Honey is an inexpensive, food-based option for treating diabetic foot ulcers (DFUs) due to its anti-inflammatory and antibacterial properties. It has proven effective against bacterial biofilms and multidrug-resistant bacteria, positioning honey as a promising candidate for DFU management. However, honey’s physicochemical properties and concentration variations can lead to differing bacterial responses. This study aimed to assess the effects of various honey types and concentrations on bacterial biofilms. Seven honey types were tested at concentrations of 1x, 5x, and 10x the minimum inhibitory concentration (MIC) against biofilms of Staphylococcus aureus, Escherichia. coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Candida albicans.

Results indicated that honey types 3 and 4 achieved significantly higher biofilm removal for C. albicans compared to types 5 (p = 0.008; p = 0.001), 8 (p = 0.022; p = 0.003), and 9 (p = 0.009; p = 0.001) at the same concentrations. Similarly, honey types 2 and 4 were more effective against E. coli than type 9 (p = 0.016; p = 0.004). Higher honey concentrations resulted in greater biofilm removal for C. albicans and E. coli (p = 0.004, both), and more pronounced biofilm metabolic inactivation for C. albicans, K. pneumoniae (p = 0.004, both), and P. aeruginosa (p = 0.048). Principal Component Analysis suggested a correlation between pollen content and antimicrobial activity. Overall, honey demonstrated significant potential in removing bacterial biofilms and inhibiting metabolic activity, particularly at higher concentrations. The differences in bacterial responses to honey treatments may be attributed to variations in the honeys' physicochemical properties and bacterial strain sensitivity.

This work is aimed at formulating, characterizing and evaluatin different aqueous formulations based on emulsions with a relatively simple composition. In particular, this study focuses on a pseudo-ternary system water–oil-stabilizing agent (Pluronic F-127), where the oily phase is constituted of a mixture of two components of essential oils, eugenol and thymol, in different proportions. The choice of this type of system lies in the multiple beneficial properties of some of the essential oil components. However, their low solubility in water makes it necessary to look for strategies for their transport and controlled release, with emulsions being ideal platforms on which to exploit the use of these bioactive compounds by encapsulation. For this purpose, in this work, the determination of compositions leading to stable formulations is explored. This implies studying formulations where both the total oil fraction and the composition of the oily phase are varied. In this way, it will be possible to find the compositional regions of stability and instability of the system, i.e., to obtain a compositional map or phase diagram. On the other hand, a characterization of stable formulations will be performed due to the impact of the characteristics of the formulations for their possible practical applications. This characterization will include a study of the distribution of the oil or the droplet size of the emulsions, but also specific details related to the potential applications of these systems.

The emergence and rapid spread of SARS-CoV-2 variants have underscored the urgent need for innovative antiviral strategies. This study investigates the potential of gold and silver nanoparticles as effective agents against COVID-19 variants, including Alpha, Beta, Gamma, Delta, and Omicron. Nanoparticles possess unique physicochemical properties that enable them to interact with viral particles and disrupt crucial viral functions, making them promising candidates for antiviral therapy. Through advanced computational modeling, integrating techniques such as molecular dynamics simulations and quantum mechanical calculations, we explore the interaction dynamics between nanoparticles and key viral spike glycoprotein specific to each variant, which plays a pivotal role in host cell entry. Our analysis elucidates the mechanisms by which gold and silver nanoparticles interact with variant-specific targets, docking analysis underscores their notable affinity towards all five ACE2-spike receptor variants. Notably, the binding affinities range between 0.18 and 0.27 Kcal/mol, indicative of strong interactions. Across the complexes, AuNPs generally exhibit a slightly higher affinity compared to AgNPs. Furthermore, we investigate the physicochemical properties of nanoparticles, such as size, shape, and surface functionalization, that influence their antiviral efficacy against different variants. Our findings provide valuable insights into the design and optimization of nanoparticle-based therapeutics for combating the evolving landscape of COVID-19 variants.

Rice (Oryza sativa L.) is a cereal crop cultivated worldwide for food, oils, and other applications. However, the processing of rice also generates large quantities of non-edible, solid residues called rice husks (RH), which account for 20% of the grain weight. The lack of effective and efficient strategies for handling RH has resulted in waste accumulation, thereby posing human health, safety, and environmental risks. To address these challenges, researchers have examined the treatment and valorisation potentials of RH through the pyrolysis process based on numerous research studies on rice husk pyrolysis (RHP) published and indexed in the Scopus database annually. Given the growing research interest and technological developments, there is an urgent need to examine the research climate and scientific landscape on RHP. Therefore, the paper presents the publication trends and a concise review of RHP based on the published documents in Scopus. The publication trends analysis revealed a geometric increase (3280% or 1,125 total published documents) from 2001 to 2021. The most prolific author on RHP research is Shuping Zhang (Nanjing University of Science and Technology), whereas the top affiliation is the Ministry of Education (China). The most cited funding organisation and country are the National Natural Science Foundation and the People Republic of China, respectively. A literature review revealed that RHP is an important research area due to the prominent publications, authors and citation counts on the topic. Lastly, the findings showed that pyrolysis is an effective technology for the treatment, disposal, valorisation, and management of RH wastes.

Cloud computing plays a vital role in managing and processing the diverse data generated by Internet of Things (IoT) devices, creating the cloud-IoT (CIoT) architecture. However, CIoT is insufficient for applications that are latency-sensitive and require significant network bandwidth. To address these challenges, fog computing complements CIoT, forming a distributed architecture called the Fog-IoT architecture. The diverse nature of Fog resources complicates the management of interoperability and scalability within the Fog-IoT architecture. Software Defined Network has been proposed as a solution in managing interoperability and heterogeneous resources in distributed architectures. This paper evaluates two software-defined network (SDN) east-west interfaces - the Modified Communication Interface for Distributed Control Plane (mCIDC) and the Distributed SDN Framework (DSF), in addressing the challenges of manageability and interoperability in Fog-IoT architecture. Experiments conducted using the SDN Floodlight controller indicated that mCIDC required more packets for inter-controller communication compared to DSF, with average captured TCP packets of 26,330.7 and 17,473.1, respectively. The DSF exhibited lower inter-controller communication overload (ICO) with an average ICO of 222.6, compared to 301.2 for mCIDC. Additionally, the DSF generated fewer errors than mCIDC, with average TCP errors of 2,713.4 and 3,935.8, respectively. The results show that DSF uses fewer packets and generates fewer errors during inter-controller communication, making it more reliable than mCIDC for Fog-IoT architecture.

Steganography, a technique of concealing data within shared information, plays a crucial role in addressing the imperative of safeguarding data within computer networks. While encryption serves as a vital process for encoding both text and images to ensure data security, its susceptibility lies in the potential exposure of encryption keys, which can lead to decryption by unauthorized parties. Cryptography, on the other hand, employs mathematical techniques to secure communication and information, ensuring confidentiality, integrity, authentication, and nonrepudiation of data. By fortifying cybersecurity, cryptography serves as a pivotal tool in protecting sensitive information across various applications.

The objective of this project is to develop a robust Advanced Encryption Standard (AES) algorithm capable of encrypting text before embedding the resulting ciphertext within an image through steganography. The Advanced Encryption Standard (AES) is widely used for securing sensitive data. This approach ensures that decoding the concealed information necessitates the correct encryption key, thereby ensuring protection for both the image and the embedded text. By integrating AES encryption with steganography, the project aims to enhance data security through layered measures, mitigating conventional encryption risks by hiding ciphertext within the pixels of an image. This fusion of encryption and steganography presents a promising strategy for bolstering data confidentiality and security within communication channels.

Traditional software-defined network (SDN) systems focus primarily based on a north–south data flow to enable centralized control of network devices. However, the growing complexity and scale of modern networks, driven by emerging internet applications and services, require a more advanced approach to handle the east–west data flow, which involves communication between devices within the network. This necessitates a distributed SDN architecture with multiple controllers to simplify network management and achieve control. This paper evaluates a modified east–west interface with network policies for Distributed Control Plane Networks, designed to meet the needs of SDN in multi-domain networks such as wide area networks (WANs) while ensuring network availability. The modified east–west interface is developed by implementing network policies on a Modified Communication Interface for Distributed Control Plane (mCIDC), which is integrated with the Floodlight controller. Experimental results demonstrate that the mCIDC outperforms the Communication Interface for Distributed Control Plane (CIDC) by reducing captured transmission control protocol (TCP) packets by 15.51%, TCP errors by 29.85%, and inter-controller communication overload by 22.98%. This indicates that the mCIDC can make better decisions in line with network policies compared to the CIDC when deployed in a real-time wide-area network. This shows that SDN architectures can support network policies for management, security, and interoperability network devices.

This paper proposes a solution aimed at optimizing recommendation systems for online commerce. Taking an ordered list of products to recommend as input, the proposed solution optimizes this list by considering trends in web searches. The solution collects data on web search trends, filters the data to retain only searches related to products and services, identifies the relevant characteristics of these products, and subsequently reorders the recommendation list based on the similarity of these characteristics with the characteristics of the products on the recommendation list. This establishes a relationship between market search trends and the most recommendable products/services from the existing offer. The solution adopts the power of Google Trends to capture consumer interest across various topics, products, and services—it is assumed that web search trends reflect market trends. Second, ChatGPT is added to refine the gathered raw trend data by removing noise, contextualizing information and matching it with the attributes of products or services in the recommendation list, ensuring that the trend insights are relevant and actionable. Finally, it integrates these insights with the user preferences to dynamically reorder the recommendation lists, prioritizing items that are most representative. Initial results show its effectiveness in improving the relevance of recommendations by demonstrating its potential as a scalable and automated framework for optimizing digital marketing campaigns to build adaptive recommendation engines. This approach provides a robust foundation for future innovations by aligning user preferences with external market signals.

The importance of assessing the microbiological safety of food products is beyond doubt, which is also true for milk and dairy products. They are very important in the diet and contain nutrients necessary for the human body in well-balanced proportions and in an easily digestible form. Therefore, the goal of this work was to evaluate the changes in the composition of the gas phase over milk based on signals from chemical sensors to predict the quantity of the coliform bacteria group in the milk samples. The gas phase over raw milk samples and samples after pasteurization, as well as for a standard (a model aqua solution of macronutrients and minerals), was studied using an array of sensors with polycomposite coatings, including those contaminated with E. coli bacteria. Assessment of microbiological indicators was carried out according to GOST in parallel with the gas-phase analysis. The patterns of the sensor signals, the calculation parameters, and calibration graphs with an error of ±100 CFU/ml were established based on the results of analyzing the standard samples. The adequacy of the calibration graphs was tested on seven raw milk samples, including those containing other types of pathogenic microorganisms (Staphylococcus aureus, Klebsiella spp., etc.). Thus, the proposed approaches to quantitative assessments of coliform bacteria in raw and pasteurized milk using gas-phase analysis with an array of sensors make it possible to significantly reduce the analysis time to 2-3 hours (including the sample collection and data processing) and thereby intensify the production of safe dairy products.

Essential oils are one of the sources of natural antioxidants in food industry. Their major representatives are phenolic compounds, whose composition is strongly dependent on the type of plant material, the geographical conditions of its growth, the vegetation stage, and the processing method. Therefore, the characterization of the antioxidant properties of essential oils is in demand today. The total antioxidant parameters obtained by electrochemical methods were shown as an effective approach for the sample characterization. In current work, the commercial essential oils from basil, ylang-ylang, bergamot, marjoram, clove, jasmine, neroli, cinnamon, lavender, rosemary, ginger, nutmeg, thyme, anise, and clary sage were studied. Galvanostatic coulometry with electrogenerated Br₂ and [Fe(CN)₆]^3- ions and chronoamperometry were used for the assessment of total antioxidant capacity (TAC), ferric reducing power (FRP), and antioxidant capacity, respectively. TAC reflects the impact of both phenolic antioxidants and terpenes, while FRP indicates the content of phenolic antioxidants only. Chronoamperometry at glassy carbon electrode covered with carboxylated multi-walled carbon nanotubes makes it possible to differentiate the impact of phenolic compounds and terpenes applying various potentials, i.e., 800 and 1400 mV, respectively. The sufficient electrolysis time was 75 s on each step. The total antioxidant parameters screening was performed, and positive correlations with the standard spectrophotometric methods (Folin–Ciocalteu for clove, cinnamon, nutmeg, and thyme essential oils only and the DPPH test for all samples) were found. Electrochemical approaches are express, cost-effective, simple, reliable, and have no limitations typical for spectrophotometry. Therefore, electrochemical assessment of the antioxidant properties of essential oils is a perspective for practice.