Traditional Routing Research Articles

Development of high-dose carrier-free inhalable heparin sodium microparticles using co-jet-milling technology.

Development of high-dose carrier-free inhalable heparin sodium microparticles using co-jet-milling technology.

Mitigating the effects of Russia's invasion of Ukraine on global food security – does the transit of Ukrainian cereals through Poland matter?

The article presents the results of empirical research, which constitutes a case study focused on the route through Poland as an alternative export channel for Ukrainian grain, developed under the conditions of the Russia-Ukraine war. It employs analytical methods and statistical description. By analyzing the volume, dynamics, structure, and geography of the transit, the significance of this route in unleashing Ukraine's export capabilities and its role as a substitute for traditional routes during periods of disruption is assessed. It was established that almost exclusively corn and wheat are transited (in a quantitative ratio of 2:1). The railway crossings in Dorohusk, Medyka, and Hrubieszów are of key importance, as rail transport dominates in land transport, handling over 4/5 of the total mass of transited goods. More than half of the transited grain is transported by rail and road in scattered European directions, and only less than half reaches Polish Baltic ports, mainly Gdańsk (over 3/5) and Szczecin (almost 1/5). The degree of containerization exceeds 1/4. Practically all container cargo reaches the terminal in Gdańsk, while the port in Szczecin is the leader in bulk transport. The volume of Ukrainian grain transited through Poland is relatively small compared to Ukraine's export potential, and intercontinental transport concerns only a tenth of the grain transited through Poland. It was concluded that the route through Poland primarily serves as a new export channel for Ukrainian grain to the European market and only marginally substitutes traditional routes.

Neural network pathways: Visualizing iRaaS decision intelligence in modern infrastructure

This article explores Intelligent Routing as a Service (iRaaS), a transformative approach to network routing that leverages machine learning to overcome the limitations of traditional protocols. The article explores how iRaaS employs dynamic adaptability, service orientation, and context awareness to address the challenges of increasingly complex network environments. The discussion first examines core architectural elements, exploring both microservice structures and machine learning pipelines. It then advances to a comparative evaluation of performance metrics, contrasting the system against traditional routing approaches and demonstrating significant enhancements in response time, processing capacity, and system stability. The article further shows security and governance frameworks necessary for iRaaS implementation, including threat models specific to AI-driven routing and compliance considerations. The article concludes by investigating future research directions, particularly integration with intent-based networking, edge computing applications, standardization efforts, and emerging use cases across government, finance, healthcare, and enterprise sectors.

Development of optimization algorithms to vehicle routing problem

The Capacitated Vehicle Routing Problem with Time-Dependent Demands (CVRPTD) is a significant optimization challenge in the logistics and transportation domain, characterized by dynamic customer demands, strict time windows, and heterogeneous vehicle fleets. This study focuses on urban parcel delivery operations as the primary object of research. The problem addressed involves the inefficiency of conventional vehicle routing strategies in adapting to time-varying customer demands and operational constraints, which often lead to increased costs and service delays. This study aims to minimize total operational costs while ensuring compliance with capacity constraints, service continuity, and demand fluctuations. A comprehensive mathematical model is developed based on a fully connected, directed acyclic graph G=(V, A), incorporating decision variables that represent vehicle routing sequences, timing, and vehicle type assignments. This study addresses the Capacitated Vehicle Routing Problem with Time-Dependent Demands (CVRPTD) in urban parcel delivery, where traditional routing methods struggle with dynamic demands and operational constraints. A mathematical model using a directed acyclic graph is developed, optimized via a gradient-based method with Hessian approximation, LU decomposition, and quasi-Newton techniques. Experiments on datasets with up to 200 customers and 20 vehicles with reductions ranging from 1.79% to 12.75%. The most significant improvement was observed in Sidorame Timur, where the optimization distance decreased by 12.75%, indicating high accuracy in route optimization. For the SCP, the proposed algorithm achieved a 6.46% improvement in solution quality over traditional greedy algorithms

Sustainable Closed-Loop Recycling of Polyester Waste Using Reconstructed Defective-Metal-Organic Frameworks.

Chemical recycling of polyester waste presents a promising strategy for achieving a sustainable circular economy. However, the development of efficient, low-cost recycling methods that minimize energy consumption and carbon emissions remains challenging. Here, we report an approach for depolymerization polyester waste to bis(hydroxyethyl)terephthalate (BHET) using a reconstructed metal-organic framework (r-Zn-MOF74-NT) catalyst under mild conditions. The r-Zn-MOF74-NT exhibited a space-time yield of 1035.8 gBHET gcat -1h-1 at 190°C. Importantly, this is an order of magnitude higher than that reported for similar MOF-based catalysts. In situ spectroscopy combined with theoretical calculations revealed that the depolymerization pathway involves the activation of oxygen and ethylene glycol adsorbed on r-Zn-MOF74-NT, forming nucleophilic intermediates. These intermediates then facilitate the cleavage of the polyester C─O bond through nucleophilic attack, thereby gradually generating the BHET product. Sustainability evaluation results validated the circular economy feasibility of the recycling approach, with a minimum sales price (MSP) of 498 $/ton, much lower than the MSP of the traditional petroleum-based production route (1000 $/ton). The approach also achieved a 61% reduction in energy use and a 52% decrease in greenhouse gas emissions. This work provides a sustainable solution for managing polyester waste accumulation.

Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means

To solve the problem of high cost and low efficiency of measuring equipment in traditional distribution network fault location, a fault section location and line selection strategy combining dynamic binary particle swarm optimization (DBPSO) configuration and fuzzy C-means (FCM) clustering is proposed in this paper. Firstly, the DBPSO algorithm is used to optimize the configuration scheme of the distributed voltage and current sensing device, which reduces the number of measuring devices and system cost on the premise of ensuring the global observability of the distribution network. When a fault occurs in the distribution network, the sensor device based on optimal configuration collects fault feature data, combines it with the FCM clustering algorithm to classify nodes according to fault feature similarity, and divides the most significant fault-affected section as the core fault area. Further, by calculating the Euclidean distance between each node in the fault section and the cluster center, the fault line is accurately identified. Finally, a fault simulation model based on an IEEE 11-node system is constructed to verify the effectiveness of the proposed method. The results show that, compared with the traditional fault section location and route selection strategy, this method can reduce the number of measurement devices optimally configured by 19–36% and significantly reduce the number of algorithm iterations. In addition, it can realize rapid fault location and precise line screening at a low equipment cost under multiple fault types and different fault locations, which significantly improves fault location accuracy while reducing economic investment.

Grain Refinement and Microstructural Evolution in Cobalt-Saving 18Ni (300) Maraging Steel via Cold Deformation-Cyclic Solution Treatment

To solve the problem of inadequate plasticity of traditional processing routes in improving the plasticity of novel Co-saving 18Ni (300) maraging steel, a cold deformation-cycle solution treatment process was developed. Through systematic characterization and tensile property testing, the study focuses on elucidating the impact of the number of solution treatments on the microstructure and mechanical behavior. The results showed that with a 30% cold deformation, three times of solution treatment at 860 °C for 10 min refined the original austenite grains (equivalent circle radius: 3.3 μm) and martensite structure (length and width: 7 μm and 1.3 μm, respectively) to the utmost extent. The grains became uniformly equiaxed, and the texture was eliminated, and a moderate content (4.5%) of retained austenite was formed. At this time, the material achieves the best match between strength (tensile strength of 1240 MPa) and plasticity (elongation of 9.93%), which are increased by 15.3% and 94.3%, respectively, compared with the traditional process. Mechanistic analysis revealed that grain refinement and uniform equiaxialization were the primary drivers for enhancing strength and plasticity. This study has demonstrated that the cold deformation-cyclic solution treatment process is an effective methodology for tailoring the microstructure and mechanical properties of maraging steel.

Model-Based Deep Reinforcement Learning for Energy Efficient Routing of a Connected and Automated Vehicle

The emergence of connected and automated vehicles (CAVs) offers promising opportunities to enhance traffic control and improve overall transportation system performance. However, the complexity and dynamic nature of modern traffic networks pose significant challenges for traditional routing methods. To achieve optimal vehicle routing and support sustainable mobility, more adaptive and intelligent strategies are needed. Among recent advancements, model-based deep reinforcement learning has shown exceptional potential in solving complex decision-making problems across various domains. Leveraging this capability, the present study applies a model-based deep reinforcement learning approach to address the energy-efficient routing problem in a simulated CAV environment. The routes recommended by the algorithm are compared to the shortest route calculated by traffic simulation software. The simulation results show a significant improvement in energy efficiency when the vehicle follows the routes suggested by the learning algorithm, even when the vehicle is subjected to new traffic scenarios. In addition, a comparison of the model-based agent with a conventional model-free reinforcement learning agent across varied traffic conditions demonstrates the robustness of the model-based algorithm. This work represents the first application of a model-based deep reinforcement learning algorithm to the energy-efficient routing problem for CAVs. This work also showcases a novel application of the foundational algorithm AlphaGo Zero.

A Large-Scale Optimization Framework for Simultaneous Design and Routing of Wind-Assisted Ships

Abstract This paper presents a comprehensive approach to optimizing the performance of wind-assisted ships. The proposed optimization framework simultaneously addresses ship routing and design, considering the complex interactions between design parameters and route optimization across multiple weather scenarios. Optimal control methods, including the direct multiple shooting technique and automatic differentiation, are employed to efficiently optimize both routing and design parameters, resulting in a large-scale optimization problem. The methodology is demonstrated through a case study of a 2200-TEU container ship equipped with Flettner rotors, operating on a transatlantic route between Brittany and Halifax. The results provide a quantitative, model-based estimate of fuel savings, highlighting the importance of integrated optimization for wind-assisted propulsion systems, while maintaining computational efficiency suitable for iterative design processes. Compared to traditional design and routing methods, based on static polar diagrams and sequential design loops, this approach drastically reduces optimization times, enabling rapid design iterations and informed decision-making. Furthermore, the study offers insights into the sensitivity of fuel consumption to key design parameters, such as the number and placement of Flettner rotors, providing a more accurate and comprehensive estimate of potential energy savings compared to conventional methods. By overcoming the limitations of traditional polar-diagram-based methods, this framework provides a more accurate and dynamic assessment of wind-assisted propulsion systems. These findings emphasize the necessity of integrated optimization for maximizing performance and sustainability in maritime transport. Keywords Wind-assisted propulsion; Design optimization; Ship routing; Large-scale optimization

A Traditional Journey in Contemporary Times: The Pilgrimage of Mehmet Barut

In Turkish literature, hajj travelogues have been written since the 13th century, conveying Muslims’ experiences during the pilgrimage and explaining how to perform hajj. With the development and widespread use of the modern means of transportation in Türkiye from the 1940s onward, the pilgrims increasingly started to travel by air to avoid the hardships and duration of long journeys. However, this shift led to a decrease in visits to historical places along the traditional pilgrimage route from Türkiye to Mecca and Medina, consequently changing the content and nature of Hajj narratives. In spite of these changes, Mehmet Barut, a mufti (cleric), offered a unique response through his travelogue Hicaz Yolları [Hijaz Roads], which can be seen as a reaction to the rise in modern means of transportation. In 1965, Barut began his hajj journey from Tokat, within the border of the Republic of Türkiye, and travelled to Mecca and Medina by bus. Along the way, he visited Ankara, Konya, Tarsus, Iskenderun, Reyhanlı, Aleppo, Damascus, Jerusalem, Halilurrahman, Amman, Tabuk, Khaybar, and Medina before finally reaching Mecca. Barut’s travelogue is a contemporary non-fiction work, yet it was written in classical Turkish. In choosing to follow the historical pilgrimage route—established during the Ottoman period and beginning in Anatolia—Barut sought to revive and preserve the spiritual and cultural destinations and hajj journeys. His travelogue not only demonstrates his own travel experiences, but also reflects examples from the travelogue menazil-i hajj, offering insights into the historical significance of the cities and stopovers along the route. This study examines Hicaz Yolları from two key perspectives. First, it compares Barut’s chosen route with the historical Ottoman hajj route, highlighting key service areas and stopovers. Second, it explores the literary value of Barut’s work and its significance in contemporary Turkish literature. Ultimately, this study reveals that Barut’s travelogue not only kept the memory of traditional hajj pilgrimages alive, but also revived a fading tradition in an era dominated by modern means of transportation.

Railway transport corridors as an alternative and complement to water routes in international logistics

Railway transport corridors play a key role in international trade, connecting countries and continents. The article analyzes the importance of these routes, their impact on the economy and logistics, as well as key problems and development prospects. Special attention is paid to the Trans-Caspian International Transport Route (TMTM), the Northern Corridor and the New Silk Road. Special attention is paid to their interaction with water transport, the potential for replacing traditional sea routes such as the Suez Canal, as well as the advantages of rail transportation in conditions of geopolitical and climatic instability. Their advantages, infrastructural limitations and the influence of geopolitical factors are investigated. The statistical indicators of freight transportation growth were also studied, and the main barriers, including administrative, tariff, and infrastructural restrictions, were identified. The prospects for development, including the modernization of the railway network, digitalization of logistics and the introduction of environmentally sustainable technologies, are considered. The main focus is on the advantages of rail transportation, such as high load capacity, reliability, safety, cost-effectiveness and weather resistance, which makes rail transport an important element of international logistics. The role of railway corridors in improving Kazakhstan's transit potential is also emphasized, and it is concluded that it is important to integrate international efforts to improve the efficiency of rail transport and its competitiveness in the global market.

“Turcoman Gypsies:” The intersectional/multiple identities of a peripatetic group and its historical segmentation

The early eighteenth-century Ottoman state correspondences reference a peripatetic group in Rumelia identified as the “Turcoman Gypsies” ( Türkmān Ḳibṭīleri ). This group originated from Southern Anatolia and actively engaged with Turkic tribal organizations, notably the Zulkadriyye spin-offs ( ifrāz-ı Ẕūlkadriyye ). In response to discontent with Ottoman policies that sought to settle mobile populations in the late seventeenth century, they modified their traditional migratory routes. This led to their dispersion across Anatolia and Rumelia. Both state authorities and local communities labelled these groups as Gypsies ( Ḳibṭī or Çingene ), which assigned them an intersectional identity typically associated with peripatetic communities within the Ottoman Empire. Furthermore, the “Turcoman Gypsies” embraced multiple identities, including Abdal and Turcoman, as well as specific band names such as Çobān , Tarḫāneci , and Baṣdırmacı , reflecting their enduring connections to Turkic tribal organizations. The archival and ethnographic materials examined in the article uncover the historical links between the “Turcoman Gypsies” and other peripatetic groups in the Near East and Crimea, illustrating how they emerged from the segmentation of an ancestral community in Southern Anatolia. This article was published open access under a CC BY licence: https://creativecommons.org/licences/by/4.0/ .

Robust Optimization of Multimodal Transportation Route Selection Based on Multiple Uncertainties from the Perspective of Sustainable Transportation

Multimodal transportation is of strategic significance in improving transportation efficiency, reducing costs and achieving low-carbon development, all of which contribute to sustainable transportation. However, in actual operation, it often encounters multiple uncertain challenges such as demand, transportation time and carbon trading price, making it difficult for traditional fixed-parameter route optimization to meet the requirements of complex situations. Based on robust optimization and Box uncertainty set, this paper constructs a hybrid robust stochastic optimization model of multimodal transportation routes with uncertain demand, transportation time and carbon trading price, designs a hybrid algorithm, and verifies the effectiveness and rationality of the model through a numerical example. The results indicate that different types of uncertainty influence the routing decisions through distinct mechanisms. That is, demand uncertainty mainly affects capacity allocation and cost structure, transportation time uncertainty increases time penalties, and carbon trading price uncertainty drives preference for low-emission modes. Compared with the single genetic algorithm and the simulated annealing algorithm, the hybrid algorithm has better performance in terms of cost and stability. The hybrid robust stochastic optimization model can handle the multimodal transportation route selection problems where the probability distribution of parameters is unknown well. It is beneficial for decision-makers to adjust the uncertain budget level according to their preferences to formulate scientific transportation plans, so as to achieve sustainable transportation development.

Routing Challenges and Enabling Technologies for 6G–Satellite Network Integration: Toward Seamless Global Connectivity

The capabilities of 6G networks surpass those of existing networks, aiming to enable seamless connectivity between all entities and users at any given time. A critical aspect of achieving enhanced and ubiquitous mobile broadband, as promised by 6G networks, is merging satellite networks with land-based networks, which offers significant potential in terms of coverage area. Advanced routing techniques in next-generation network technologies, particularly when incorporating terrestrial and non-terrestrial networks, are essential for optimizing network efficiency and delivering promised services. However, the dynamic nature of the network, the heterogeneity and complexity of next-generation networks, and the relative distance and mobility of satellite networks all present challenges that traditional routing protocols struggle to address. This paper provides an in-depth analysis of 6G networks, addressing key enablers, technologies, commitments, satellite networks, and routing techniques in the context of 6G and satellite network integration. To ensure 6G fulfills its promises, the paper emphasizes necessary scenarios and investigates potential bottlenecks in routing techniques. Additionally, it explores satellite networks and identifies routing challenges within these systems. The paper highlights routing issues that may arise in the integration of 6G and satellite networks and offers a comprehensive examination of essential approaches, technologies, and visions required for future advancements in this area. 6G and satellite networks are associated with technical terms such as AI/ML, quantum computing, THz communication, beamforming, MIMO technology, ultra-wide band and multi-band antennas, hybrid channel models, and quantum encryption methods. These technologies will be utilized to enhance the performance, security, and sustainability of future networks.

Assessing the viability of magnetic separator tailings as a secondary source of nickel, cobalt and copper: a case study for Tati Nickel Mining Company

To date, the recovery of nickel and cobalt sulphide minerals from low-grade ores poses significant challenges in mineral processing due to their complex nature. With the decline of rich ore bodies, a paradigm shift to low-grade ores and secondary sources exists for these critical metals, particularly in the renewable energy sector, i.e. storage batteries. This study explores the potential consideration of the magnetic separator tailings obtained from Tati Nickel Mining Company in Botswana as a lucrative base metal secondary resource for the recovery of nickel, cobalt and copper. It becomes a dual approach to obtain valuable base metals while economically handling the waste material to ease the environmental challenges it was posing to the mine and the community. Characterisation of the samples obtained through crystallographic analysis, mineralogy and mapping, and elemental analysis showed the presence of nickel and copper minerals to a degree by which they can be economically extracted through hydrometallurgical means. Cobalt concentration in the sample was in trace amounts as it could only be detectable through the destructive technique. Concentration through froth flotation was conducted post characterisation, with emphasis on flotation time. The optimum flotation time was determined to be 3 minutes, giving metal recoveries of 15.56%, 27.40% and 52% for cobalt, nickel and copper respectively, with an enrichment ratio of 7.39 for copper. However, the yield obtained was 7.04% highlighting the ineffectiveness of the traditional concentration route previously practised in the mine. It was recommended therefore to re-design the flotation process and tailor it for the magnetic separator tailings, concentrating on the effects of pH and particle size distribution primarily, before the other factors, e.g. collectors, modifiers, etc. In conclusion, it was noted that the recovery of nickel, copper and the by-product iron was feasible; therefore, a recommendation was made to apply the Activox technology.

An adaptive intelligent thermal-aware routing protocol for wireless body area networks

Wireless Body Area Networks (WBANs) have gained significant attention due to their widespread applications in healthcare monitoring, sports performance tracking, military communication, and remote patient care. These networks consist of wearable or implanted sensor nodes continuously collecting and transmitting physiological data, requiring an efficient and reliable communication framework. However, the unique challenges of WBANs, such as limited energy resources, dynamic network topology, and high sensitivity to node temperature, necessitate specialized routing strategies. Traditional routing protocols, which often prioritize shortest-path selection, tend to create traffic congestion and overheating in specific nodes, leading to early network failures and reduced overall performance. To address these issues, this paper proposes an intelligent, temperature-aware, and reliability-based routing approach that enhances the overall efficiency and stability of WBANs. The proposed method operates in two phases: (1) network setup and intelligent path selection and (2) dynamic traffic management and hotspot avoidance. In the first phase, sensor nodes exchange vital network status information, including residual energy, node temperature, link reliability, and delay, to build an optimized network topology. Instead of relying solely on shortest-path routing, a multi-criteria decision-making algorithm is employed to select the most efficient paths, prioritizing those that balance energy consumption, temperature regulation, and communication stability. This prevents excessive energy depletion in specific nodes and avoids forming traffic bottlenecks. The system continuously monitors real-time network conditions in the second phase, dynamically rerouting traffic away from overheated or energy-depleted nodes. This ensures that critical sensor data is reliably delivered while extending the network’s lifetime. Simulation results demonstrate the superiority of the proposed approach compared to existing methods. The proposed method improves throughput by 13% and reduces end-to-end delay by 10%. Additionally, it achieves a 25% reduction in energy consumption. The proposed method also significantly reduces the normalized routing load by 30%.

Addressing the lack of ethnic diversity in the UK paramedic profession: a call for action

Ethnic minorities are starkly underrepresented among paramedics in the UK, with their numbers significantly lower than in other allied healthcare professions. This disparity is not reflective of the diverse population the NHS serves. To achieve truly patient-centred care, the paramedic workforce must be representative of the communities it serves. This professional practice article aims to discuss the role of higher education institutions, NHS England and NHS ambulance trusts in addressing this issue.The article examines traditional entry routes to paramedic education and highlights financial constraints and limited entry points as significant barriers for aspiring paramedics from diverse backgrounds. Furthermore, a lack of ethnic diversity in paramedic leadership positions is identified as a discouraging factor. The article then critically appraises existing initiatives aimed at promoting diversity, such as the College of Paramedics’ campaign. It acknowledges that raising awareness is a valuable step forward and advocates for a more comprehensive approach to achieve greater impact.The article lists some of the strategies employers could adopt to foster a more inclusive workplace culture and to support the career progression of paramedics from ethnic minority backgrounds. These strategies include targeted outreach programmes, mentorship initiatives, diversity and inclusion training for all staff and revisions to promotion policies.The article concludes by emphasising the need for a multi-pronged approach, involving collaboration between educational institutions, ambulance services, professional bodies and the government. Through implementing targeted recruitment strategies, fostering inclusive workplaces and providing career development opportunities, stakeholders can work together to build a more diverse and representative paramedic workforce, ultimately leading to improved equitable health outcomes at the individual, group and population level.

O-279 Go rectal!

Abstract In assisted reproductive technology (ART), adequate luteal phase support is critical for successful embryo implantation and pregnancy maintenance. Progesterone plays a pivotal role in this process. Traditional administration routes, such as vaginal, intramuscular, subcutaneous and oral, have their limitations, including discomfort, variable absorption rates and differential distribution between the endometrium and serum. This presentation explores the innovative approach of rectal administration of progesterone, highlighting the pharmacokinetic, enhanced bioavailability, and improved patient compliance. Studies, which provide insights into the efficacy of rectal progesterone compared to conventional methods in Hormone Replacement Therapy Frozen Embryo Transfer (HRT-FET) cycles will be presented. These studies demonstrate that rectal administration not only supports the luteal phase effectively but also increases patient satisfaction through reduced discomfort. In addition to summarising the clinical research findings, the presentation will outline suggestions for practical guidelines for implementing rectal progesterone in HRT-FET protocols, including potential challenges, such as patient acceptance and side effects, as well as future directions for research in this field will be discussed. This presentation aims to inform and engage IVF professionals by advocating for the consideration of rectal progesterone as a viable option in ART, ultimately contributing to improved patient outcomes and experiences.

Accessing Rights and Entitlements Under the Withdrawal Agreement: A View From the East of England

In this commentary we reflect on the citizens’ rights provisions of the Withdrawal Agreement (WA), which came into force on 1 February 2020, and the experiences of low paid (low skilled) EU migrant workers in the East of England in accessing these rights and entitlements. It is well documented that low paid EU citizens do not access/ enforce their rights and entitlements via traditional dispute resolution routes. The Independent Monitoring Authority (IMA) was, in fact, set up to assist EU nationals in the UK not with enforcement as such but with (i) Monitoring how UK public bodies are protecting the rights of EU and EEA EFTA citizens and their family members; and (ii) Promoting the effective implementation of citizens’ rights. They (the IMA) also have powers to launch inquiries and take legal action when appropriate. We have been working with two charities, GYROS (in Great Yarmouth, Norfolk) and PBIC (in 12 Bedford, Bedfordshire), who carried out a survey (drawing on the IMA’s annual citizens’ rights 13 survey) to understand the experiences of low skilled migrant workers from ‘hard to reach’ 14 communities. Using this data, we wanted to understand first, whether low skilled EU nationals are having difficulties accessing their rights (monitoring), and second, whether there are issues with the implementation of those rights (implementation)? The data from the survey suggests that low skilled EU citizens are still having difficulty gaining access to their rights. This is for two reasons: (1) lack of awareness of those rights and (2) some lack of trust in public bodies to fulfil these obligations. These findings are relevant to the full implementation of the Withdrawal Agreement and citizen’s rights to which the UK has committed to faithfully implement (where failure to do so can result in proceedings brought by the EU Commission). This article therefore aims to contribute to the evolving area of scholarship around understanding the experiences of EU citizens in the UK post Brexit by including those ‘harder to reach’ communities and their experiences of accessing rights and entitlements under the WA.

Microwave-assisted Synthesis of Benzimidazole Derivatives: A Green and Effective Approach

Background: Benzimidazole derivatives are pivotal in medicinal chemistry due to their diverse therapeutic applications. Traditional synthesis methods often require catalysts and long reaction times, which can be inefficient and environmentally unfriendly. Hence, there is a growing need for more efficient and eco-friendly synthetic methodologies. Methods: A newly devised and efficacious synthetic methodology has been established for the synthesis of benzimidazole derivatives, employing microwave assistance without the requirement for a catalyst. This method facilitated the synthesis of fifteen derivatives with notable efficiency, characterized by significantly reduced reaction times ranging from 5 to 10 minutes and impressive yields ranging from 94% to 98%. Results: The identity and purity of the synthesized benzimidazole derivatives were meticulously verified through a comprehensive analysis, encompassing a comparison of their physicochemical properties and spectral characteristics with authenticated reference data. Conclusion: This method represents a significant advancement in the synthesis of benzimidazole derivatives, offering a rapid and high-yielding alternative to traditional synthetic routes.