and store encrypted data today, planning to decrypt it later once powerful quantum computers exist.
  • This makes long-term confidential data especially vulnerable.
  • As per the Digital Threat Report 2025–26 (by CERT-In), while full-scale quantum threats haven’t arrived, HNDL strategies are already active.
• The solution: Transition to Post-Quantum Cryptography (PQC) — encryption algorithms resistant to quantum attacks — before the threat fully emerges.
• Preparation involves:
  • Creating an inventory of cryptographic systems in use.
  • Identifying the most sensitive/critical data.
  • Testing quantum-resistant algorithms.
  • Working with technology vendors.
  • Building Crypto-agility — the ability to switch cryptographic standards without a complete system rebuild. This matters because bank infrastructure spans legacy systems, cloud platforms, third-party vendors, and payment networks.

How Imminent Is the Threat?

• India currently has only a handful of quantum computers, mostly under 10 qubits, developed by institutions like IISc Bengaluru and startups like QpiAI.
• India’s National Quantum Mission (launched 2023) aims to scale from 20–50 physical qubits initially to larger systems over time.
• Globally, NIST (US) has already finalised PQC standards; the G7 has a roadmap for financial-sector transition; the EU wants member states to begin transition by end-2026, with high-risk systems migrated by end-2030.

India’s Quantum-Safe Roadmap

• The Department of Science and Technology’s roadmap for banking/financial services/insurance envisages:
  • Foundational work by 2027;
  • Migration of high-priority systems by 2028; and
  • Full PQC adoption by 2029.
• RBI’s Quantum Secure and Adaptive Financial Ecosystem (Q-SAFE) expert committee is examining quantum’s implications for finance and recommending a roadmap.
• NITI Aayog’s 2025 roadmap for a quantum-powered economy identifies financial modelling, fraud detection, and encryption as key application areas.
• This creates a dual policy challenge for India: protecting digital infrastructure from the quantum threat while simultaneously building domestic quantum capabilities for economic gain.

Conclusion

Quantum computing represents a slow-building but potentially severe threat to the cryptographic backbone of digital finance — not because it will “hack” banks directly, but because it could eventually break the encryption securing decades of sensitive data.

The “Harvest Now, Decrypt Later” risk makes early action non-negotiable, which is why India, alongside global regulators, is already laying out phased roadmaps toward post-quantum cryptography.

The challenge ahead is as much about building domestic quantum capability as it is about defending against it.

Context:

• Property tax is the most important own revenue source for India’s municipal bodies and is critical for bridging the urban investment gap, since such investment depends heavily on municipal creditworthiness.
• Yet, India’s property tax performance remains poor. In this context, this article argues that technology alone cannot fix this — what’s needed is deeper structural reform.

The Scale of the Problem

• India’s cumulative property tax collection is just 0.15–0.2% of GDP.
• Compare this to 0.6% in middle-income countries and 0.3% in low-income countries — India trails even poorer economies.
• Multiple policy efforts — successive Finance Commissions, the Jawaharlal Nehru National Urban Renewal Mission (JNNURM), and the Atal Mission for Rejuvenation and Urban Transformation (AMRUT) — have pushed technology and process-based reforms.
• Yet outcomes remain sub-optimal.

What Recent Research Reveals?

• Various studies have explained why reforms haven’t worked.
  • One such study was a working paper on Chennai’s property tax, by Nobel Laureate Esther Duflo and co-authors.
• Key finding from these studies: Technology and process reforms will keep underperforming unless backed by structural reform.
  • Duflo’s Chennai study found municipal human resources are a critical determinant of tax outcomes — a municipality’s own tax assessors perform far better than assessors from outsourced firms.
  • Another study found two additional structural issues: irregular municipal elections and poor financial reporting practices, both of which hurt tax outcomes.

The Three Life Stages of Property Tax

• Property tax administration involves three sequential stages, each with its own structural weaknesses:
  • Enumeration (identifying properties and maintaining records)
    • GIS-based mapping using satellite imagery and drones is the popular tech solution.
    • But such mapping must be paired with physical inspections by municipal assessors, and repeated regularly.
    • Problem: Perennial staff shortages, skill gaps, and weak capacity-building in municipalities.
    • Outsourcing human resources is a limited substitute — municipal assessors carry institutional memory that outsourced staff lack.
  • Valuation and Tax Assessment
    • The common policy recommendation is capital valuation, where a property’s value is linked to its stamp duty-based ‘circle rate’, set and revised by the State revenue department.
    • But most municipalities instead use a base rate method (rupees per sq. ft per month), set by the municipality itself — and tax buoyancy depends on how often this base rate is revised.
    • Critical finding: In many cities, base rate revisions did not happen during periods without elected municipal councils.
    • Implication: There is a direct link between delayed municipal elections and stagnant tax revenue — since delayed elections are common across India, so is infrequent base-rate revision and weak tax buoyancy.
  • Billing and Collection
    • Recommendations include online collection systems and outsourcing collection to external vendors — but collection efficiency remains poor.
    • An even bigger concern: the absence of properly maintained financial accounts makes it difficult to even estimate collection efficiency reliably.

The Core Argument

• Technology and process fixes address symptoms, not root causes. Genuine improvement requires:
  • Strengthening municipal human resources — adequate, skilled, permanent staff rather than over-reliance on outsourcing.
  • Ensuring timely municipal elections, since elected councils are linked to regular base-rate revisions and better tax buoyancy.
  • Improving financial reporting and transparency, so that collection efficiency can be accurately measured and monitored.

Conclusion

• India’s property tax shortfall is not a failure of technology — GIS mapping, online payments, and digitised records exist, yet revenues stay flat.
• The real bottlenecks are structural: understaffed municipalities, irregular elections that stall tax revisions, and opaque financial records that make accountability impossible.
• Unless policy shifts from technical fixes to genuine municipal governance reform — staffing, electoral regularity, and financial transparency — India’s cities will continue to under-collect the one tax that is entirely theirs to strengthen.

Why in the News?

• The second death anniversary of former Delhi University professor G.N. Saibaba on October 12 has renewed debate over the Unlawful Activities (Prevention) Act (UAPA), particularly its stringent bail provisions, broad definitions of offences and implications for civil liberties.

What’s in Today’s Article?

• About UAPA (Overview, Concerns Regarding Application, Stringent Bail Conditions, Implications, Reform Priorities)

Overview of the UAPA

• The Unlawful Activities (Prevention) Act, 1967 is India's principal legislation for preventing unlawful activities and addressing terrorism-related offences.
• It provides the legal framework for action against activities considered threats to India's sovereignty, integrity and security.
• While national security is a legitimate state responsibility, the application of anti-terror legislation also raises questions concerning due process, individual liberty and safeguards against arbitrary detention.
• The central challenge is to ensure that the law effectively addresses genuine security threats without creating undue restrictions on constitutional freedoms.

Concerns Regarding the Application of UAPA

• Critics highlight several cases in which individuals accused under the UAPA spent extended periods in prison before their trials could begin or conclude.
• Prolonged incarceration without trial
  • Professor G.N. Saibaba, who was severely physically disabled, was arrested in 2014 on allegations of links with Maoists. A trial court convicted him in 2017 and sentenced him to life imprisonment.
  • The Bombay High Court acquitted him of all charges in 2024, after he had spent approximately a decade in prison. His health had deteriorated significantly, and he died soon after his release.
  • Such cases raise concerns about the consequences of lengthy pre-trial detention, particularly when judicial proceedings take years to progress.
• Broad and ambiguous legal provisions
  • Critics also identify the meaning of membership of an unlawful organisation as an example of ambiguity within the law.
  • Their argument is that broadly worded provisions can permit different interpretations of conduct, potentially extending their application beyond clearly established acts of violence.
  • Such ambiguity can increase the discretion available to investigating agencies and create uncertainty about the boundary between unlawful conduct and protected expression or association.

Stringent Bail Conditions and Judicial Interpretation

• The UAPA imposes stringent restrictions on bail. Under Section 43D(5), bail may be denied where the court finds reasonable grounds for believing that the accusations are prima facie true.
• Critics argue that this provision can make bail particularly difficult when proceedings are delayed and courts give substantial weight to the prosecution's case at the preliminary stage.
• They also highlight inconsistent judicial approaches to interpreting the law and assessing delays in trials. Different courts have taken different positions on the scrutiny required of prosecution material and on whether prolonged incarceration constitutes excessive delay.
• Also, they have raised concerns with respect to judicial decisions concerning the interpretation of membership and the definition of terrorism-related offences. These developments illustrate how judicial interpretation can substantially influence the practical scope of a criminal law.

Implications for Constitutional Governance

• The identified concerns have implications for several principles of India's constitutional and legal framework.
• Personal liberty: Article 21 protects life and personal liberty, subject to procedure established by law. Prolonged detention without timely trial raises questions about the effective protection of this right.
• Due process: Criminal proceedings must operate through fair legal procedures, with meaningful judicial scrutiny and safeguards against arbitrary action.
• Rule of law: Legal provisions should be sufficiently clear to enable consistent interpretation and limit arbitrary or excessive discretion.
• Judicial independence: Courts play a critical role in reviewing detention, interpreting statutory provisions and protecting individual rights.
• Balance between security and liberty: The State must address terrorism and threats to national security while ensuring that enforcement powers remain subject to legal and constitutional safeguards.

Reform Priorities

• Critics call for a fundamental reconsideration of the UAPA's provisions and their judicial application. The following priorities emerge from the analysis:

• Greater legal clarity: Ambiguous terms and broadly framed offences require clearer interpretation to reduce uncertainty and excessive discretion.
• Timely trials: Effective case management and adequate judicial capacity are important to prevent prolonged pre-trial detention.
• Consistent bail jurisprudence: Courts should apply coherent principles when evaluating prosecution evidence, bail applications and delays in proceedings.
• Meaningful judicial scrutiny: The application of stringent bail restrictions should remain subject to careful examination of the material placed before the court.
• Protection of civil liberties: Anti-terror legislation should be implemented in a manner consistent with constitutional rights and the rule of law.

Context:

• The global AI race is dominated by investments in advanced chips, data centres, computing infrastructure and frontier AI models.
• However, the economic benefits of Artificial Intelligence (AI) will depend not merely on generating intelligence but on deploying it at scale to solve practical problems.
• The World Bank’s World Development Report 2026 - ‘The Promise of Artificial Intelligence’ - highlights AI’s potential to sustain economic growth, improve productivity, strengthen public services and expand opportunities.
• For India, the priority should be to translate AI capabilities into widespread economic and social benefits rather than compete solely with global technology giants.

AI as an Engine of Economic Growth:

• The history of general-purpose technologies shows that substantial economic gains often accrue to downstream users who adopt technologies, adapt them to local conditions and diffuse them across the economy.
• India is well-positioned to benefit because of its rapid economic growth and experience in deploying digital technologies at population scale.
• Its Digital Public Infrastructure (DPI) demonstrates how technology, institutions and market incentives can reduce costs, expand access and encourage innovation.
• Therefore, India's AI strategy should focus on practical applications that improve productivity across agriculture, healthcare, education, businesses and public administration.

AI and Employment - Complementing Human Capabilities:

• The employment impact of AI is a major concern. Only 4.5% of existing jobs in low- and middle-income countries are highly exposed to automation by generative AI, compared with 14.2% in high-income countries.
• Meanwhile, 16.2% of jobs in low- and middle-income countries could experience meaningful productivity gains, compared with 18.7% in advanced economies.
• These estimates suggest that AI may complement rather than replace many workers in developing economies, although its impact will vary across occupations and sectors.
• Affordable, task-specific AI tools can -
  • Help farmers access agricultural advice and weather forecasts.
  • Assist health workers with diagnosis and disease screening.
  • Support teachers in improving learning outcomes.
  • Enhance business productivity and government administration.
  • Expand access to essential public services.

Major Challenges to AI-Led Development:

• Concentration of AI capabilities:
  • Advanced semiconductors, computing infrastructure, data, research talent and risk capital remain concentrated in a few firms and countries.
  • Excessive dependence on these providers may create technological vulnerabilities, restrict strategic autonomy and increase the risk of market dominance and technological lock-in.
• Inadequate supporting ecosystems:
  • AI's effectiveness depends on complementary investments in -
    • Reliable electricity and digital connectivity.
    • Affordable devices and computing resources.
    • Local-language datasets and relevant applications.
    • Digital literacy, technical skills and workforce reskilling.
    • Institutional capacity to evaluate, procure and regulate AI systems.
  • Without these foundations, technological progress may fail to generate development gains and could widen existing inequalities.

India's Emerging AI Applications:

• India has begun using AI to address practical challenges in key sectors.
  • Agriculture: Bharat VISTAAR, the government's digital initiative for agricultural information, aims to improve farmers' access to AI-enabled advisory services, including through multilingual applications.
  • Healthcare: Wadhwani AI's tuberculosis-screening tools demonstrate the potential of AI to support disease detection.
  • Public services: Locally adapted AI applications can improve weather forecasting, administrative efficiency and access to government services.
• The central challenge is to move beyond successful pilot projects and ensure that effective solutions are adopted by millions of people.

DPI - Lessons for AI Adoption:

• Platforms such as Aadhaar, the Unified Payments Interface (UPI), DigiLocker and emerging data-sharing systems provide shared digital infrastructure that reduces costs, enables interoperability and supports innovation.
• UPI is particularly instructive because its interoperable architecture promotes competition and reduces dependence on a single service provider.
• Similar principles should guide AI development and adoption -
  • Encourage open standards and interoperability.
  • Ensure data portability and technological flexibility.
  • Prevent excessive dependence on individual AI providers.
  • Promote competition and innovation.
• Emerging economies need not match the enormous investments made by global AI hyperscalers.
• Instead, India should build strategic capabilities through domestic research, Indian-language models, shared computing resources and a stronger deep-tech investment ecosystem.
• Initiatives such as IndiaAI; the Research, Development and Innovation (RDI) Fund; and the Anusandhan National Research Foundation (ANRF) can support this objective.

Way Forward:

• Design for scale: Every AI pilot should have a credible pathway to wider adoption, supported by sustainable financing, institutional ownership and integration with existing systems.
• Prioritise evidence-based evaluation: AI interventions should be tested under real-world conditions to assess their effectiveness, costs and development outcomes.
• Replicate success and learn from failure:
  • Successful solutions should be scaled across states and ministries, while ineffective interventions should be discontinued or redesigned.
  • Sharing evidence will prevent duplication and strengthen institutional learning.

Conclusion:

• India's AI opportunity lies not simply in adopting advanced technologies but in converting them into economy-wide productivity gains and inclusive development.
• A strategy centred on large-scale deployment, DPI, evidence-based policymaking and domestic capabilities can maximise AI's economic impact while ensuring that its benefits are distributed more equitably.