Abstract This review aimed to explore the integration of Quantum Computing (QC) with Artificial Intelligence (AI) subsets such as Machine Learning (ML) and Deep Learning (DL), addressing the computational demands posed by the exponential growth of visual data. It identifies key challenges such as interdisciplinary complexity, lack of standard benchmarks, scalability, integration barriers, and the theoretical-practical gap in quantum applications. The review systematically examines existing literature on the application of quantum algorithms in areas including image processing, Natural Language Processing (NLP), Transfer Learning (TL), Federated Learning (FL), networking, cybersecurity and the finance sector. It highlights the usage of quantum principles like superposition and entanglement to accelerate computations, optimize models, and enhance data security in ML/DL frameworks. Findings indicate that integrating QC with ML/DL offers faster convergence, improved optimization, secure decentralized learning, and efficient handling of large-scale and complex data. Specific improvements are observed in TL and FL approaches, NLP accuracy, cryptographic robustness, and performance in medical diagnostics and autonomous systems. QC holds transformative potential in enhancing ML/DL capabilities across domains. Despite existing challenges such as error mitigation and integration complexity, its combination with classical learning methods opens new frontiers for research in AI-driven sectors. Future studies should focus on bridging theoretical and application-level gaps while creating standardized evaluation frameworks.
Open access
Quantum Computing Algorithms and Architecture
Big Data and Digital Economy
Artificial Intelligence in Healthcare and Education
The programmable economy lacks a universal computational layer capable of interpreting, translating, verifying, and simulating the mathematical and cryptographic operations that underpin digital assets. Existing tools are fragmented: wallet software provides only rudimentary transaction signing, portfolio trackers offer aggregated views without evidence, and specialized calculators address isolated problems. No general-purpose, cryptographically verifiable, language-native computational environment exists for digital value. KHOTOR is designed to fill this gap. It is a universal, deterministic runtime that interprets the anti-entropic linguistic protocol Kryptophon, transforms plain-language queries into executable computational expressions, and performs multi-domain financial mathematics across asset conversion, transaction analysis, decentralized finance, tokenomics simulation, cryptographic proof generation, and risk assessment. Every output carries an epistemic classification — verified, observed, inferred, simulated, or uncertain — and can be exported as a Gamma-Proof: a cryptographically signed, independently verifiable artifact. This paper presents the complete KHOTOR architecture: a ten-layer computational engine, a formal abstract machine for Kryptophon evaluation, a tiered adoption model that makes the programmable economy accessible to non-technical users while creating a new domain of expertise for professionals, and a product family spanning a public cloud API, a web platform, a handheld consumer device, and integration with dedicated hardware instruments. All components are designed around a single governing principle: every calculation shows its work, every output carries a truth label, and no inference is ever presented as fact.
Sibelle Torres Vilaça, Alexandre Aleixo, Juliana A. Vianna
The biodiversity crisis is accelerating, with recent IUCN Red List confirming multiple recent species extinctions (IUCN, 2025). Of the 17 megadiverse countries, which account for ~70% of Earth's biodiversity, 15 are part of the Global South. Most of the habitat and biodiversity loss is concentrated in nine of the megadiverse countries. Generating knowledge for all life on Earth is fundamental for bending the curve of biodiversity loss, and genomics has recently emerged as an important component in conservation biology. Mapping and understanding genome-wide variation can help estimate important biological variables essential for species conservation, understanding adaptation to climate change, and predicting populations' long-term resilience (Vilaça et al., 2024).Genome sequencing has ramped up in the last decade as the costs drop and technology advances (Wetterstrand et al, 2025). The Earth BioGenome Project (EBP) is capitalizing on this in its aim to sequencing the genomes of all known eukaryotic species. The lead article by Blaxter et al., (2025) paves the way for Phase II of the EBP, which aims to sequence reference genomes for 150,000 species throughout the tree of life. With an estimated cost of US$ 1.1 billion (US$4.42 billion for all 3 phases) Phase II will bring important developments in technology for data production and processing, while establishing sequencing centers worldwide. Although these accomplishments are set to change the way we do biodiversity genomics research globally, we believe that major challenges need to be overcome for the project to accomplish its goals and truly reach equitable partnerships and effective engagement with the Global South. Bringing our significant experience as researchers involved in EBP-affiliated initiatives based in South America, we address potential blockers for Phase II in the Global South in sequencing infrastructure and technology, funding sources, enabling equitable global participation, and engaging government and policy makers.Sequencing life on Earth requires global participation, especially in biodiversity-rich regions. A solution proposed by Blaxter et al., (2025) involves the creation of decentralized laboratories (gBox) established at 25 regional nodes. This model is based on the approach used in outbreak response for pathogen detection like COVID-19. While laboratories for rapid response to disease outbreaks require a Biosecurity Level 3/4, the general infrastructure (Affara et al., 2021) is typically simpler in terms of equipment than the laboratories required for sequencing reference genomes. In our experience, maintaining sequencers in countries where few or no other similar equipment is available is challenging due to the lack of specialized and timely maintenance. The reliance on imported reagents from the Global North can further undermine efforts because of common cold-chain failures that often lead to reagents not arriving at their destination with the required integrity for optimal use (Vilaça et al., 2024). The current limitations in technology, maintenance, importing reagents, and keeping sample integrity are important obstacles that need to be overcome for the gBox model to work in countries without a tradition in genomic sequencing.Securing adequate funding remains a key issue. During the SARS-CoV-2 pandemic, rapid funding availability by governments and the private sector allowed investments of USD$9.2 billion in vaccine development (Tortorice et al., 2024) generating trillions in social, health, economic revenue. The same model is needed for biodiversity. With an estimated global cost of €14 trillion in ecosystem services associated with biodiversity loss until 2050 (ten Brink et al., 2009), this loss will bring severe impacts on health, economy and social well-being. Unfortunately, this sense of urgency is not yet instilled in funding priorities and financial investments. In our experience, this is a general pattern of biodiversity-related science funding, as both the Chilean and Brazilian governments have invested in large facilities for astronomy and physics (Catanzaro et al., 2014;Angelo, 2017). Environmental expenditures by governments decrease in times of recession with some countries failing to include biodiversity agendas in their post-COVID economy recovery packages (McElwee et al., 2020). Because reference genomic libraries are key for supporting the monitoring of endangered species and developing local bioeconomy initiatives, wider investments focused on biodiversity knowledge are necessary for its conservation and recovery. The creation of a global public-private co-funding mechanism similar to the recently established Tropical Forests Forever Facility (TFFF) -aimed at compensating financially countries that commit to preserving their tropical forests (https://www.wri.org/insights/financing-nature-conservation-tropical-forest-forever-facility) -could be explored as an alternative to support sequencing efforts in megadiverse countries. Under such a co-funding mechanism, Global South countries would find mechanisms for matching at least some percentage of the external funding that is brought into the country for biodiversity genomics in several alternative ways.We view this as an important step to root perennial biodiversity initiatives in their Global South countries' own territories. These mechanisms could include institutional commitments (e.g., integration into national biodiversity and bioeconomy agendas) and recurrent budget lines supporting the development of local biological collections, biobanks, and molecular biology laboratories, in addition to genomics expertise.Achieving the goals of Phase II of the EBP will require more than advances in sequencing technologies and expanded reference databases; it will require structural changes that enable equitable global participation and governance. Researchers based in megadiverse countries cannot be relegated to sample providers (Vilaça et al., 2024), but need to be embedded in decision-making, generate data locally, and contribute as skilled personnel.Therefore, it is important that EBP-Phase II -in addition to direct efforts to reference genome sequencing proper -also include the training of local researchers in genome sequencing, assembly, curation, and annotation to overcome the capacitation gap in genomics found nowadays in Global South countries.First, the involvement of Global South scientists within the EBP must extend to decision-making and leadership roles that reflect the contribution of the communities within megadiverse countries. Other critical roles include setting local priorities in terms of species to be sequenced and linking locally generated genomes with national research, development, and innovation agendas, as done in the Genomics of Brazilian Biodiversity (GBB) consortium (Vilaça et al., 2024;Povill et al., 2025). Recently, Latin American countries started organizing an EBP node (Red de Genomas Neotropicales -BioGenomas) with country representatives sharing experiences, realities and local models for sequencing projects with reduced financing support. Brazil and Chile began coordinating meetings with scientists from Argentina, Colombia, and Mexico. Since then, Argentina has set the first framework for a national biodiversity genomics consortium. In our model, organizing under nationwide initiatives, followed by a larger network is the first step to ensure that regional and local realities are represented and considered. Other approaches can also be used as models, like the African BioGenome Project, which started as a continent-wide initiative.Second, the feasibility of decentralized sequencing infrastructure-such as the proposed gBox-must be carefully evaluated within the context of countries facing recurrent challenges in importing reagents, maintaining equipment, and ensuring reliable cold-chain delivery. These barriers remain major bottlenecks that cannot be overlooked when deploying high-throughput sequencing technology globally. The establishment of the proposed US$0.5 billion Foundational Impact Fund (FIF) in Phase II is therefore essential. By focusing support on capacity development and long-term infrastructure in the Global South, the FIF could catalyze sustainable growth in biodiversity genomics rather than short-term or project-bound grants. Decentralized funding models, unconstrained from politically-bound research agendas are crucial for the EBP hubs to dictate research direction considering local aspects. In this way, we can focus on local solutions to solve global problems.In many Global South countries, the acquisition of reagents is hindered by persistent failures in maintaining the required cold chain during importation, customs delays, and the lack of reliable distributor networks. These issues lead to frequent reagent degradation and increased costs that slow down or halt genomic workflows. There is a pressing need for supply chains that support room temperature reagents to preserve, high-quality samples.Legal uncertainties, the absence of standardized national frameworks, and administrative bottlenecks further constrain access and sharing of biological samples. Creating and supporting existing local biodiversity biobanks, possibly associated with natural history collections, is also important for access to high-quality well-documented samples for genome sequencing. Addressing these challenges requires coordinated technological advances, policy development and long-term engagement with keystone local institutions.Third, a critical step toward enabling equitable participation in EBP's Phase II is transforming how political leaders and policymakers engage with biodiversity science. They must recognize that the biodiversity crisis is as urgent as climate change or future pandemics, and that delaying action will have profound consequences. The ongoing discussions in international policy like the Convention for Biological Diversity highlight a timely opportunity: biodiversity genomics must be integrated into global and national environmental agendas as a strategic tool for conservation, climate adaptation, and sustainable development.Genomic resources are not only essential for monitoring and protecting biodiversity, they also underpin emerging bioeconomy value chains, biotechnological innovation, and preparedness for future biological emergencies.Importantly, national public policies for genetic-resource protection-including implementation of the Nagoya Protocol and emerging approaches to Digital Sequence Information (DSI) benefit sharing-are key to enabling local sequencing and ensuring that local researchers remain central. Countries need legislation that not only regulates the use of genetic resources but also actively encourages and funds local sequencing, capacity development, and equitable scientific leadership. This will enable Global South researchers and governments to play active roles in international agreements, boosting their confidence in becoming equitable partners in biodiversity genomics initiatives, rather than adopting a defensive attitude to avoid any undue use of the countries' genomic resources.As biodiversity loss accelerates, investments in biodiversity genomics should not depend solely on academic enthusiasm; they must be recognized as essential national and global priorities, with clear economic, health, and societal implications. To realize this vision, policymakers should no longer be considered as "stakeholders". They must become active partners in the co-creation of genomic initiatives (see Vilaça et al. 2024). Co-designing strategies with governments ensures that genomic data are incorporated into national priorities, that legal frameworks evolve in tandem with scientific advances, and that investments in infrastructure and capacity remain stable across political cycles. This shift is especially critical for megadiverse countries, where genomic knowledge can directly inform sustainable resource management, climate resilience, and health surveillance systems. By integrating scientific, political, and community perspectives, the EBP Phase II can become not only a global sequencing effort but a transformative movement toward a more inclusive, resilient, and strategically valuable model of biodiversity science.Author contribution
Local government institutions (LGIs) are widely recognized as the cornerstone of democratic governance and sustainable local development. In Bangladesh, Union Parishads, Municipalities (Pourashavas), Upazila Parishads, Zila Parishads, and City Corporations play a vital role in delivering public services, promoting participatory governance, and fostering socio-economic development. Despite significant progress in decentralization, the financial autonomy of local governments remains limited due to excessive dependence on central government transfers and grants. The inadequate mobilization of own-source revenue (OSR) restricts the capacity of LGIs to finance infrastructure, maintain essential public services, and respond effectively to local development needs. This conceptual paper examines the relationship between strengthening local government institutions and improving own-source revenue mobilization in Bangladesh. Drawing upon theories of fiscal decentralization, public financial management, and good governance, the paper argues that sustainable local development requires financially autonomous local governments capable of generating, managing, and utilizing local revenues efficiently and transparently. The study identifies key institutional, legal, administrative, technological, and political constraints affecting local revenue collection while proposing policy options to enhance fiscal capacity. The paper further emphasizes that digital transformation, improved tax administration, citizen participation, institutional accountability, and fiscal transparency can significantly strengthen local revenue systems. Effective utilization of locally generated revenue not only improves service delivery but also reinforces public trust and democratic accountability. The findings contribute to the growing literature on decentralization and local public finance by providing a conceptual framework for strengthening local government finance in Bangladesh.
This paper introduces Automated Institutional Discovery (AID), a novel computational framework that conceptualizes economic institutional design as a high-dimensional combinatorial search problem. Traditional institutional design relies heavily on human intuition, historical evolution, or analytically constrained mechanism design, which often fails in complex, adaptive multi-agent environments. AID transcends these limitations by framing institutions as tuples i = (r_1, r_2, ..., r_K) within an expansive institutional space and utilizing advanced search and optimization algorithms to discover configurations that maximize global objective functions F(i). By combining multi-agent simulation modeling with metaheuristic search strategies, AID evaluates allocative efficiency, incentive compatibility, resilience, and distributional equity without requiring empirical laboratory experiments. The framework establishes a paradigm shift from manual rule-making to automated machine discovery, offering robust applications for digital economies, decentralized finance, and economic governance.
Decentralized Finance (DeFi) refers to an open financial ecosystem built on blockchain technology that does not require the participation of centralized institutions. The technology and operational mechanisms it employs represent a significant "paradigm mismatch" with the current financial regulatory framework. This paper examines the comprehensive impact of DeFi on existing financial regulation from multiple perspectives, including the blurring of regulatory authority and a lack of accountability; the difficulty in identifying regulatory targets and the ambiguity in determining their nature; the ineffectiveness of regulatory rules and the absence of relevant provisions; overlapping jurisdictions, and difficulties in enforcement. Through a comparative study of regulatory experiences in the United States, Europe, and other regions, this paper proposes solutions such as shifting the existing regulatory philosophy toward functional regulation, embedding compliance requirements into the underlying technology at the institutional level, and strengthening international cooperation at the operational level, while also discussing the specific context in China. This paper identifies a threefold paradigm mismatch between decentralized finance and traditional financial regulation, giving rise to multiple regulatory challenges such as difficulties in holding entities accountable, ambiguity in defining regulatory targets, ineffective regulatory rules, and obstacles to cross-border enforcement. A comparison of regulatory practices in the U.S. and Europe reveals that it is difficult for any single country to independently manage the risks associated with globalized DeFi.
Biometric authentication offers enhanced usability for digital payments, but traditional centralized architectures suffer from single points of failure. While blockchain integration promises decentralized trust, existing solutions often store biometric helper data (e.g., fuzzy commitments) directly on-chain. We demonstrate that such transparency, even in permissioned settings, exposes low-entropy biometric inputs to offline brute-force attacks and identity-linkage risks if the immutable ledger is accessed by malicious nodes. To resolve this transparency–privacy paradox, we propose a threshold-based decentralized authentication framework. Unlike prior works, our protocol keeps all sensitive Biometric-Enhanced Key Derivation (BEKD) tokens entirely off-chain, using the blockchain solely for freshness enforcement. We provide a game-based security analysis of brute-force resistance, unforgeability, and unlinkability. Our experimental results demonstrate that our scheme’s gas cost is acceptable, offering a robust solution for self-sovereign biometric identity.
Autonomous multi-agent systems powered by Large Language Models (LLMs) are increasingly deployed in high-frequency algorithmic trading, decentralized finance (DeFi), and complex financial decision-making workflows. However, existing multi-agent interaction architectures rely heavily on implicit semantic trust: context passing between upstream and downstream agents occurs via unauthenticated, unstructured natural language or JSON payloads. This design creates critical vulnerabilities, exposing systems to indirect prompt injection, context tampering, system prompt spoofing, and multi-turn cascade poisoning. When an upstream agent ingests malicious external data, adversarial payloads can propagate through the inter-agent execution graph, bypassing single-agent perimeter guardrails and hijacking downstream financial execution logic. To resolve these vulnerabilities, we introduce AgentShield-Crypto, a zero-trust cryptographic framework for multi-agent LLM trading pipelines. AgentShield-Crypto enforces the Know-Your-Agent (KYA) protocol, replacing probabilistic natural language filters with deterministic cryptographic state boundaries. Under KYA, every agent's identity, static system prompt hash H(S_i), temporal liveness timestamp t_i, and output payload M_i are encapsulated into cryptographically signed state envelopes (E_i) using HMAC-SHA256. Inter-agent communication channels are guarded by Inline Cascading Anomaly Firewalls (ICAF), which evaluate verification predicates before allowing state transitions into downstream context windows. We construct and release AgentInject-Bench v1.0, an empirical benchmark comprising 7,000 test vectors spanning direct prompt injections, indirect context hijacking, multi-turn cascade poisoning, system prompt spoofing, and clean financial market baselines across GPT-4o, Claude 3.5 Sonnet, and Llama-3-70B-Instruct. Empirical evaluation demonstrates that AgentShield-Crypto achieves a 100.00% Defense Mitigation Rate (DMR) with a 0.00% False Positive Rate (FPR), completely eliminating multi-hop context hijacking while incurring sub-millisecond per-message execution latency (0.382 ms).