Influence of Vacuum Impregnation with Different Substances on the Metabolic Heat Production and Sugar Metabolism of Spinach Leaves

Vacuum impregnation (VI) has been widely used as pre-treatment prior to, e.g., minimal processing, freezing, or drying of fruit and vegetables. Most of the investigations have focused on the applicability of VI to modify physicochemical, sensory, and nutritive characteristics. However, little attention has been paid to the metabolic consequences of impregnating different substances into the plant tissue. This study explores short- and long-term metabolic responses of baby spinach leaves at 5 °C after impregnation with several substances that are commonly used in food industry, e.g., sucrose, calcium lactate, citric acid, and ascorbic acid. Short-term metabolic response of impregnated spinach leaves was measured with isothermal calorimetry for 7 h. Results demonstrated that leaves impregnated with calcium lactate and sucrose showed a drastic increase in metabolic heat production, but no change was recorded in leaves impregnated with solutions of ascorbic acid or citric acid. Long-term metabolic responses were evaluated by measuring sugars and starch. The different impregnation solutes provoked specific changes in the carbohydrate composition during cold storage and the concentrations at each time point are likely to be the result of mobilization of starch, which sharply decreased during storage, and solute-specific differences in metabolization and interconversion of sugars.     

Task switching performance reveals heterogeneity amongst patients with mild cognitive impairment.

Objective: To assess executive function in patients with mild cognitive impairment (MCI) and to determine whether task switching ability is associated with transition to Alzheimer's disease. Methods: Twenty-seven MCI patients and 19 older controls were tested using a cued letter-digit classification switching task. Sixteen patients could perform the task (MCI-able), 6 could not (MCI-unable), and 5 were able only with cognitive support (MCI-cue). Demographic, neuropsychological, event-related potential (ERP), MRI, and genetic data were also collected. Results: The four groups did not differ on age, gender, and APO E4 frequency. Compared to the controls, the MCI-unable group had significantly poorer performance on the Trail Making task (η2 = .430), lower education (η2 = .234), and smaller cortical volume (η2 = .245). Most MCI patients exhibited task-switching deficits but to vastly different degrees and with varying outcomes. The combined pattern of neuropsychological and task switching performance indicates that the MCI-able patients displayed memory retrieval difficulties (F(2,39) = 3.6, p = .036, MSE = 1.44), generally preserved task switching abilities, and had a high probability of remaining dementia-free at follow-up. The MCI-cue patients had increased mixing costs, F(2,39) = 11.0, p     

Optical Fibre-Enabled Photoswitching for Localised Activation of an Anti-Cancer Therapeutic Drug

Local activation of an anti-cancer drug when and where needed can improve selectivity and reduce undesirable side effects. Photoswitchable drugs can be selectively switched between active and inactive states by illumination with light; however, the clinical development of these drugs has been restricted by the difficulty in delivering light deep into tissue where needed. Optical fibres have great potential for light delivery in vivo, but their use in facilitating photoswitching in anti-cancer compounds has not yet been explored. In this paper, a photoswitchable chemotherapeutic is switched using an optical fibre, and the cytotoxicity of each state is measured against HCT-116 colorectal cancer cells. The performance of optical-fibre-enabled photoswitching is characterised through its dose response. The UV–Vis spectra confirm light delivered by an optical fibre effectively enables photoswitching. The activated drug is shown to be twice as effective as the inactive drug in causing cancer cell death, characterised using an MTT assay and fluorescent microscopy. This is the first study in which a photoswitchable anti-cancer compound is switched using an optical fibre and demonstrates the feasibility of using optical fibres to activate photoswitchable drugs for potential future clinical applications.     

DEICA: A differential evolution-based improved clustering algorithm for IoT-based heterogeneous wireless sensor networks

With the evolution of technology, many modern applications like habitat monitoring, environmental monitoring, disaster prediction and management, and telehealth care have been proposed on wireless sensor networks (WSNs) with Internet of Things (IoT) integration. However, the performance of these networks is restricted because of the various constraints imposed due to the participating sensor nodes, such as nonreplaceable limited power units, constrained computation, and limited storage. Power limitation is the most severe among these restrictions. Hence, the researchers have sought schemes enabling energy-efficient network operations as the most crucial issue. A metaheuristic clustering scheme is proposed here to address this problem, which employs the differential evolution (DE) technique as a tool. The proposed scheme achieves improved network performance via the formulation of load-balanced clusters, resulting in a more scalable and adaptable network. The proposed scheme considers multiple parameters such as nodes' energy level, degree, proximity, and population for suitable network partitioning. Through various simulation results and experimentation, it establishes its efficacy over state-of-the-art schemes in respect of load-balanced cluster formation, improved network lifetime, network resource utilization, and network throughput. The proposed scheme ensures up to 57.69%, 33.16%, and 57.74% gains in network lifetime, energy utilization, and data packet delivery under varying network configurations. Besides providing the quantitative analysis, a detailed statistical analysis has also been performed that describes the acceptability of the proposed scheme under different network configurations.     

Google Scholar University Ranking Algorithm to Evaluate the Quality of Institutional Research

Education quality has undoubtedly become an important local and international benchmark for education, and an institute’s ranking is assessed based on the quality of education, research projects, theses, and dissertations, which has always been controversial. Hence, this research paper is influenced by the institutes ranking all over the world. The data of institutes are obtained through Google Scholar (GS), as input to investigate the United Kingdom’s Research Excellence Framework (UK-REF) process. For this purpose, the current research used a Bespoke Program to evaluate the institutes’ ranking based on their source. The bespoke program requires changes to improve the results by addressing these methodological issues: Firstly, Redundant profiles, which increased their citation and rank to produce false results. Secondly, the exclusion of theses and dissertation documents to retrieve the actual publications to count for citations. Thirdly, the elimination of falsely owned articles from scholars’ profiles. To accomplish this task, the experimental design referred to collecting data from 120 UK-REF institutes and GS for the present year to enhance its correlation analysis in this new evaluation. The data extracted from GS is processed into structured data, and afterward, it is utilized to generate statistical computations of citations’ analysis that contribute to the ranking based on their citations. The research promoted the predictive approach of correlational research. Furthermore, experimental evaluation reported encouraging results in comparison to the previous modification made by the proposed taxonomy. This paper discussed the limitations of the current evaluation and suggested the potential paths to improve the research impact algorithm.     

A typology of secure multicast communication over 5 G/6 G networks

International Journal of Information Security - The growth of media services, multimedia conferencing, interactive distance learning, and distributed interactive simulations is becoming more...     

A hybridization of butterfly optimization algorithm and harmony search for fuzzy modelling in phishing attack detection

Neural Computing and Applications - Fuzzy system is one of the most used systems in the decision-making and classification method as it is easy to understand because the way this system works is...     

An Omniphobic Spray Coating Created from Hierarchical Structures Prevents the Contamination of High-Touch Surfaces with Pathogens

Engineered surfaces that repel pathogens are of great interest due to their role in mitigating the spread of infectious diseases. A robust, universal, and scalable omniphobic spray coating with excellent repellency against water, oil, and pathogens is presented. The coating is substrate-independent and relies on hierarchically structured polydimethylsiloxane (PDMS) microparticles, decorated with gold nanoparticles (AuNPs). Wettability studies reveal the relationship between surface texturing of micro- and/or nano-hierarchical structures and the omniphobicity of the coating. Studies of pathogen transfer with bacteria and viruses reveal that an uncoated contaminated glove transfers pathogens to >50 subsequent surfaces, while a coated glove picks up 10⁴ (over 99.99%) less pathogens upon first contact and transfers zero pathogens after the second touch. The developed coating also provides excellent stability under harsh conditions. The remarkable anti-pathogen properties of this surface combined with its ease of implementation, substantiate its use for the prevention of surface-mediated transmission of pathogens.     

Output Linearization of Single-Input Single-Output Fuzzy System to Improve Accuracy and Performance

For fuzzy systems to be implemented effectively, the fuzzy membership function (MF) is essential. A fuzzy system (FS) that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output (SISO) FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s output. Utilizing a variety of non-linear techniques, a SISO FS is simulated. The results of FS experiments conducted in comparable conditions are then compared. The simulated results and the results of the experimental setup agree fairly well. The findings of the suggested model demonstrate that the relative error is abated to a sufficient range (≤ ± 10%) and that the mean absolute percentage error (MPAE) is reduced by around 66.2%. The proposed strategy to reduce MAPE using an FS improves the system’s performance and control accuracy. By using the best input and output MFs protocol, the energy and financial efficiency of every SISO FS can be improved with very little tuning of MFs. The proposed fuzzy system performed far better than other modern days approaches available in the literature.