Search Results (40)

Traffic crashes and congestion generate high social and economic costs, yet traditional traffic monitoring methods, such as police patrols, fixed cameras, and helicopters, are costly, labor-intensive, and limited in spatial coverage. This paper presents a novel Drone Routing and Scheduling with Flexible Multiple Visits (DRSFMV) framework, an optimization model for planning drone-based highway monitoring under realistic operational constraints, including battery limits, variable monitoring durations, recharging at a depot, and target-specific inter-visit time limits. A mixed-integer nonlinear programming (MINLP) model and a linearized version (MILP) are presented to solve the problem. Due to the NP-hard nature of the underlying problem structure, a heuristic solver, Hexaly, is also used. A case study using real traffic census data from three Southern California counties tests the models across various network sizes and configurations. The MILP solves small and medium instances efficiently, and Hexaly produces high-quality solutions for large-scale networks. Results show clear trade-offs between drone availability and time-slot flexibility, and demonstrate that stricter revisit constraints raise operational cost. Full article

As China’s economy grows and travel demand increases, its aviation market has evolved to become the second-largest in the world. This study presents a pioneering analysis of China’s aviation network evolution (1990–2024) by integrating temporal dynamics into a network density matrix theory, addressing critical gaps in prior static network analyses. Unlike conventional studies focusing on isolated topological metrics, we introduce a triangulated methodology: ① a network sequence analysis capturing structural shifts in degree distribution, clustering coefficient, and path length; ② novel redundancy–entropy coupling quantifying complexity evolution beyond traditional efficiency metrics; and ③ economic-network coordination modeling with spatial autocorrelation validation. Key innovations reveal previously unrecognized dynamics: ① Time-embedded density matrices ($\rho$) demonstrate how sparsity balances information propagation efficiency ($\eta$) and response diversity, resolving the paradox of functional yet sparse connectivity. ② Redundancy–entropy synergy exposes adaptive trade-offs. Entropy ($H$) rises 18% (2000–2024), while redundancy ($R$) rebounds post-2010 (0.25→0.33), reflecting the strategic resilience enhancement after early efficiency-focused phases. ③ Economic-network coupling exhibits strong spatial autocorrelation ($Moran’sI>0.16$, $p<0.05$), with eastern China achieving “primary coordination”, while western regions lag due to geographical constraints. The empirical results confirm structural self-organization. Power-law strengthening, route growth exponentially outpacing cities, and clustering ($C$) rising 16% as the path length ($L$) increases, validating the hierarchical hub formation. These findings establish aviation networks as dynamically optimized systems where economic policies and topological laws interactively drive evolution, offering a paradigm shift from descriptive to predictive network management. Full article

Modern logistics requires effective solutions for the optimization of intermodal transportation, providing cost reduction and improvement of transport flows. This paper proposes a multi-objective optimization method for intermodal freight transportation planning within the framework of sustainable service network design. The approach aims to balance economic efficiency and environmental sustainability by minimizing both transportation costs and delivery time. A bi-criteria mathematical model is developed and solved using the Non-dominated Sorting Genetic Algorithm III (NSGA-III), which is well-suited for handling complex, large-scale optimization problems under multiple constraints. The aim of the study is to develop and implement this technology that balances economic efficiency, environmental sustainability and manageability of operational processes. The research includes the development of a two-criteria model that takes into account both temporal and economic parameters of the routes. The optimization method employs the NSGA-III, a well-known metaheuristic that generates a diverse set of near-optimal Pareto-efficient solutions. This enables the selection of trade-off alternatives depending on the decision-maker’s preferences and specific operational constraints. Simulation results show that the implementation of the proposed technology can reduce the costs of intermodal operators by an average of 8% and the duration of transportation by up to 50% compared to traditional planning methods. In addition, the automation of the process contributes to a more rational use of resources, reducing carbon emissions and increasing the sustainability of transportation networks. This approach is in line with the principles of sustainable economic development, as it improves the efficiency of logistics operations, reduces pressure on infrastructure and minimizes the environmental impact of the transport sector. Route optimization and digitalization of transport processes can increase resource efficiency, improve freight flow management and contribute to the long-term stability of transport systems. The developed technology of automated planning of intermodal transportation is oriented to application in large-scale production systems, providing effective management of cargo flows within complex logistics chains. The proposed method supports the principles of sustainable development by providing a formal decision-making framework that balances transportation cost, delivery time and environmental objectives. Instead of optimizing for a single goal, the model enables the identification of efficient trade-offs between economic performance and ecological impact. Moreover, by generating multiple routing scenarios under varying operational constraints, the approach enhances the adaptability and robustness of freight transportation systems in dynamic and uncertain environments. Full article

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. Full article

This paper explores the origins and global significance of Judaic hermeneutics as a foundational logical culture, arguing that it constitutes one of the earliest and most sophisticated systems of reasoning in human history. Far beyond a method of religious interpretation, Rabbinic hermeneutics represents a logic in practice: a structured, culturally embedded framework of inference rules (middôt), such as qal wāḥōmer (a fortiori reasoning), that guided legal deliberation and textual exegesis. By comparing Judaic hermeneutic methods with Greco-Roman rhetoric, Indian logic, and Chinese philosophy, this study reveals that similar logemes—elementary reasoning units—appear only in these four ancient traditions. All emerged within a narrow geographic corridor (32–38° N latitude) historically linked by trade routes, particularly the Silk Road. Drawing on legal documents and logic history, this paper argues that logical cultures did not arise from isolated individuals, but from collective intellectual traditions among elites engaged in commerce, law, and education. Judaic hermeneutics, with its roots in Babylonian legal traditions and its codification in the Talmud, offers a clear example of logic as a communal, evolving practice. This study thus reframes the history of logic as a pluralistic, global phenomenon shaped by cultural, economic, and institutional contexts. Full article

Research on fish skin artefacts’ dyeing practices among the Nivkh, Nanai, Ulchi, Udegei, Oroch, and Negidal Indigenous Peoples of the Amur River basin remains scarce. These fishing communities traditionally crafted fish skin garments, essential to their subsistence and spiritual life, adorning them with protective motifs. While artistic and cultural aspects of these belongings have been explored, their dyeing techniques remain understudied. This multidisciplinary research examines natural colourants in fish skin artefacts from international museum collections, using historical textual research, ethnographic records, Native Traditional Knowledge, and previous dye analysis by museum conservators. Findings reveal a restricted but meaningful palette of red, blue, yellow, and black colourants, sourced from plants, minerals, and organic materials. Early dyers extracted blue from indigotin-rich plants such as Polygonum tinctorium, or from Commelina communis petals. Red hues were obtained from Carthamus tinctorius petals, introduced through Silk Route trade networks, or from minerals like red ochre. Black was derived from carbon black, while riverine minerals were ground with dry fish roe diluted with water to create additional colour variations. This study first reviews fish skin use in Amur River Indigenous cultures, explores nineteenth-century dyeing materials and techniques, and finally considers broader implications for Indigenous material heritage. Full article

This study presents a sustainable, environmentally friendly synthetic route for the production of key intermediates in losartan using palladium nanoparticles (PdNPs) derived from a brown seaweed, Sargassum incisifolium, as a recyclable nanocatalyst. A key intermediate, biaryl, was synthesized with an excellent yield (98%) via Suzuki–Miyaura coupling between 2-bromobenzonitrile and 4-methylphenylboronic acid, catalyzed using bio-derived PdNPs under mild conditions. Subsequent bromination using N-bromosuccinimide (NBS) under LED light, followed by imidazole coupling and tetrazole ring formation, allowed for the production of losartan with an overall yield of 27%. The PdNP catalyst exhibited high stability and recyclability, as well as strong catalytic activity, even at lower loadings, and nitrosamine formation was not detected. While the overall yield was lower than that of traditional industrial methods, this was due to the deliberate avoidance of the use of toxic reagents, hazardous solvents, and protection/deprotection steps commonly used in conventional routes. This trade-off marks a shift in pharmaceutical process development, where environmental and safety considerations are increasingly prioritized in line with green chemistry and regulatory frameworks. This study provides a foundation for green scaling up strategies, incorporating sustainability principles into drug synthesis. Full article

Cloud computing revolutionizes the way computing resources are managed, delivered, and accessed as it aims to provide the notion of unlimited resources (e.g., computing services, storage, applications, etc.) over the internet with a flexible model for accessing them. Cloud computing performs the required computations at its data centers, and the remote end-users are highly dependent on the provided internet facilities by the network providers like Internet Service Providers (ISPs) to avail the services provided by the cloud. In most cases, cloud-based architecture cannot ensure the Quality of Service (QoS) aspects of the provided remotely located services due to the high dependencies on the internet. Such limitations of traditional cloud computing models can be addressed with the advent of edge computing by bringing computation closer to the consumer or by considering data storage closer to the source of data generation. While edge computing effectively addresses latency issues inherent in cloud computing, it does not entirely overcome the requirement for high computational resources and related network dependency associated with accessing cloud services. On the traditional internet, it is a challenge for the intermediary ISPs to ensure the QoS required by their direct and indirect end-users to avail cloud services. The software-defined wide area network (SD-WAN) has emerged as a promising architecture for the next generation of wide area networks (WANs) where providers can enhance their cooperation, specifically in ensuring QoS aspects. In this article, a QoS-aware routing protocol using SD-WAN is proposed to fulfill the stringent QoS requirements for cloud services. Additionally, a blockchain-based trading model is proposed to address the challenge of providing financial benefits to the ISPs in an automated and trustworthy manner for their provided support in satisfying the required QoS with additional or special workload of routing state management. Finally, this research leverages the dynamic network management capability to address the challenges of accessing cloud services with any QoS requirement. Full article

Economic growth and environmental sustainability represent two critical components of sustainable development. This study analyzed the impacts of China’s international economic circulation (IC) on value added and carbon emissions, using a global value chain accounting framework, seeking to answer how to achieve the dual goals of economic growth and carbon emissions reductions through IC routes: traditional, simple, and complex international economic circulations (TIC, SIC, CIC). The major findings are as follows: (1) The contribution of China’s IC to the domestic economy has decreased since 2008, while its contribution to foreign economies continues to increase. Exports mainly promote domestic economic growth through TIC, while imports mainly promote foreign economic growth through SIC. (2) The carbon emissions embodied in China’s IC through exports are 2.1–4.5 times higher than those in imports. The impact of SIC on the embodied carbon emissions in exports is higher than that in imports, while the impact of CIC in exports is equivalent to that in imports. (3) Although China is a net exporter of carbon emissions, through certain routes, China’s bilateral trade with countries such as Korea, Australia, Malaysia, and Russia are conducive to China’s carbon emissions reductions. These findings provide scientific evidence for the design of trade and carbon emissions mitigation policies. Full article

Underwater acoustic sensor networks (UASNs) play an increasingly crucial role in both civilian and military fields. However, existing routing protocols primarily rely on node position information for forwarding decisions, neglecting link quality and energy efficiency. To address these limitations, we propose a fuzzy logic reasoning adaptive forwarding (FLRAF) routing protocol for three-dimensional (3D) UASNs. First, the FLRAF method redefines a conical forwarding region to prioritize nodes with greater effective advance distance, thereby reducing path deviations and minimizing the total number of hops. Unlike traditional approaches based on pipeline or hemispherical forwarding regions, this design ensures directional consistency in multihop forwarding, which improves transmission efficiency and energy utilization. Second, we design a nested fuzzy inference system for forwarding node selection. The inner inference system evaluates link quality by integrating the signal-to-noise ratio and some metrics related to the packet reception rate. This approach enhances robustness against transient fluctuations and provides a more stable estimation of link quality trends in dynamic underwater environments. The outer inference system incorporates link quality index, residual energy, and effective advance distance to rank candidate nodes. This multimetric decision model achieves a balanced trade-off between transmission reliability and energy efficiency. Simulation results confirm that the FLRAF method outperforms existing protocols under varying node densities and mobility conditions. It achieves a higher packet delivery rate, extended network lifetime, and lower energy consumption. These results demonstrate that the FLRAF method effectively addresses the challenges of energy constraints and unreliable links in 3D UASNs, making it a promising solution for adaptive and energy-efficient underwater communication. Full article

Effective and evidence-based biosecurity measures are essential to prevent trade disruption, protect industries and contain the chains of biological invasions. There are increasing demands for analysts to use quantitative data to monitor this system, with the goals of early detection and forecasting. However, standard approaches often struggle with the incomplete and complex nature of trade data, which tends to include non-normality, temporal and spatial autocorrelation, and limited observations. In this study, a time series of open access import data spanning three years was used to generate measures of diversity indices and network topology, alongside detailed analyses of import pathways and interception records of harmful organisms, revealing their dynamic patterns across different trade routes. Patterns of annual seasonality were evident across the board. A combination of Inverse Simpson’s diversity and network Linkage density optimised the monitoring power of import data for interceptions of harmful taxa. Traditional correlations to total number of interceptions remained intractable, but machine learning tools demonstrated predictive power to forecast these temporal patterns. Combined, these methods provide a novel approach for biosecurity monitoring in plant and animal trade across international borders. These indicators complement more conventional economic metrics, giving actionable insights into trade complexity and biosecurity status. Full article

This paper considers a decentralized and autonomous wireless network of low SWaP (size, weight, and power) fixed-wing UAVs (unmanned aerial vehicles) used for remote exploration and monitoring of targets in an inaccessible area lacking communication infrastructure. Here, the UAVs collaborate to find target(s) and use routing protocols to forward the sensed data of target(s) to an aerial base station (BS) in real-time through multihop communication, which can then transmit the data to a control center. However, the unpredictability of target locations and the highly dynamic nature of autonomous, decentralized UAV networks result in frequent route breaks or traffic disruptions. Traditional routing schemes cannot quickly adapt to dynamic UAV networks and can incur large control overhead and delays. In addition, their performance suffers from poor network connectivity in sparse networks with multiple objectives (exploration and monitoring of targets), which results in frequent route unavailability. To address these challenges, we propose two routing schemes: Pipe routing and TC-Pipe routing. Pipe routing is a mobility-, congestion-, and energy-aware scheme that discovers routes to the BS on-demand and proactively switches to alternate high-quality routes within a limited region around the routes (referred to as the “pipe”) when needed. TC-Pipe routing extends this approach by incorporating a decentralized topology control mechanism to help maintain robust connectivity in the pipe region around the routes, resulting in improved route stability and availability. The proposed schemes adopt a novel approach by integrating the topology control with routing protocol and mobility model, and rely only on local information in a distributed manner. Comprehensive evaluations under diverse network and traffic conditions—including UAV density and speed, number of targets, and fault tolerance—show that the proposed schemes improve throughput by reducing flow interruptions and packet drops caused by mobility, congestion, and node failures. At the same time, the impact on coverage performance (measured in terms of coverage and coverage fairness) is minimal, even with multiple targets. Additionally, the performance of both schemes degrades gracefully as the percentage of UAV failures in the network increases. Compared to schemes that use dedicated UAVs as relay nodes to establish a route to the BS when the UAV density is low, Pipe and TC-Pipe routing offer better coverage and connectivity trade-offs, with the TC-Pipe providing the best trade-off. Full article

As a distinct musical form, blues music from the Mississippi Delta has been extensively studied across various academic disciplines. While much of this attention has treated blues primarily as an auditory experience, I argue that it represents far more than just sound or entertainment. This research project examines Delta blues as a comprehensive cultural phenomenon, exploring its evolution through a series of distinct diffusionary pathways that reveal complex global interactions and transcultural exchange. This study posits that Delta blues emerged from a broad cultural milieu, shaped by multiple layers of geographical processes ranging from ancient African trade routes to twentieth-century migration patterns. I position Delta blues within the context of the African diaspora, emphasizing not only its strong roots in African and African American cultural traditions but also its crucial role as a vehicle for cultural resistance and consciousness-raising. By mapping the evolution of blues music and culture through specific circuits of exchange, I illuminate the intricate interrelationships between different peoples and places across time and space. This approach reveals how global interactions generated a unique musical and cultural expression that both embodies and transcends the complex social dynamics inherent in the African diaspora. Full article

The illegal trade in leopard and lion parts is a major threat to felid conservation across Africa, especially in under-researched areas like francophone West Africa. Between April and June 2024, we conducted surveys in 16 cities and 46 markets in Côte d’Ivoire, interviewing 39 sellers and 14 users of felid products. We found leopard and lion parts in 42.7% and 25% of stalls, respectively. The illegal trade is driven by the demand for felid products for traditional purposes, with both species holding strong symbolic values. Products were often trafficked through informal networks and sourced from Sahelian neighboring countries like Mali and Burkina Faso. We identified some key trade routes across West Africa and beyond. Without effective control measures, this illegal trade could accelerate the decline of West Africa’s remaining large felid populations. We recommend establishing a regional database of confiscated felid parts for genetic tracing and developing standardized questionnaires for use during traffickers’ arrests to gain further insights into their operations. Additionally, targeted behavioral change campaigns should be implemented to address corruption, increase enforcement agencies’ interest and capacity, and shift the practices of traditional practitioners toward sustainable alternatives. Training law enforcement officers, raising awareness among key communities, and increasing cross-border collaboration and controls are critical to providing a more comprehensive understanding of the trade dynamics in the region. Full article

This study investigates the phylogenetic and geographical distribution of wild food plants (WFPs) across 30 Mediterranean and North African (MENA) regions, focusing on the intersection of evolutionary lineage, ecological adaptation, and cultural utilization. A phylogenetic analysis of 111 genera of WFPs used in traditional diets reveals clusters reflecting shared ancestry, functional adaptations, and ecological resilience. Key regions such as Lebanon and Ikaria stand out as potential centers for the diversity of wild food plant use, suggesting that the Eastern Mediterranean may be a primary origin area, especially for species adapted to semi-arid climates. Major plant families including Lamiaceae, Rosaceae, and Fabaceae form distinct clusters that underscore their common ancestry and adaptability, making them foundational to traditional diets and medicinal applications across various environments. Geographical analysis indicates historical connections, such as those between Malta and Egypt, supporting the hypothesis that ancient trade routes influenced the spread and cultural exchange of wild food plant use across the Mediterranean. The study emphasizes the integration of phylogenetic and ethnobotanical perspectives, shedding light on how biodiversity, ecological adaptation, and cultural practices intersect in these regions. This research demonstrates that WFPs serve as both ecological and cultural assets, crucial for preserving traditional diets and supporting biodiversity conservation amid environmental changes. Integrating evolutionary and cultural knowledge can enrich ecological understanding and contribute to the sustainable use of plant resources in the MENA regions. Full article