The paper discusses how artificial intelligence (AI) is transforming public services that are provided to people by governments and directing decision-making in the government. The research addresses the topic of AI technologies being fitted into government processes more often to achieve efficiency, better service provision, and data-driven policymaking. The research applies a secondary research methodology, which is a desk analysis of the available literature, in assessing the opportunities and challenges linked to the use of AI in the public sector. The results show that AI can enhance the quality of government and society services in the field of governance management, law enforcement, and medical services, and help make more informed administrative decisions. The paper also points to the significance of tackling the problem concerning data privacy concerns, ethical governance, and institutional preparedness. The study indicates that the successful implementation of AI should entail proper technological infrastructure, regulatory framework, and organizational capacity in government institutions.

This contribution aims to analyze medical interventions scheduled and executed using image-guided robots. Such interventions, which can be surgical or restricted drug delivery, involve minimally invasive, precise, and harmless therapies. The accuracy of robotic positioning is trained via uncertainty and complexity reductions. This could be achieved by matching real and virtual procedures involving physical and virtual phantoms of the relevant part of the living tissues. Such tailored training includes personalized, patient and interventional tool features. The training results enable a real (with patient) intervention controlled by staff and a possible matched autonomous intervention under staff supervision. The paper includes regards on the control and monitoring of image-guided procedures, and on augmented matched digital twins for real interventions. The various topics covered in this narrative review, are supported by examples from the literature.

This paper revisits the longstanding problem of the urban core-periphery structure through the lens of complexity and network theories. We argue that this relation remains central to urban science, requiring cities to be interpreted as dynamic systems in which urban form and social structure co-evolve through continuous interaction. Building on classical geographical and economic models, as well as developments in complexity science, the study proposes a systemic approach to describe and simulate the emergence of multicentricity. Using Porto Alegre (Brazil) as a case study, we examine how socio-spatial centralities emerge and interact within the urban system. The results suggest that polycentricity is not merely decentralization, but an emergent property of urban complexity shaped by path-dependent dynamics and social inequality. The study contributes to linking Latin American urbanization to broader discussions on emergence, self-organization, and peripheral urbanization.

Bangladesh's path to upper-middle-income status by 2041 hinges on transformative infrastructure expansion, with annual investment needs estimated at USD 10–12 billion. Conventional public financing mechanisms are insufficient to meet this demand, especially as external aid flows decline in the post-LDC transition. This study positions Public-Private Partnerships (PPPs) not as a supplementary tool, but as a strategic imperative for bridging fiscal gaps, mobilizing private capital, and accelerating infrastructure delivery across transport, energy, and urban services. Building on global PPP models and Bangladesh's policy evolution since 2010, the study reviews frameworks from the UK, Australia, India, and China. At the same time, the study also examines domestic challenges through reports and field-level experience. It incorporates practitioner insights from the roles in the Bangladesh Economic Zones Authority (BEZA), the Dhaka Bypass Expressway, and the Planning Commission. The study uses a mixed-method approach combining document analysis, comparative case studies, and implementation experience to highlight the need for bankable project design, transparent procurement, and inclusive governance. It contributes to the policy discourse on development financing and institutional reform, offering strategic recommendations for policymakers, development partners, and civil society. It also shows how PPPs can advance key Sustainable Development Goals (SDGs), including clean energy, decent work, innovation, and urban resilience.

The present study investigates the effect of nano-Fe₂O₃ particles as a micronutrient on the growth of plant seedlings of Mung (Vigna radiate) and Gram (Cicer arietinum) using the plant agar method. The laboratory experiment was carried out in the test units comprising a petri dish and plant agar medium. The plant agar medium used acts as a false soil that supports the seedlings for germination, prevents precipitation of water-insoluble nanoparticles and eliminates the possibility of any nutrients from external sources other than the nano-Fe₂O₃ particles. Each test unit containing agar media was treated with nano-Fe₂O₃ particle suspension at different concentrations. The effect of nano-Fe₂O₃ particle dose-response on root and shoot growth of the seedlings, as well as on biomass assay, was examined. The results showed that among the various concentrations of nano-Fe₂O₃ particles studied, a good agronomic value over control was observed only for certain optimum concentration i.e., 50 mg/L for mung and 5 mg/L for gram seedlings. Beyond this dose limit, the seedlings showed retardation in their growth characteristics, indicating phytotoxicity.

Liver cancer, particularly hepatocellular carcinoma (HCC), remains a major cause of cancer-related mortality worldwide due to various reasons, including late-stage diagnosis, treatment resistance, and limited therapeutic efficacy. Conventional treatment strategies- surgical resection, chemotherapy, and targeted therapies- pose significant limitations such as poor specificity, systemic toxicity, and disease recurrence, preventing timely treatment. Recent advances in nanotechnology provide promising solutions, particularly in early diagnosis and precision medicine. This review focuses on nanotechnology-based theranostic techniques, including nano biosensing, liquid biopsy innovations, and imaging enhancements. Furthermore, significant improvements in therapeutic strategies, such as nanoparticle-mediated drug delivery and immunomodulation, are discussed, as well as existing challenges and potential prospects. Understanding the potential of these innovations is crucial for establishing more effective, personalized, and minimally invasive strategies for liver cancer management.