Search Results (178)

Wireless sensor networks have become a vital technology that is extensively applied across multiple industries, including agriculture, industrial operations, and smart cities, as well as residential smart homes and environmental monitoring systems. Security threats emerge in these systems through hidden routing-level attacks such as Wormhole and Sinkhole attacks. The aim of this research was to develop a methodology for detecting security incidents in WSNs by conducting real-time analysis of Wormhole and Sinkhole attacks. Furthermore, the paper proposes a novel detection methodology combined with architectural enhancements to improve network robustness, measured by hop counts, delays, false data ratios, and route integrity. A real-time WSN infrastructure was developed using ZigBee and Global System for Mobile Communications/General Packet Radio Service (GSM/GPRS) technologies. To realistically simulate Wormhole and Sinkhole attack scenarios and conduct evaluations, we developed a modular cyber–physical architecture that supports real-time monitoring, repeatability, and integration of ZigBee- and GSM/GPRS-based attacker nodes. During the experimentation, Wormhole attacks caused the hop count to decrease from 4 to 3, while the average delay increased by 40%, and false sensor readings were introduced in over 30% of cases. Additionally, Sinkhole attacks led to a 27% increase in traffic concentration at the malicious node, disrupting load balancing and route integrity. The proposed multi-stage methodology includes data collection, preprocessing, anomaly detection using the 3-sigma rule, and risk-based decision making. Simulation results demonstrated that the methodology successfully detected route shortening, packet loss, and data manipulation in real time. Thus, the integration of anomaly-based detection with ZigBee and GSM/GPRS enables a timely response to security threats in critical WSN deployments. Full article

In relay-assisted Industrial Internet of Things (IIoT) systems with ultra-reliable low-latency communication (uRLLC) requirements, finite blocklength coding imposes stringent resource constraints. In this work, the packet error probability (PEP) and blocklength allocation across two-hop links are jointly optimized to minimize total blocklength (resource consumption) while satisfying reliability, latency, and throughput requirements. The original multi-variable problem is decomposed into two tractable subproblems. In the first subproblem, for a fixed total blocklength, the achievable rate is maximized. A near-optimal PEP is first derived via theoretical analysis. Subsequently, theoretical analysis proves that blocklength must be optimized to equalize the achievable rates between the two hops to maximize system performance. Consequently, the closed-form solution to optimal blocklength allocation is derived. In the second subproblem, the total blocklength is minimized via a bisection search method. Simulation results show that by adopting near-optimal PEPs, our approach reduces computation time by two orders of magnitude while limiting the achievable rate loss to within 1% compared to the exhaustive search method. At peak rates, the hop with superior channel conditions requires fewer resources. Compared with three baseline algorithms, the proposed algorithm achieves average resource savings of 21.40%, 14.03%, and 17.18%, respectively. Full article

Grapevine (Vitis vinifera L.) cultivation is an important agricultural sector worldwide. Its expansion into new areas, like Kazakhstan, brings significant phytosanitary risks. Viroids, such as grapevine yellow speckle viroid 1 (GYSVd-1) and hop stunt viroid (HSVd), are RNA pathogens that threaten vineyard productivity. They can cause a progressive decline through latent infections. Traditional diagnostic methods are usually targeted and therefore not suitable for thorough surveillance. In contrast, modern high-throughput sequencing (HTS) methods often face challenges due to their high costs and complicated sample preparation, such as ribosomal RNA (rRNA) depletion. This study introduces a simplified diagnostic workflow that overcomes these barriers. We utilized the latest Oxford Nanopore V14 cDNA chemistry, which is designed to prevent internal priming, by substituting a targeted oligo(dT)VN priming strategy to facilitate the sequencing of non-polyadenylated viroids from total RNA extracts, completely bypassing the rRNA depletion step and use of random oligonucleotides for c DNA synthesis. This method effectively detects and identifies both GYSVd-1 and HSVd. This workflow significantly reduces the time, cost, and complexity of HTS-based diagnostics. It provides a powerful and scalable tool for establishing strong genomic surveillance and phytosanitary certification programs, which are essential for supporting the growing viticulture industry in Kazakhstan. Full article

This paper addresses the critical challenge of time management in wireless sensor networks (WSNs) applied to industrial process control. Although wireless technologies have gained ground in industrial monitoring, their adoption in control applications remains limited due to concerns around reliability and timing accuracy. This study proposes a practical, low-cost solution based on commercial off-the-shelf (COTS) components, leveraging the IEEE 802.15.4-2020 standard in Time-Slotted Channel-Hopping (TSCH) mode. A custom time management algorithm is developed and implemented on STM32 microcontrollers paired with AT86RF212B transceivers. The proposed system ensures a sub-millisecond synchronization drift across nodes by dividing communication into a structured slot frame and implementing precise scheduling and enhanced beacon-based synchronization. Validation is performed through experimental setups monitored with logic analyzers, demonstrating a time drift consistently below 600 microseconds. The results confirm the feasibility of using synchronized wireless nodes for real-time industrial control tasks, suggesting that further improvements in hardware precision could enable even tighter synchronization and broader applicability in fast and critical processes. Full article

Optimal path planning algorithms offer substantial benefits in high-density storage (HDS) systems in modern smart manufacturing. However, traditional algorithms may encounter significant optimization challenges due to intricate architectural configurations and traffic constraints of the HDS system. This paper addresses these issues by introducing a two-step novel path planning method: (1) the mesh-tree grid map topological representation and the (2) Lattice-Hopping (LH) algorithm. The proposed method first converts the layout of an HDS system into a mesh-tree grid hierarchical structure by capturing and simplifying the spatial and geometrical information as well as the traffic constraints of the HDS system. Then, the LH algorithm is proposed to find optimal shipping path by leveraging the global connectivity of main tracks (main track priority) and the ‘jumping’ mechanism of sub-tracks. The main track priority and the ‘jumping’ mechanism work together to save computational complexity and enhance the feasibility and optimality of the proposed method. Numerical and case studies are performed to demonstrate the superiorities of our method to properly modified benchmark algorithms. Algorithm scalability, robustness, and operational feasibility for industrial production in modern smart manufacturing are also displayed and emphasized. Full article

Four different yeast strains were isolated from industrial gluten-free bread (GFB) purchased from a local supermarket. These strains, including Hyphopichia burtonii, Wickerhamomyces anomalus, Saccharomycopsis fibuligera, and Cyberlindnera fabianii, are responsible for spoilage, which consists of white powdery and filamentous colonies due to the fragmentation of hyphae into short-length fragments (dust-type spots) that is typical of the spoilage produced by chalk yeasts. The isolated strains were identified using genomic analysis. Among them, C. fabianii was also isolated, which is a rare ascomycetous opportunistic yeast species with low virulence attributes, uncommonly implicated in bread spoilage. The yeast growth was studied in vitro on Malt Extract Agar (MEA) at two temperatures (20 and 25 °C) and at different Aws (from 0.99 to 0.90). It was inferred that the temperature did not influence the growth. On the contrary, different Aws reduced the growth, but all the yeast strains could grow until a minimum Aw of about 0.90. Different preservatives (ethanol, hop extract, and sorbic and propionic acids) were used to prevent the growth. In MEA, the growth was reduced but not inhibited. In addition, the vapor-phase antimicrobial activity of different preservatives such as ethanol and hop extract was studied in MEA. Both preservatives completely inhibited the yeast growth either at 20 or at 25 °C. Both preservatives were found in GFB slices. Contrary to hop extract, 2% (v/w) ethanol completely inhibited all the strains. The spoilage was also confirmed by the presence of various compounds typically present in yeasts, derived from sugar fermentation and amino acid degradation. These compounds included alcohols, ketones, organic acids, and esters, and they were identified at higher concentrations in the spoiled samples than in the unspoiled samples. The concentration of acetic acid was low only in the spoiled samples, as this compound was consumed by yeasts, which are predominately present in the spoiled samples, to produce acetate esters. Full article

Industry 4.0 has transformed manufacturing and automation by integrating cyber–physical systems with the Industrial Internet of Things (IIoT) for real-time monitoring, intelligent control, and data-driven decision making. The IIoT increasingly relies on IEEE 802.15.4e Time-Slotted Channel Hopping (TSCH) to achieve reliable, low-latency, and energy-efficient industrial communications. The 6TiSCH protocol stack integrates scheduling and routing to optimize transmissions for resource-constrained devices, enhancing Quality of Service (QoS) in IIoT deployments. This paper proposes an innovative adaptive and cross-layer slotframe allocation technique for 6TiSCH networks, dynamically scheduling cells based on node hop distance, queue backlog, predicted traffic load, and link quality metrics. By dynamically adapting to these parameters, the proposed method significantly improves key QoS metrics, including end-to-end latency, packet delivery ratio, and network lifetime. The mechanism integrates real-time queue backlog monitoring, link performance analysis, and energy harvesting awareness to optimize cell scheduling decisions proactively. The results demonstrate that the proposed strategy reduces end-to-end latency by up to 32%, enhances PDR by up to 27%, and extends network lifetime by up to 10% compared to state-of-the-art adaptive scheduling solutions. Full article

Hop by-products constitute a significant part of biomass in cones production for the brewing industry. The phenolic compounds (PCs) they contain can be used in the food and pharmaceutical industries but require qualitative and quantitative analysis. The aim of this study was to investigate the extent to which phenolic compounds profiles depend on cultivar, plant organ, and plant level. This paper shows for the first time that for hop, it is not only the plant organ that is important for PC content, but also the level from which it is obtained. Metabolites were investigated in cones, leaves, and stalks at three levels of the plant in Polish hop cultivars (Marynka, Lubelski, and Magnum). The PC content showed a differentiation due to the cultivar of hops, their anatomical part, and position in the plant (level), which reflects the degree of organ maturity. The total PC was the highest in leaves (up to 922 mg/100 g), while lower contents were found in cones (up to 421 mg/100 g) and stalks (up to 105 mg/100 g). The main PCs of leaves were kaempferol-3-glucoside (up to 328 mg/100 g) and rutin (up to 293 mg/100 g), while rutin dominated in cones (up to 209 mg/100 g). Full article

Humulus lupulus L. (common hop) is a herbaceous plant whose female inflorescences, commonly called hop “cones”, are traditionally used in Bulgaria to prepare sourdough starters or “kvass”. Drawing from a review of historical and linguistic sources and ethnographic information collected by the authors, this study aims to define the traditional preparation of bread with hop sourdough, starting from the preparation of the hop cone decoction. Archival materials and early cookbooks attest to a rich tradition where hop-infused bread was valued for its distinctive flavor and preservative qualities. Fieldwork conducted in Bulgaria and among Bulgarian diasporas in Moldova provided insights into the continuity of these practices, underscoring the persistence of these traditional preparations despite modern industrial pressures. Ethnographic interviews and participant observations highlighted the ritualistic preparation of hop kvass and its role in community identity. The effect of hops on dough’s rheological properties and the quality features of bread were also reviewed. An increase in dough stability and resistance to elongation were generally reported, with a reduction in bread volume and porosity, especially with hop sourdough levels above 30%, but the incorporation of bioactive molecules was responsible for antioxidant, antimicrobial, and flavoring properties. Possible prospects for using hops in the food industry, based on the biological properties of this resource-rich plant, are outlined with a multidisciplinary approach. Full article

Hop (Humulus lupulus L.) is a crucial ingredient in beer, valued for its bitter acids and essential oils. Traditionally cultivated in temperate regions, hop production faces challenges from climate change, necessitating the exploration of new growing areas. This study evaluated the chemical quality of hop varieties grown in Brazil’s subtropical conditions to assess their suitability for brewing. Seven hop varieties (Cascade, Centennial, Columbus, Chinook, Comet, Fuggle, and Nugget) were analyzed for total α- and β-acids and essential oil composition. Bitter acids were quantified by spectrophotometric analysis, and volatile compounds were identified using gas chromatography coupled to mass spectrometry (GC-MS). Comet exhibited the highest a-acid level (10.54%), indicating strong bittering potential. Essential oil analysis revealed β-myrcene, (E)-caryophyllene, and α-humulene as predominant compounds. Centennial showed a distinct (E)-β-farnesene profile, a characteristic of noble hops. All varieties contained α- and β-selinene, suggesting a common metabolic pattern. The results indicate that Brazil has the potential to produce high-quality hops with suitable chemical profiles for brewing. As traditional hop-growing regions face climate-related challenges, hops cultivated in Brazil may offer a viable alternative for achieving the desired chemical composition required by the brewing industry. Full article

Natural compounds represent a fundamental source of antimicrobial agents with applications in numerous industries. This study investigates the antimicrobial properties of different fractions of extracts obtained from six hop varieties, as well as of certain compounds contained in hops and other plants. The results indicate that soft resins exhibit the strongest antibacterial activity among the hop-derived fractions evaluated, reaching a minimum MIC₉₀ value of 25 µg/mL (Fuggle variety) against Gram-positive bacteria (S. aureus) and 50 µg/mL (Chinook variety) against Gram-negative bacteria (E. coli). Furthermore, the composition of hops varies among varieties, resulting in divergent antimicrobial patterns, indicating the necessity for further research to elucidate the origins of these activities. Additionally, while hop-derived fractions exhibited noteworthy antibacterial properties, their antifungal activity against A. niger was found to be negligible. In addition, natural compounds such as carvacrol and thymol demonstrated the lowest MIC₉₀ values against E. coli (130 and 250 µg/mL, respectively) and S. aureus (280 and 250 µg/mL, respectively). Moreover, xanthohumol exhibited a better MIC₉₀ value against S. aureus (3 µg/mL), while no inhibitory effects were observed against E. coli. These insights highlight the necessity for further exploration of natural extracts in the development of new antimicrobial agents. Full article

Personalized learning resource recommendation is an essential component of intelligent tutoring systems. To address the issue of the plethora of learning resources and enhance the learner experience in intelligent tutoring systems, learning resource recommendation systems have been developed to model learners’ preferences. Despite numerous efforts and achievements in academia and industry toward more personalized learning, intelligent education tailored to individual learners still faces challenges, such as inadequate user representation and potential information loss during the aggregation of multi-source heterogeneous information features. In recent years, knowledge-graph-based recommendation systems have brought hope for mitigating these issues and achieving more accurate recommendations. In this paper, we propose a novel personalized learning resource recommendation method based on a knowledge graph named the Learner-Enhanced Knowledge Graph Attention (LKGA) network. This model enhances learner representation by extracting collaborative signals, where learning resources clicked by learners who have clicked the same resource are considered potential collaborative signals and are concatenated with the original learning resource features to form the initial entity set for the learner. Furthermore, during the entity aggregation process, each tail entity has different semantic expressions, and an attention mechanism is used to distinguish the importance of different neighbor entities. Additionally, residual connections are added in each hop of the learner’s aggregation process, with the information from the first hop added to each subsequent hop to reduce information loss. We applied the proposed LKGA model to a real-world dataset, and the experimental results fully validate the effectiveness of our model. Full article

The growing concern over the transmission of pathogens, particularly in high-risk environments such as healthcare facilities and public spaces, necessitates the development of effective and sustainable antimicrobial solutions. Traditional coatings often rely on metals, which despite their efficacy, pose significant environmental and economic challenges. This study explores the potential of bio-based alkyd resins, supplemented with natural antimicrobial bioadditives, as an eco-friendly alternative to traditional antibacterial and antiviral coatings. Specifically, alkyd formulations incorporating thymol and soft resins extracted from hops were evaluated for antimicrobial and antiviral efficacy, following ISO standards (ISO 22196:2007 and ISO 21702:2019, respectively). The coating formulations showed significant activity against Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus), and Influenza A (H3N2) virus, proving their potential for mitigating pathogen spread. These bio-based coatings not only reduce reliance on harmful chemicals but also align with circular economy principles by repurposing industrial by-products. This innovative approach represents a significant step toward greener antimicrobial technologies, with broad applications in healthcare, public infrastructure, and beyond, especially considering the rising zoonotic disease outbreaks. Full article

Ru–Zn catalysts exhibit excellent catalytic performance for the selective hydrogenation of benzene to cyclohexene and has been utilized in industrial production. However, the structure–performance relationship between Ru–Zn catalysts and benzene hydrogenation remains lacking. In this work, we focused on the evolution of Ru–Zn nanoparticles with size and Ru/Zn ratio. The structures of Ru nanoparticles and Ru–Zn bimetallic nanoparticles with different sizes were determined by the minima-hopping global optimization method in combination with density functional theory and high-dimensional neural network potential. Furthermore, we propose the growth mechanism for Ru nanoparticles and evolution processes for Ru–Zn bimetallic nanoparticles. Additionally, we analyzed the structural stability, electronic properties, and adsorption properties of Zn atoms. This work provides valuable reference and guidance for future theoretical research and applications. Full article

Long-range wireless area networks (LoRaWAN) typically use a simple star topology. However, some nodes may experience connectivity issues with the gateway due to signal degradation or limited coverage, often resulting from challenging environments in sectors such as agriculture, industry, smart cities, smart grids, and healthcare, where LoRaWAN-based IoT solutions have expanded. The main contribution of this paper is the implementation of a hybrid topology for LoRaWAN networks that remains fully transparent to current spec LoRaWAN servers and IoT applications. It enables the coexistence of mesh (multi-hop) and star (single-hop) communication schemes, dynamically adapting a node’s transmission mode based on physical link quality metrics. Additionally, the user interface allows for customizing network topology and parameters. Experimental proof-of-concept tests were conducted on a campus-wide testbed. Results showed that all devices successfully switched topology mode in 100% of the instances, enabling data transmission across all three scenarios under test. Network performance metrics were evaluated, with latencies ranging from 0.5 to 3.2 s for both single-hop and multi-hop transmissions. Additionally, improvements in RSSI and SNR were observed, validating the efficiency of the proposed solution. These results demonstrate the feasibility and effectiveness of our approach in extending network connectivity to areas beyond the gateway’s coverage. Full article