Madhavi Repe, Dr. Nilakshi Rajule, Vandana Katarwar, Ankita Bombatkar
In response to the growing demand for secure and transparent digital elections, this paper presents a blockchain based Smart Election System that leverages advanced cryptographic and artificial intelligence techniques to ensure privacy, scalability, and verifiability. The proposed system integrates multi-factor authentication, Zero-Knowledge Proofs (ZKPs), smart contracts, and a sharded blockchain ledger to enable real-time, tamper-proof voting. Additionally, an Artificial intelligence based anomaly detection module monitors voting behaviour to flag suspicious patterns.Experimental evaluation demonstrates that the system achieves an average vote transaction latency of 1100ms with sharding, compared to 2800ms without it. The throughput increases from 130 to 220 votes/sec when sharding is enabled. ZKP integration ensures privacy at the cost of a moderate increase in validation time from 130ms to 230ms. The anomaly detection model, based on supervised learning, attained 92% precision, 88% recall, and an F1-score of 90%, ensuring proactive fraud detection. These results confirm the system’s effectiveness in delivering a smart scalable, private, and trustworthy e-voting platform suitable for national and institutional elections.
As smart cities continue to evolve through the integration of IoT, AI, and big data analytics, the complexity and scale of cybersecurity challenges have intensified. This chapter examines key vulnerabilities ranging from data privacy breaches to cyber-physical system attacks and highlights the critical role of modern cryptographic technologies in addressing these risks. Techniques such as encryption, blockchain, PKI, homomorphic encryption, zero-knowledge proofs, and quantum cryptography are analyzed for their potential to strengthen smart city infrastructures. Drawing on recent case studies and emerging research, we further explore future directions, including post-quantum security and AI-driven cybersecurity frameworks. The findings of this chapter suggest that strategically embedding cryptographic solutions is essential for building secure, resilient, and citizen-centered smart cities capable of withstanding both current and emerging cyber threats.
Dr.E. Gnanaprasuna, B. Arun Kumar, Dr. Avula Sreenivasulu, T. Navaneetha
A growing number of financial institutions are showing interest in Cryptocurrency, prompting a need to understand its role in the current financial system. This article, using a narrative literature review, highlights both the benefits and drawbacks of Cryptocurrency adoption. Key concerns include security risks, privacy issues, price volatility, lack of regulatory oversight, potential for criminal misuse, high energy consumption, and governmental restrictions. Despite early resistance, cryptocurrencies like Bitcoin and Ether have gained legitimacy, especially among corporations. However, environmental concerns remain, as crypto mining consumes vast energy, contributing to carbon emissions and climate change. Using data from 2013 to 2024, the study examines how publicly traded U.S. companies account for Cryptocurrency holdings. It finds that while corporate adoption is growing, the landscape lacks transparency and standardized reporting norms. Companies differ in how they report crypto assets, with a shift toward treating them as indefinite-lived intangible assets over time. Reporting practices vary in terms of fair value assessments and impairment testing assumptions. These inconsistencies highlight the challenges in understanding corporate crypto exposure. This study offers a concise overview for scholars and practitioners, shedding light on the evolving intersection of Cryptocurrency and mainstream finance.
A lack of data security and interoperability are significant challenges in low-carbon building design due to the involvement of numerous architects, engineers, and carbon auditors. This study proposes a novel framework that integrates blockchain, building information modelling (BIM), and life cycle assessment (LCA) to enhance data management and decision-making for low-carbon building design. Blockchain, as a distributed ledger, ensures data security by maintaining an immutable record of architectural design changes, energy system configurations, and carbon footprints. BIM visualises all the design information in a three-dimensional model to ensure real-time updates of energy and carbon performance. LCA assesses the trade-off between embodied carbon and operating carbon emissions across a building’s life span, optimising architectural and energy system design decisions. The proposed framework establishes a secure and transparent workflow by integrating blockchain, BIM, and LCA into an iterative design process. Smart contracts facilitate the automatic verification of design parameters, enabling architects and engineers to adjust their designs when carbon footprint targets and energy-saving requirements are unmet. Additionally, the framework incorporates a database of future weather profiles, material properties, and inventory information to support accurate and informed decision-making. This study enhances data security, improves interoperability and supports the iterative refinement of low-carbon building designs. The framework was validated on an industrial building project, demonstrating its effectiveness in designing low-carbon buildings and its potential to contribute to global net-zero ambitions. By offering a structured approach to integrating blockchain, BIM, and LCA, this study offers valuable insights for practitioners and researchers in the architecture, engineering, and construction industries.
This paper studies the practical aspects of adding zero-knowledge proofs of vote correctness to Internet voting, specifically to the IVXV system used in Estonia. We discuss various available alternatives and present a concrete instantiation based on Bulletproofs together with implementation details and benchmarking results. As IVXV currently uses the ElGamal cryptosystem with a 3072-bit prime modulus for vote encryption, but Bulletproofs work most efficiently on elliptic curves, a group switching solution is also implemented and benchmarked. Despite all the extra work required, our solution is very performant and well capable of sustaining the load of votes, even during peak vote submission periods.
This study investigates the evolving landscape of scholarly research on nature finance and the financialization of biodiversity through a comprehensive bibliometric analysis of literature indexed in Scopus from 2000 to 2025. Using VOSviewer, we mapped co-occurring keywords, author networks, temporal trends, and country collaborations to identify dominant themes, emerging topics, and influential contributors. The findings reveal a conceptual transition from traditional ecosystem service valuation toward market-based conservation instruments, including conservation finance, carbon markets, and blockchain-based solutions. The thematic clusters emphasize the increasing intersection between finance, sustainability, and biodiversity policy, with recent trends showing a surge in decentralized finance applications for environmental assets. Notably, the United Kingdom and United States dominate collaborative networks, while Asia-Pacific regions exhibit growing engagement in the field. This study contributes to the theoretical understanding of biodiversity financialization and offers practical insights for policymakers, financial institutions, and environmental stakeholders aiming to design inclusive and effective biodiversity finance strategies. It also identifies gaps for future interdisciplinary research that bridges ecological science with financial innovation.
Open access
Forest Management and Policy
Conservation, Biodiversity, and Resource Management
This paper examines the interconnection and wavelet coherence between the green cryptocurrency market and the green conventional market, utilizing daily data. The research period covers 1 July 2020 to 30 September 2024. Employing the time-varying parametric vector autoregression (TVP-VAR) model and wavelet coherence analysis, we capture both short- and long-term spillovers across markets. The results show that cryptocurrencies, particularly Binance and Litecoin, act as dominant transmitters of volatility and return shocks, while green conventional indices function mainly as receivers with strong self-dependence. Spillover intensity is highly time-varying, with peaks during periods of systemic stress, particularly during the COVID-19 pandemic, and troughs indicating diversification opportunities. These findings advance the literature on systemic risk and portfolio design by showing that crypto assets can simultaneously amplify vulnerabilities and enhance diversification when combined with green finance instruments. For policy, the results highlight the need for regulatory frameworks that integrate sustainability taxonomies, mandate environmental disclosures for digital assets, and incentivize energy-efficient blockchain adoption to align crypto markets with sustainable finance objectives. This research enhances our understanding of the interrelationship between green investments and cryptocurrencies, providing valuable insights for investors and policymakers on risk management and diversification strategies in an increasingly sustainable financial landscape.
Africa’s growing water stress and energy access challenges necessitate sustainable wastewater treatment solutions. This review critically examines three emerging approaches: solar-based, membrane-based, and hybrid solar-membrane systems, across the African continent. Solar technologies, including solar water disinfection, photocatalysis, and advanced oxidation processes, demonstrate significant potential in sun-rich regions, achieving more than 90% pathogen and contaminant removal in decentralized settings. Membrane bioreactors (MBRs) and advanced filtration systems show robust performance in industrial applications, with 95%–99% pollutant rejection, though their energy demands remain a significant constraint. Hybrid solar-membrane systems synergize these advantages, as evidenced by case studies in Kenya (solar-MBR for aquaculture, 40% energy autonomy) and Namibia (solar-powered desalination, 99.7% salt rejection). Despite technological promise, adoption barriers persist, including high capital costs, technical capacity gaps, and policy fragmentation. This review analyze 32 implementations across 17 African countries, evaluating performance metrics, scalability, and socioeconomic viability. Key findings highlight the cost-effectiveness and sustainability gains from waste-derived membranes (e.g., geopolymers, recycled plastics, oasis waste), nanoparticle-enhanced photocatalysts (TiO 2 /MnO 2 ), and modular system designs tailored to off-grid and resource-limited settings. The review concludes with policy recommendations to accelerate deployment. These include fostering decentralized systems in peri-urban and rural areas, promoting public-private partnerships to finance infrastructure, and supporting localized research to adapt technologies to diverse hydroclimatic and socio-economic conditions. Together, these approaches offer a viable pathway toward achieving SDG 6 and SDG 7 in Africa.
Md Mehedi Hasan Emon, Md. Mazid-Ul-Haque, Most. Sharmin Ara Chowdhury, Kh. Mustafizur Rahman
This chapter explores the critical role of advanced cryptographic technologies in securing smart city applications across domains such as e-health, e-commerce, and e-banking. As urban environments become increasingly digitized, safeguarding sensitive data, ensuring transaction integrity, and protecting user privacy emerge as paramount challenges. The chapter explores a spectrum of cryptographic solutions, including blockchain, homomorphic encryption, zero-knowledge proofs, and quantum cryptography, that address these complexities. Through detailed analysis and real-world case studies, it highlights practical implementations and emerging trends that reinforce trust and resilience in smart city infrastructures. Moreover, the chapter discusses the policy and ethical dimensions necessary to balance security with usability and transparency. Finally, it provides a comprehensive framework for integrating cryptographic safeguards into the evolving digital fabric of smart cities, ensuring secure, scalable, and citizen-centric urban services.
Ronald Ravinesh Kumar, Hossein Ghanbari, Peter Josef Stauvermann
The market for digital assets, and more specifically cryptocurrencies, is growing, although their adoption in small island countries remains absent. This paper explores the potential benefits of integrating cryptocurrencies into portfolios alongside stocks, with a focus on Fiji’s stock market. This is the first study on a small market like Fiji, which emphasizes the role of cryptocurrencies in portfolio management. We analyze the outcomes (returns and risks) of combining cryptocurrencies with stocks using 12 different techniques. We use monthly stock returns data of 18 companies listed on the South Pacific Stock Exchange from Aug-2019 to Jun-2025 (71 months) and nine cryptocurrencies from Sept-2019 to Jun-2025 (70 months). Our main analysis shows that only one cryptocurrency, albeit with a small exposure, consistently appears in the stock-cryptocurrency portfolios in the 12 methods. Using the return-to-risk ratio across methods as a guide, we find that the stocks-cryptocurrencies portfolio based on EQW, MinVar, MaxSharpe, MinSemVar, MaxDiv, MaxDeCorr, MaxRMD, and MaxASR offers better outcomes than the stock-only portfolios. Using high returns as a guide, we find that six out of 12 methods (EQW, MaxSharpe, MaxSort, MaxCEQ, MaxOmega, and MaxUDVol) support the stocks-cryptocurrencies portfolios. Portfolios satisfying both conditions (high return-risk ratio and high return) are supported by the EQW and MaxSharpe portfolios. The consistency of assets in both stock and stock−cryptocurrency portfolios is further confirmed by 24-month out-of-sample forecasts and Monte Carlo simulations, although the latter supports small exposures in two out of the nine cryptocurrencies. Based on the results, we conclude that a small exposure to certain cryptocurrencies can strengthen diversification and improve potential returns.
Maria Nuțu, Giorgi Akhalaia, Răzvan Bocu, Maksim Iavich
Commitment schemes represent foundational cryptographic primitives enabling secure verification protocols across diverse applications, from blockchain systems to zero-knowledge proofs. This paper presents a systematic survey of vector, polynomial, and functional commitment schemes, analyzing their evolution from classical constructions to post-quantum secure alternatives. We examine the strengths and limitations of RSA-based, Diffie–Hellman, and lattice-based approaches, highlighting the critical shift toward quantum-resistant designs necessitated by emerging computational threats. The survey reveals that while lattice-based schemes (particularly those using the Short Integer Solution problem) offer promising security guarantees, they face practical challenges in proof size and verification efficiency. Functional commitments emerge as a powerful generalization, though their adoption is constrained by computational overhead and setup requirements. Key findings identify persistent gaps in adaptive security, composability, and real-world deployment, while proposed solutions emphasize optimization techniques and hybrid approaches. By synthesizing over 90 research works, this paper provides both a comprehensive reference for cryptographic researchers and a roadmap for future developments in commitment schemes, particularly in addressing the urgent demands of post-quantum cryptography and decentralized systems.
• Comprehensive review of RH-specific continuous pyrolysis technologies and performance • Achieves up to 45% biochar yield and >70% thermal efficiency under optimal conditions • Analyzes AI-driven control and modular reactor designs for decentralized deployment • Reports 1.8–2.2 kg CO₂-eq/kg biochar sequestration with ROI under 3.5 years • Proposes hybrid heating and MRV-linked carbon credits for scalable climate solutions This review consolidates recent advances in continuous pyrolysis of rice husk (RH), emphasizing reactor engineering, digital process regulation, and carbon finance opportunities within a circular bioeconomy framework. RH, produced in quantities exceeding 150 million tons annually, is characterized by high silica (15–20%), moderate lignin (∼25%), and appreciable fixed carbon, creating both design challenges and opportunities for biochar production. Unlike general biomass studies, this work focuses exclusively on continuous reactor systems, screw, rotary kiln, auger, and fluidized bed, evaluated under optimized conditions (∼500–550°C, 20 min residence time, and 50°C/min heating rate). These systems typically yield 35–43% biochar with surface areas above 300 m²/g and carbon concentrations exceeding 75%. Life cycle assessments indicate net sequestration of 1.8–2.2 kg CO₂-eq per kilogram of biochar, while techno-economic analyses estimate production costs at $120–$180 per ton with return-on-investment periods of 2.5–3.5 years. Future developments are likely to focus on hybrid heating strategies (such as microwave or solar-assisted), neural network–based predictive control for real-time optimization, and blockchain-enabled monitoring, reporting, and verification (MRV) platforms to support carbon credit trading. By linking RH pyrolysis performance with policy frameworks, market mechanisms, and advanced process regulation, this review provides actionable insights for researchers, technology developers, and policymakers pursuing scalable, climate-aligned solutions.
Facial recognition technology has been recognized as a powerful tool for enhancing security and authentication, especially in transaction systems. However, serious risks—like data breaches and unauthorized access—are presented by traditional methods that store biometric data in centralized databases. To address these concerns, a decentralized facial biometric system built on blockchain and smart contracts has been developed. User privacy and security are prioritized by this approach. Instead of being reliant on a central database, transactions are securely verified by our system through a comparison of users’ facial biometrics with data that has already been stored in a distributed, tamper-resistant way. By distributing the data across a decentralized network, the system minimizes the risk of unauthorized access or data breaches. This setup not only strengthens security but also builds trust with users by protecting their privacy—while still delivering consistent and reliable performance.
Arif Perdana, W. Eric Lee, Chu Yeong Lim, Gary Pan · 5 authors
The characteristics of cryptocurrencies, such as decentralization, fluctuation, and anonymity, have often raised ethical concerns about their impact on privacy, cybersecurity, prosperity, and liberty. With an increased awareness of the potential consequences, it is essential to address how, in the face of ethical challenges, and together with one’s unique cultural values, various influences may affect the issue of trust toward cryptocurrencies. From an inter-country perspective, this study examines how ethical elements and cultural dimensions can interact to influence trust. In particular, we examine the ethical and cultural aspects of trust formation among cryptocurrencies’ users in the three predominant countries of Germany, China, and the United States. We use configurational analysis to investigate the relationships among ethics, culture, and trust in cryptocurrencies across these countries. The results of this study contribute to a greater global understanding of how different configurations of ethics and culture can influence one’s trust in cryptocurrencies.
Accreditation has historically played a central role in securities regulation, seeking to balance investor protection, market access, and capital formation. Traditionally, regulatory frameworks have relied on wealth or income thresholds as proxies for investor sophistication, premised on the assumption that individuals with greater financial resources are better equipped to manage risk and obtain professional advice. However, in rapidly evolving crypto-asset markets, these wealth-based criteria have become increasingly misaligned with market realities. Such thresholds frequently exclude technically proficient but less affluent participants, thereby perpetuating inequality and conflicting with the inclusive ethos of digital finance. Moreover, these criteria have failed to prevent significant losses among wealthy accredited investors, as evidenced by the collapses of Terra-Luna, Three Arrows Capital, and FTX. Competence-based frameworks are still underdeveloped, unevenly applied, and can become overly formal, while traditional disclosure rules do not fully address the technical and behavioral challenges of decentralized finance. This article takes a critical look at accreditation in crypto-asset markets, drawing on legal, empirical, and normative analysis. By comparing the United States, European Union, Singapore, and Russia, and examining cases like the ICO boom, Singapore’s regulatory sandboxes, and the Terra-Luna and FTX collapses, the article shows that wealth-based accreditation falls short in fairness and effectiveness. It proposes a hybrid approach that combines competence assessments, crypto-specific disclosure, prudential safeguards, regulatory sandboxes, and international cooperation. This article contends that reforming accreditation constitutes a fundamental transformation in the approach to investor protection, advancing principles of fairness, legitimacy, and systemic robustness. By introducing a hybrid framework grounded in fairness and empirical evidence, the article contributes to policy discourse and informs scholarly understanding of the evolution of financial regulation in the context of digital innovation.
Purpose: Enterprise Resource Planning (ERP) systems, such as SAP (Systems, Applications, and Products in Data Processing), are critical to modern enterprises, enabling the integration of core business functions and the management of essential data. Ensuring their availability, reliability, and adaptability is paramount, as disruptions can result in significant operational and financial consequences. Traditional Knowledge Management (KM) approaches emphasize the preservation of ERP-related knowledge but often lack responsiveness to emergent risks. This study introduces a novel framework grounded in the concept of antifragility—where systems grow stronger under stress—by simulating disruptions to enable continuous knowledge evolution and system adaptation. Methodology: A mixed-methods research design combines simulation-based inquiry with Design Science Research (DSR) to investigate antifragile KM within ERP environments. Artificial Intelligence (AI) tools are integrated into the KM system to analyse ERP failures, generate runbooks, and proactively manage recovery knowledge. Controlled simulations of kernel upgrades and failure scenarios—modelled on ITIL 4 incident typologies—serve as structured stressors to expose vulnerabilities. Lightweight LLMs, Retrieval-Augmented Generation (RAG) pipelines, and semantic search tools are employed to codify procedural knowledge and enhance the responsiveness of ERP operations. Findings: The results demonstrate that embedding antifragile principles into ERP KM improves organizational learning, responsiveness, and recovery capabilities. Transitioning from static knowledge repositories to dynamic, AI-enabled systems allows for autonomous decision-making, decentralized knowledge flow, and adaptive documentation. Each disruption becomes a learning event, reinforcing the resilience and self-improvement of the ERP knowledge ecosystem. Implications: Empirical insights suggest that AI-driven antifragile KM transforms ERP disruptions into opportunities for growth, rather than threats to stability. The proposed framework supports the development of systems that not only recover from failure but also become progressively more robust and adaptive through structured experimentation and continuous learning.
The objective of this research was to analyze the impact of organizational culture on human talent management within the Decentralized Autonomous Government of Chilla Canton. A mixed-methods approach with a non-experimental, descriptive, and correlational design was used. For data collection, surveys were administered to 85 public servants from different administrative areas, and the instrument was validated using Cronbach’s Alpha coefficient, reaching a value of 0.994, ensuring high reliability. The results showed a significant positive correlation between organizational culture and human talent management, with a coefficient of 0.992. Each specific dimension analyzed—such as internal communication, organizational identity, training processes, and performance evaluation—showed coefficients above 0.95, which demonstrated the strength of the link between these factors. A solid organizational culture was observed to promote motivation, commitment, and staff retention, favoring a more efficient work environment. In conclusion, the study confirmed that strengthening organizational culture contributes to optimizing human talent management at the institutional level and revealed that organizational practices aligned with institutional values lead to improvements in performance, organizational climate, and staff satisfaction, which are key aspects for the sustainability of public management.
Substandard medicines in Nepal represent an under-documented yet critical threat to universal health coverage (UHC) and patient safety, disproportionately impacting marginalized communities. This opinion piece seeks to illuminate the prevalence, drivers, and far-reaching consequences of compromised pharmaceuticals, drawing on both local and global evidence. This paper offers pragmatic strategies to strengthen regulatory capacity and accountability by spotlighting ethical imperatives and systemic gaps. Bridging best practices from international frameworks with Nepal's unique context, I aim to catalyze policy discourse, cultivate public awareness, and spur multi-sectoral collaboration. Ultimately, the goal is to foster equitable and high-quality healthcare for all, reinforcing the moral imperative of safeguarding the integrity of Nepal's medicine supply.Substandard medicines are a pressing, under-recognized public health crisis in Nepal. Despite expanded healthcare access, compromised pharmaceuticals undermine patient well-being and public trust (1,2). The World Health Organization (WHO) estimates that at least one in ten medicines in low-and middle-income countries (LMICs) is substandard or falsified (3). In Africa, reports indicate up to 18.7% of sampled pharmaceuticals are compromised (4). This global issue is significantly influenced by two of the world's major suppliers of medicine, both domestically and internationally: India and China (5). According to estimates from India's Health Ministry, 5% of the nation's medicines are counterfeit and 0.3% are spurious, with one study suggesting that 75% of counterfeit medicines supplied globally originate in India (6). While recent, precise prevalence data for counterfeit drugs from China is not readily available, its role as a global manufacturing powerhouse is undisputed; for example, the country produces approximately 120 billion aspirin tablets annually for the North American market alone (7). A 2024 literature review highlights the historical scale of the issue, noting that 31% of the world's falsified and counterfeit medications are produced in China and Hong Kong (8). This geopolitical context is critically important for Nepal. The country's porous borders with these major pharmaceutical producers (9), combined with its own under-regulated supply chains, significantly heighten its susceptibility to the circulation of substandard drugs (10).A Nepal Health Research Council (NHRC) study found that 15.16% of 244 tested medicine batches failed pharmacopeial standards (11). Alarmingly, 62.16% of these were government-supplied. Compromised products included essential antibiotics, analgesics, and iron supplements, with failures in dissolution, assay, fill volume, and sterility. A 2010-2020 review of drug recall notices in Nepal revealed a surge in recalled products, most frequently antimicrobials (2). These findings indicate an ethical breach: public health facilities primarily serve the underprivileged, disproportionately imposing the burden of substandard medicines on them-a direct affront to the principle of justice (12). Patients, often unaware of compromised drug quality due to identical appearance, are denied meaningful informed consent. This erodes trust in the healthcare system and fuels antimicrobial resistance, a global health security threat with severe implications (3).Limited regulatory capacity exacerbates these dangers. In the Nepalese context, chronic under-resourcing of the Department of Drug Administration (DDA) and the National Medicines Laboratory hampers rapid testing and enforcement (13,14). Testing delays can extend for months, allowing compromised medications to circulate (15). While decentralizing drug procurement to local governments was intended to improve responsiveness, this policy has inadvertently weakened quality control due to a lack of local testing facilities and specialized personnel (14).Nepal's crisis of substandard medicines undermines human rights and core ethical principles.Tolerating this compromise of patient safety is incompatible with universal health coverage (UHC) (16). In Nepal, where a significant portion of the population relies on public health facilities for essential medicines, the prevalence of substandard drugs, especially in public health facilities (17), directly undermines the core tenets of UHC. Specifically, it violates the principle of access to quality healthcare: even if services are nominally affordable or free, receiving ineffective or harmful medication means that true, effective healthcare is not being delivered. Furthermore, the consequences of substandard medicines -prolonged illness, treatment failure, or adverse drug reactions -often lead to increased financial hardship for patients who may require further treatment, hospitalization, or experience loss of income due to illness. This directly contradicts the UHC goal of protecting people from financial risks associated with healthcare (18). This creates a two-tiered system, where those with resources can seek higher-quality care in the private sector, while the most vulnerable are left exposed to potentially dangerous treatments. Addressing this inequity and ensuring the integrity of the medicine supply is not just a matter of policy but a fundamental requirement for social justice. Success requires sustained political commitment, collaboration across sectors, and a steadfast focus on the public interest. Nepal must act decisively to eliminate substandard medicines and ensure equitable, high-quality healthcare for every citizen. This is not merely a matter of improving healthcare statistics; it is about upholding the fundamental dignity and rights of every citizen of Nepal.To address this crisis comprehensively, I argue that Nepal must move beyond isolated interventions and adopt a multi-pronged, systemic approach grounded in international best practices and adapted to the local context. The solution to the challenge of substandard medicines is complex, requiring a foundational shift from reactive detection to proactive prevention and quality assurance throughout the entire supply chain.First, the cornerstone of any effective strategy must be the robust implementation of a national quality assurance framework based on established WHO principles (19). This involves the mandatory adoption and enforcement of Good Manufacturing Practices (GMP) for domestic producers, ensuring that quality is built into products from the outset (20).Critically, this must be complemented by the nationwide implementation of Good Storage Practices (GSP) and Good Distribution Practices (GDP), which are presently lacking in Nepal (2). As detailed in WHO guidelines, this requires establishing a comprehensive Quality Management System that governs every stage of the supply chain, from procurement to delivery. This includes temperature-controlled storage and transport, proper documentation to ensure traceability, and rigorous training for all personnel involved (21,22). The goal is to create a secure, transparent, and controlled environment where opportunities for degradation or the introduction of falsified products are minimized.Second, this preventative framework must be supported by strengthening practices at the point of care through the enforcement of Good Pharmacy Practices (GPP). While pharmacistled detection of visibly substandard medicines is challenging and should not be the primary line of defense, pharmacists are integral to maintaining quality assurance (23). The US Agency for International Development (USAID) funded Medicines, Technologies, and Pharmaceutical Services (MTaPS) program has already highlighted the significant impact of GPP implementation on product quality and patient safety in Nepal (24). The urgency of this is underscored by recent local evidence from the Supervision, Performance Assessment, and Recognition Strategy (SPARS) pilot. The baseline assessment from the SPARS pilot, conducted in 2022 across 284 health facilities, revealed alarmingly poor medicines management practices, with an overall median score of only 34% across key performance indicators. Particularly low scores in domains such as storage management and stock management highlight critical, systemic gaps that a robust GPP framework is precisely designed to address (25). Therefore, a renewed focus on GPP-including proper storage, inventory management using the First-Expired-First-Out (FEFO) principle, and patient counselling (26,27)-is not merely a recommendation but an evidence-based necessity to safeguard medicine quality at the final stage of the supply chain.Third, a fundamental overhaul of the national regulatory body is imperative. While establishing a new, fully autonomous commission with civil society oversight represents an ideal long-term goal, a more pragmatic and immediate strategy is to empower the existing Department of Drug Administration (DDA). Given Nepal's resource constraints, strengthening the current regulatory infrastructure is a more feasible first step. Following successful models from other nations, such as the autonomous South African Health Products Regulatory Authority (SAHPRA) (28), granting the DDA greater operational and financial autonomy would be transformative. An empowered DDA could then engage in the kind of international collaboration essential for modern pharmacovigilance, such as the recent Memorandum of Understanding between SAHPRA and Australia's Therapeutic Goods Administration (TGA) to share regulatory information and expertise (29). Recent progress within Nepal indicates a readiness for such advancement; for instance, with support from USAID MTaPS, the DDA has begun modernizing its document management system by installing secure, access-controlled repositories to increase efficiency and security (30).While these foundational improvements are commendable, they must be viewed as the first steps in a much longer journey. Full regulatory maturity requires sustained investment to build upon these gains. This must include a significant increase in the number of trained inspectors and a shift towards a risk-based inspection model that prioritizes systematic laboratory testing of products from importers and wholesalers before they enter the market, thereby ensuring quality at the source rather than attempting to recall products that have already been dispensed.Finally, these systemic and regulatory reforms should be amplified by leveraging modern technology and strengthening post-market surveillance. A vital component underpinning all these reforms is compliance with Good Practice (GxP) principles. GxP is an acronym for a collection of quality guidelines and regulations designed to ensure that products within heavily regulated industries, such as pharmaceuticals, are consistently safe, effective, and fit for their intended use (31). This framework is not a single standard but an ecosystem of practices-including GMP, GSP, and GPP-that collectively safeguard product integrity.While technology is not a panacea, rigorous track-and-trace systems-using technologies like blockchain or simple 2D barcoding-offer a powerful tool for enforcing GxP compliance and achieving end-to-end visibility. This enables regulators to verify authenticity and rapidly identify diversions in the supply chain (32,33). Such systems, proven to be cost-effective in settings like Bangladesh (34), would support the broader GxP framework (31) and provide crucial data for the empowered DDA. Within this enhanced surveillance system, pharmacists, supported by legally protected reporting mechanisms, become vital nodes for reporting suspected adverse events or quality issues, thereby creating a feedback loop that strengthens the entire regulatory ecosystem (35).The integrity of a nation's medicine supply is a direct reflection of its commitment to health equity and social justice. For Nepal, the continued presence of substandard medicines in the supply chain represents a fundamental contradiction to its goal of achieving universal health coverage. The systemic reforms proposed-implementing a robust GxP framework, empowering an autonomous regulator, and leveraging technology for surveillance-are not merely technical exercises; they are essential acts of building trust with the nation's most vulnerable citizens and affirming their right to safe, effective healthcare. Moving forward, the challenge is not one of awareness, but of political will and sustained action. Ensuring the quality of every pill and vial is not just a matter of public health policy-it is a fundamental test of Nepal's promise of equitable healthcare for all.
Raphaël Bentegeac, Bastien Le Guellec, Grégory Kuchcinski, Philippe Amouyel · 5 authors
Abstract Background Chatbots have demonstrated promising capabilities in medicine, scoring passing grades for board examinations across various specialties. However, their tendency to express high levels of confidence in their responses, even when incorrect, poses a limitation to their utility in clinical settings. Objective The aim of the study is to examine whether token probabilities outperform chatbots’ expressed confidence levels in predicting the accuracy of their responses to medical questions. Methods In total, 9 large language models, comprising both commercial (GPT-3.5, GPT-4, and GPT-4o) and open source (Llama 3.1-8b, Llama 3.1-70b, Phi-3-Mini, Phi-3-Medium, Gemma 2-9b, and Gemma 2-27b), were prompted to respond to a set of 2522 questions from the United States Medical Licensing Examination (MedQA database). Additionally, the models rated their confidence from 0 to 100, and the token probability of each response was extracted. The models’ success rates were measured, and the predictive performances of both expressed confidence and response token probability in predicting response accuracy were evaluated using area under the receiver operating characteristic curves (AUROCs), adapted calibration error, and Brier score. Sensitivity analyses were conducted using additional questions sourced from other databases in English (MedMCQA: n=2797), Chinese (MedQA Mainland China: n=3413 and Taiwan: n=2808), and French (FrMedMCQA: n=1079), different prompting strategies, and temperature settings. Results Overall, mean accuracy ranged from 56.5% (95% CI 54.6‐58.5) for Phi-3-Mini to 89% (95% CI 87.7‐90.2) for GPT-4o. Across the United States Medical Licensing Examination questions, all chatbots consistently expressed high levels of confidence in their responses (ranging from 90, 95% CI 90-90 for Llama 3.1-70b to 100, 95% CI 100-100 for GPT-3.5). However, expressed confidence failed to predict response accuracy (AUROC ranging from 0.52, 95% CI 0.50‐0.53 for Phi-3-Mini to 0.68, 95% CI 0.65‐0.71 for GPT-4o). In contrast, the response token probability consistently outperformed expressed confidence for predicting response accuracy (AUROCs ranging from 0.71, 95% CI 0.69‐0.73 for Phi-3-Mini to 0.87, 95% CI 0.85‐0.89 for GPT-4o; all P Conclusions Due to the limited capacity of chatbots to accurately evaluate their confidence when responding to medical queries, clinicians and patients should abstain from relying on their self-rated certainty. Instead, token probabilities emerge as a promising and easily accessible alternative for gauging the inner doubts of these models.
In recent times., the accelerated growth of data has established big data analytics as an integral part of decision making in various industries., including healthcare., finance., manufacturing., retail etc. With the rise of big data., cloud computing., the relatively recent trend of using remote servers to hold and process data., has become a powerful tool for managing large datasets., providing storage and computational capabilities that are scalable., economical., and also elastic. But., when data is getting complex and distributed., security., privacy and data integrity have emerged as major concerns. The inherent features of blockchain technology like decentralization., immutability., and transparency can serve as a revolutionary alternative to tackle these challenges., while improving the efficiency and trustworthiness of big data analytics based on cloud. Data integrity., tampering prevention., and transparency-based auditing mechanisms help to secure data on cloud systems., and blockchain can improve these aspects. Additionally., the distributed nature of blockchain makes it possible to securely share data across different organizations without sacrificing privacy., which is especially important in industries like healthcare and finance. In addition., incorporating blockchain technology enables efficient tracking of data provenance., guaranteeing the verifiability of data origins and transformations., thereby enhancing trust and transparency. Blockchain has applied the security enhancement of cloud-based big data analytics platforms., which can also improve processing efficiency. Similarly., various consensus mechanisms used by blockchain i.e.., Proof of Work., Proof of Stake etc.., aid in cutting down the amount of time and resources required to validate and authenticate data in real-time., thus making a faster yet more secure processing time possible. Moreover., self-executing contracts (smart contracts) define terms that are directly built into the blockchain., and can automate data workflows and decisions., thus improving efficiencies. By ushering in new efficiencies that could sharply trim operational budgets and accelerate data- based decision-making across an array of sectors., these abilities hold immense potential.
The ever-growing dependency on blockchain technology to secure e-evidence in a forensic investigation will involve building architecture that is intrinsically tamper-proof and at the same time optimized contextually for investigative purposes. Most of the extant blockchain forensic frameworks incorporate static evaluation models and a monolithic approach to consensus, rendering them ill-suited to the dynamic forensic context of various event sensitivity, legality requirements, and auditability demands. Existing barriers to practical deployment in high-stakes forensic environments have been created. To begin addressing these gaps, this work presents Forensic-Driven Blockchain Evaluation and Simulation Architecture (ForBESA), which provides a complete simulation-based evaluation framework to com- pare Byzantine Fault Tolerant (BFT), Directed Acyclic Graph (DAG), and Proof-of- Stake (PoS) blockchains against forensic key performance indicators (KPIs). This framework consists of five novel modules. First, the Context-Aware KPI Weighting Engine (CAKWE) develops dynamic generation of KPI weight vectors using forensic incident metadata through the use of a decision tree classifier. Second, the Temporal Provenance DAG Tracker (TPDT) constructs enriched DAGs embedding trans- action timelines and investigator metadata to enhance traces’ future availability. Third, evidence routing across Hyperledger, IOTA, and Ethereum 2.0 will be simulated within the Hybrid Ledger Simulation Module under individual KPIs weighted with forensic considerations. Fourth, the Performance-Forensic Tradeoff Analyzer (PFTA) employs a utilitybased optimization and Pareto analysis to identify architecture suitability based on forensic depth versus performance trade-offs. Finally, the Chain-of-Custody Cryptographic Verifier (C3V) ensures evidence integrity and legal admissibility using smart contracts and zero- knowledge proofs. The improved forensic effectiveness and trace reconstruction up to 98.1% accuracy and 100% tamper detection are scantly recorded in the experiments. This study creates the first model of its kind regarding forensic-aware blockchain evaluation. The system provides precise, legally compliant, and context-responsive digital investigations in process.