Search Results (128)

Numerous protocols have emerged to address the energy depletion problem in Wireless Sensor Networks (WSNs). Among these protocols, the Dynamic Multi-Hop Routing (DMR) protocol adopts a dynamic technique for routing data across the network. The use of the DMR protocol has shown promising results in reducing energy consumption, prolonging the network lifetime, and increasing throughput. To improve the performance of WSNs, this paper proposes the Enhanced Dynamic Multi-Hop Routing (EDMR) protocol as a modification of the DMR protocol. The EDMR protocol introduces an effective sleeping mechanism that selectively deactivates clusters that do not generate significantly updated data for a specific duration. This mechanism reduces redundant transmissions, thereby saving energy and prolonging the network lifetime. The EDMR protocol incorporates static and dynamic approaches to support two major categories of applications: monitoring and event-driven applications. The proposed protocol is evaluated against the DMR protocol, the Enhanced Dynamic Multi-Hop Technique (EMDHT-LEACH) protocol, and the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol. The simulation results demonstrate that the EDMR protocol mitigates energy depletion, extends the network lifetime, increases stability, and improves network throughput toward the Base Station (BS), while reducing packet redundancy compared with the other protocols. Full article

Mining by-products present both an environmental challenge and a resource opportunity. This review investigates their potential application in road pavement construction, focusing on materials such as fly ash, slag, sulphur, red mud, tailings, and silica fume. Drawing from laboratory and field studies, the review examines their roles across pavement layers—subgrade, base, subbase, asphalt mixtures, and rigid pavements—emphasising mechanical properties, durability, moisture resistance, and ageing performance. When properly processed or stabilised, many of these wastes meet or exceed conventional performance standards, contributing to reduced use of virgin materials and greenhouse gas emissions. However, issues such as variability in composition, leaching risks, and a lack of standardised design protocols remain barriers to adoption. This review aims to consolidate current research, evaluate practical feasibility, and identify directions for future studies that would enable the responsible and effective reuse of mining waste in transportation infrastructure. Full article

Sustainable agriculture and food security are challenged by the indiscriminate use of synthetic nitrogen (N₂) fertilizers, inefficient water management, and land degradation. Hydroponic cultivation uses nutrient-rich aqueous media and is a climate-resilient and resource-efficient alternative to traditional farming methods, whose dependence on synthetic N₂ fertilizers reduces their long-term sustainability. Biological nitrogen fixation (BNF), which is mediated by diazotrophs that reduce atmospheric N₂ to plant-available ammonium, has emerged as a sustainable alternative to synthetic N₂ input in hydroponic systems. This review discusses the integration of BNF into hydroponic systems by exploring the functional diversity of diazotrophs, root–microbe interactions, and environmental constraints. It further highlights recent advances in strain improvement, microbial consortia development, nitrogenase protection, and genome editing tools, novel bioformulation strategies to enhance microbial compatibility with hydroponic nutrient regimes, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Key challenges, such as microbial leaching, nitrate-induced inhibition of nitrogenase activity, and the absence of standardized biostimulant protocols, are discussed. Case studies on staple crops have demonstrated enhanced NUE and yield productivity following diazotroph applications. This review concludes with future perspectives on synthetic biology, regulatory policies, and omics-based tools for the real-time assessment of N₂ fixation and microbial functionality. Full article

The growing demand for rare earth elements (REEs) in high-tech and green energy sectors has prompted renewed exploration of unconventional sources. Drill cuttings, which are commonly discarded during subsurface drilling, are increasingly recognized as a potentially valuable, underutilized secondary REE reservoir. This review adopts a mineral-first lens to assess REE occurrence, extractability, and recovery strategies from drill cuttings across various lithologies. Emphasis is placed on how REEs associate with specific mineral host phases ranging from ion-adsorbed clays and organically bound forms to structurally integrated phosphates, each dictating distinct leaching pathways. The impact of drilling fluids on REE surface chemistry and mineral integrity is critically examined, alongside an evaluation of analytical and extraction methods tailored to different host phases. A scenario-based qualitative techno-economic assessment and a novel decision-tree framework are introduced to align mineralogy with optimal recovery strategies. Limitations in prior studies, particularly in characterization workflows and mineralogical misalignment in leaching protocols, are highlighted. This review redefines drill cuttings from industrial waste to a strategic resource, advocating for mineralogically guided extraction approaches to enhance sustainability in the critical mineral supply chain. Full article

Entomopathogenic fungus-based biopesticides are an excellent alternative to synthetic pesticides and are widely used in insect pest control. With the transformations of the agri-food system, it is important to consider the One Health approach, which recognizes that health threats are shared at the interface between people, animals, plants, and the environment. The safety and environmental impact of fungi-based insecticides should be assessed comprehensively, taking into account not only their effects on non-target organisms and human health but also their environmental fate. This includes how these substances degrade, persist, or dissipate in soil, water, and air and their potential to bioaccumulate or leach into groundwater. Such assessments are essential to ensure that their long-term use does not pose unintended risks to ecosystems or public health. This systematic review aims to identify and analyze available studies on the potential One Health hazards associated with fungal biopesticides. A total of 134 articles were selected: 84 bioassay articles (63%), 36 case reports (27%), 10 field studies (7%), and 4 other types of studies (3%). Of these articles, 59 were studies on vertebrate animals and 65 studies on invertebrate animals, 6 studies on diverse organisms, 2 studies focused specifically on risk assessment for non-target organisms in the environment, while 2 other studies looked at the toxicological hazards associated with human exposure to the metabolites of the fungus present in air. The United States had the highest number of publications (33). Beauveria bassiana and Metarhizium anisopliae followed by the fungi Cordyceps fumosorosea (Paecilomyces fumosoroseus) and B. brongniartii were the most prevalent fungal species in the studies. This review highlights that case reports of infections in humans and other vertebrates by fungi are not related to the use of fungal biopesticides. A predominance of studies with bees was identified due to the importance of these insects as pollinators. The findings indicate that fungal biopesticides pose minimal risks when used appropriately. Nevertheless, the necessity for standardized safety assessments is emphasized. In order to ensure greater effectiveness, it is essential to develop unified protocols and bioassays with specific risk indicators aligned with the One Health approach. This includes evaluating potential effects on pollinators, vertebrate toxicity, and the environmental persistence of metabolites. In future research, the development of integrated guidelines that simultaneously consider human, animal, and environmental health is recommended. Full article

Wireless sensor networks face challenges such as energy consumption, scalability, security vulnerabilities, and communication range limitations, impacting their overall performance and reliability. To resolve these problems, energy-efficient protocols and adaptive sleep modes are implemented in wireless sensor networks (WSNs). Actually, LEACH clustering is widely regarded as one of the primary strategies to extend the lifetime of WSNs. However, clustering does not always guarantee optimal performance. In this paper, we demonstrate that clustering effectiveness is contingent on specific conditions related to several key parameters, including cluster density and the distance of nodes from the base station. Our research presents a mathematically validated analysis, supported by simulation results, that illustrates how clustering can enhance WSN performance, particularly in terms of network lifetime, throughput, and the timing of the first, middle, and last node deaths. Our findings indicate that LEACH is inefficient when nodes are within 80 m of the base station. Furthermore, clusters’ densities are related directly to the distance to the base station. Specifically, for distances less than 80 m, nodes should send their data individually; for distances between 83 and 123 m, a cluster density of two is most effective; and for distances between 123 and 149 m, the optimal density increases to three nodes. Full article

Sub-nano metal clusters have important physicochemical features that lead to a wide range of applications. Herein, we point out an unfailing reproducible protocol to synthesize ruthenium single-atom catalysts and ultra-small clusters supported on various silica–alumina mixed oxides. The catalysts were synthesized via a dendrimer-free, sonication-assisted route, with ruthenium loadings up to 2 wt%. Raman spectroscopy mapping revealed a wide coverage of the materials’ surfaces by ruthenium, while HAADF-STEM evidenced that 100% of the ruthenium was at the sub-nano scale, with up to 74% of the single atoms and metal clusters having an average size between 0.3 and 0.7 nm, independently of the support or the metal’s loading. These materials exhibited highly selective size-dependent catalytic performances in upgrading biomass-derived furfural into transportation biofuel additive 2,2′-difurfurylether, with turnover frequencies up to 1148 h⁻¹. Ruthenium single atoms and sub-nano clusters showed an exceptional resistance to sintering, with a size variation of ±0.1 nm before and after reaction, and no metal leaching was observed. Full article

Wireless sensor networks are at the center of scientific interest thanks to their ever-growing range of applications. The main weakness of wireless sensor networks is the restricted lifetime of their sensor nodes due to limited energy capacity. The extension of the lifespan of sensor nodes is pursued in various ways. One of them is the usage of protocols that achieve energy-efficient routing. LEACH is one of the pioneering protocols of this type and has numerous descendants. This research article focuses on energy-efficient routing protocols that are based on LEACH. Specifically, a study of LEACH along with many of its successors is provided. In addition, a novel protocol of this kind, named T-LEACH_SAS is introduced. This protocol combines the threshold-based approach for selecting cluster heads that was first introduced in T-LEACH, which is a well-known protocol, along with a mechanism for sleep–awake scheduling. The performance of T-LEACH_SAS is compared against that of both LEACH and T-LEACH via simulation tests that confirm that T-LEACH_SAS indeed provides a promising choice for energy-efficient routing in WSNs. Full article

Starch digestibility and the content of resistant starch (RS) play a crucial role in human health, particularly in relation to glycemic responses, insulin sensitivity, fat oxidation, and satiety. This study investigates the impact of processing methods on potato starch digestibility and RS content, focusing on two modification techniques: autoclaving and high hydrostatic pressure (HHP), followed by retrogradation at different temperatures. The research employs a comprehensive approach to characterize structural changes in starch samples using X-ray diffraction (XRD), attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy, and scanning electron microscopy (SEM). In turn, semi-dynamic in vitro digestion experiments based on the INFOGEST protocol were conducted to assess starch digestibility, while RS content was evaluated through enzymatic digestion of the non-RS fraction. SEM, XRD, and FTIR measurements reveal thermal processing appreciably affected starch architectures while HHP had a marginal effect. Further, the FTIR 1045/1022R ratio was found to be correlated with RS content measurements while reducing rapidly digestible starch (RDS). The findings led to the stipulation that thermal processing facilitates amylose leaching and granular disruption. In turn, retrogradation enabled the deposition of the amylose onto the disrupted structures which delineated their subsequent liability to enzymatic digestion. Conversely, HHP had minimal effects on granular architectures and amylose leaching. Overall, this research provides valuable insights for processing starch-based food products with the goal of increasing RS content, which may have significant implications for the food industry and nutritional science. Full article

Wireless Sensor Networks are formed by tiny, self-contained, battery-powered computers with radio links that can sense their surroundings for events of interest and store and process the sensed data. Sensor nodes wirelessly communicate with each other to relay information to a central base station. Energy consumption is the most critical parameter in Wireless Sensor Networks (WSNs). Network lifespan is directly influenced by the energy consumption of the sensor nodes. All sensors in the network send and receive data from the base station (BS) using different routing protocols and algorithms. These routing protocols use two main types of clustering: hierarchical clustering and flat clustering. Consequently, effective clustering within Wireless Sensor Network (WSN) protocols is essential for establishing secure connections among nodes, ensuring a stable network lifetime. This paper introduces a novel approach to improve energy efficiency, reduce the length of network connections, and increase network lifetime in heterogeneous Wireless Sensor Networks by employing the K-Nearest Neighbours (KNN) algorithm to optimise node selection and clustering mechanisms for four protocols: Low-Energy Adaptive Clustering Hierarchy (LEACH), Stable Election Protocol (SEP), Threshold-sensitive Energy Efficient sensor Network (TEEN), and Distributed Energy-efficient Clustering (DEC). Simulation results obtained using MATLAB (R2024b) demonstrate the efficacy of the proposed K-Nearest Neighbours algorithm, revealing that the modified protocols achieve shorter distances between cluster heads and nodes, reduced energy consumption, and improved network lifetime compared to the original protocols. The proposed KNN-based approach enhances the network’s operational efficiency and security, offering a robust solution for energy management in WSNs. Full article

Infiltration swales are a prospective key component of water-sensitive urban planning. The utilization of appropriate soil amendments is intended to facilitate the retention of pollutants from the stormwater runoff of traffic areas. Little is known about the possibility of utilizing processed construction and demolition waste (CDW) as an amendment to improve pollutant retention. We conducted batch and field tests to investigate (i) the leaching of metals and other elements from soil substrates containing CDW and (ii) their retention potential for copper (Cu) and zinc (Zn) when charged with real traffic area runoff. To gain a comprehensive understanding of the chemical interactions, we (iii) employed sequential extractions using an optimized protocol from treated and untreated soil substrates. In batch tests, the potential of vanadium leaching from technosols amended with brick-dominated CDW was apparent. When charged with traffic area runoff, the retentions of Cu and Zn in the technosols were comparable to those of the control soil without CDW. However, the simulation of high rainfall intensities reduced Cu and Zn retention in the technosols and the control. The results from the subsequent sequential extraction of Cu and Zn imply shifts in the chemical binding in the technosols compared to the control. Full article

Giant unilamellar vesicles (GUVs) are versatile cell models in biomedical and environmental research. Of the various GUV production methods, hydrogel-assisted GUV production is most easily implemented in a typical biological laboratory. To date, agarose, polyvinyl alcohol, cross-linked dextran-PEG, polyacrylamide, and starch hydrogels have been used to produce GUVs. Some leach and contaminate the GUVs, while others require handling toxic material or specialised chemistry, thus limiting their use by novices. Alternative hydrogel materials could address these issues or even offer novel advantages. To facilitate discovery, we replaced the manual spreading of reagents with controlled drop-casting in glass Petri dishes and polystyrene multi-well plates, allowing us to rapidly screen up to 96 GUV-production formulations simultaneously. Exploiting this, we rapidly evaluated assorted biomedical hydrogels, including PEG-DA, cross-linked hyaluronic acid, Matrigel, and cross-linked DNA. All of these alternatives successfully produced GUVs. In the process, we also developed a treatment for recycling agarose and polyvinyl alcohol hydrogels for GUV production, and successfully encapsulated porcine liver esterase (PLE-GUVs). PLE-GUVs offer a novel method of GUV labelling and tracing, which emulates the calcein-AM staining behaviour of cells. Our results highlight the utility of our protocol for potentiating substrate material discovery, as well as protocol and product development. Full article

In this paper, we propose an enhanced clustering protocol that integrates an improved K-means with a Mobility-Aware Cluster Head-Election Scored (IK-MACHES) algorithm, designed for extending the lifetime and operational efficiency of Wireless Sensor Network (WSN) with mobility. Variety approaches applying Low Energy Adaptive Clustering Hierarchy (LEACH) often struggle to manage optimal energy distribution due to their static clustering and limited cluster head (CH) selection criteria, primarily focusing on the proximity of residual energy or distance. Thus, this paper proposes an algorithm that takes into account both the residual energy of sensor nodes and the distance between the cluster’s central point to the base station (BS), which ultimately enhances the network’s lifetime. Additionally, our approach incorporates mobility considerations, enhancing the adaptability of the mobility environments, such as autonomous vehicular networks. Our proposed method first constructs the cluster’s configuration and then elects the CH applying an improved K-means clustering algorithm—one of the machine learning methods—integrated with a proposed IK-MACHES mechanism. Three CH scoring strategies in the proposed IK-MACHES protocol evaluate the residual energy of the nodes, their distance to the BS and the cluster central point, and relative node’s mobility. The simulation results demonstrate that the proposed approach improves performance in terms of the first node dead (FND) and 80% alive nodes metrics with mobility, compared to other LEACH protocols such as classical LEACH, LEACH-B, Improved-LEACH, LEACH with K-means, Particle Swarm Optimization (PSO), and LEACH-GK protocol, thereby enhancing network lifetime through optimal CH selection. Full article

Precision agriculture (PA), leveraging wireless sensor networks (WSNs) for efficient data collection, is set to revolutionize intelligent farming. However, challenges such as energy efficiency, data collection time, data quality, redundant data transmission, latency, and limited WSN lifespan persist. We propose a novel edge computing-driven WSN framework (ECDWF) for PA, designed to enhance network longevity by optimizing data transmission to the base station (BS) and enhancing energy dissipation by abolishing data redundancy through aggregation. This framework involves a two-step data aggregation process: within clusters, where the cluster head (CH) aggregates data, and at a central network point, where an edge computing-enabled gateway node (GN) performs further aggregation. Our MATLAB simulation evaluates the proposed ECDWF against the Low-energy adaptive clustering hierarchy (LEACH) protocol and two classic sensing strategies, Effective Node Sensing (ENS) and Periodically Sensing with All Nodes (PSAN). Results reveal significant energy efficiency, quality of data (QoD) transmission, and network lifespan improvements. Due to reduced long-range transmissions, nodes in our scheme dissipate energy over 2500 rounds, compared to 1000 rounds in LEACH. Our method sends data packets to the CH and base station (BS) for 2500 rounds at 3.6 × 10¹⁰ bits, while LEACH stops at 1000 rounds at 2 × 10¹⁰ bits data transmission rate. Our approach improves network stability and lifetime, with the first node dying at 2070 rounds, versus 999 rounds in LEACH, and the last node remaining functional until 2476 rounds compared to 1000 rounds in LEACH. Our proposed system, ECDWF, outperforms PSAN and ENS in latency, data collection time (DCT), and energy usage. At 50 Mbps, the communication latency of ECDWF is just 8 s, compared to 24 s for ENS and 45 s for PSAN. ECDWF maintains a QoD of 100% across various valid sensor and node counts, surpassing ENS and PSAN. Our contribution integrates edge computing with WSN for PA, enhancing energy utilization and data aggregation. This approach effectively tackles data redundancy, transmission efficiency, and network longevity, providing a robust solution for precision agriculture. Full article

The Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is a widely used method for managing energy consumption in Wireless Sensor Networks (WSNs). However, it has limitations that affect network longevity and performance. This paper presents an improved version of the LEACH protocol, termed MFG-LEACH, which incorporates the Mean Field Game (MFG) theory to optimize energy efficiency and network lifetime. The proposed MFG-LEACH protocol addresses the imbalances in energy consumption by modeling the interactions among nodes as a game, where each node optimizes its transmission energy based on the collective state of the network. We conducted extensive simulations to compare MFG-LEACH with Enhanced Zonal Stable Election Protocol (EZ-SEP), Energy-Aware Multi-Hop Routing (EAMR), and Balanced Residual Energy routing (BRE) protocols. The results demonstrate that MFG-LEACH significantly reduces energy consumption and increases the number of packets received across different node densities, thereby validating the effectiveness of our approach. Full article