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The integration of Information Centric Networking (ICN) with the Internet of Things (IoT) will meet the expectations of end users by providing an admirable network system. ICN enhances the IoT by utilizing in-network caching regarding data dissemination with the help of various paths labeled by the name of the path by which the data is returned. Caching is a significant technique for improving content accessibility, reducing hops while transferring data, and finally shortening data access time, which in turn improves IoT networks. This study develops a novel caching strategy that caches content in suitable locations at highly requested nodes, thereby improving the information caching efficiency of ICN-based IoT systems. When comparing the proposed caching scheme with other caching methods, it pay attention to the data retrieval latency, cache hit ratio, and the average number of hops. These results consistently show that the proposed strategy enhances cache performance by a high margin. The future context of the utilization of the specified caching strategy will lie in the advancements of fog, edge, and ad hoc networks concerning the concept of IoT and new trends like 5 G and 6 G.

Mobile data offloading is a highly promising approach in mobile networks that tackles network congestion at Base Stations (BSs) and greatly improves both the Quality of Service (QoS) and Quality of Experience (QoE) for users. It presents significant business opportunities for operators, particularly in light of the exponential growth in mobile data traffic and the ongoing digital transformation. To effectively uphold the desired levels of QoS and QoE in the elevation of escalating digitalization and the unprecedented surge in data traffic, this paper presents offloading through a diverse range of technologies such as data offloading through Small Cell Networks (SCNs), Wi-Fi offloading, Device-to-Device (D2D) offloading, and data offloading through Vehicular Ad-Hoc Networks (VANETs). The SCNs and Wi-Fi offloading involve migrating data traffic to the alternative infrastructure i.e. the small BS and the Wi-Fi Access Points (AP), respectively while D2D focuses on transferring data through the device without transversing the BSs. VANETs is the process of offloading data in vehicular scenarios that consist of Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X). Additionally, mobile data offloading from cellular BS is categorized into four main factors: energy consumption or energy awareness, economic considerations, user satisfaction, and network congestion. These factors play a crucial role in the ongoing adoption and implementation of mobile data offloading strategies. Different technologies utilize diverse techniques to tackle the challenge of offloading, aligning with their specific research objectives. This paper delves into the challenges and outlines future research directions in the field of mobile traffic offloading.

This paper introduces a transformative approach to managing producer mobility in Named Data Networking (NDN). It presents a novel analytical model known as Producer Mobility Management Model (PMMM) that significantly improves handoff latency, signalling cost, and packet delivery efficiency, overcoming limitations of traditional static anchor-based methods. This model serves as an extension of well-established theories drawn from existing literature, thus offering an advanced approach towards managing producer mobility. The model provides the dynamic mobility management solution to adapt to efficiently manage producer movements, ensuring optimal routing and efficient network performance. Comparative evaluations demonstrate marked advancements over existing solutions, establishing the model as a scalable and robust solution for NDN environments that solves high handoff latency, excessive signalling and long packet delivery issues. This work not only addresses current challenges in producer mobility but also sets a new direction for future research and practical applications in NDN architecture.

The effectiveness of the current Internet architecture has been challenged due to the exponential and revolutionary expansion of smart mobile devices and content requirements. Therefore, the underlying solutions, such as Named Data Networks (NDN), is designed to achieve a highly efficient architecture for content delivery and to manage mobile devices in the network. Mobility is becoming a more exciting and hotly debated topic nowadays as it plays an increasingly significant role in the expanding trend of network device mobilisation. Thus, this study deliberates one of the emerging popular mobility issues in NDN and enlightens both consumer and producer mobility. While NDN paradigm made possible the consumer mobility by establishing the in-network caching functionality, producer mobility is still struggling to manage content distribution. The mobile producer handoff process confronting several challenges due to lack of new location update towards the network. Although, the research community has discovered numerous improvements related to producer mobility, but the network is still experiencing long handoff latency and packet loss. Therefore, this paper critically examined the substantial research works on producer mobility that have already been completed and struggling to achieve the desired level of mobility support in NDN. This survey categorizes producer mobility solutions into five different approaches depending on their characteristics and functionalities. In addition, it also measured the performance of each mobile producer approach in terms of handoff latency through network analysis model. Moreover, the research problems and long-standing challenges among the approaches have been summarised and suggested an intuitive direction through network analysis results.

This study investigates the potential of flavonoid compounds from Sandoricum koetjape leaf extracts as tyrosinase inhibitors, using in vitro and in silico methodologies. Tyrosinase is crucial for melanin synthesis, and its excessive activity leads to hyperpigmentation disorders. The extracts underwent maceration, partitioning, and concentration, followed by tyrosinase inhibition assays and LC-MS/MS analysis. The ethyl acetate fraction showed the highest inhibitory activity, revealing key flavonoids like Kaempferol-3-O-β-Dglucopyranoside and Quercimeritrin. Molecular docking and dynamic simulations provided insights into their binding mechanisms. Kaempferol-3-Oβ-D-glucopyranoside exhibited a binding affinity of -8.4 kcal/mol, while Quercimeritrin had -7.7 kcal/mol. PreADME profiles indicated Quercimeritrin’s higher solubility, better skin permeability, and lower environmental toxicity. This comprehensive evaluation underscores the viability of S. koetjape as a natural source for tyrosinase inhibitors, highlighting the need for further optimization and in vivo studies to confirm efficacy and safety for dermatological applications.

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.