A Novel Hybrid Optimization for Cluster‐Based Routing Protocol in Information-Centric Wireless Sensor Networks for IoT Based Mobile Edge Computing

Wireless Personal Communications - In present days, the utilization of mobile edge computing (MEC) and Internet of Things (IoT) in mobile networks offers a bottleneck in the evolving technological...     

Intelligent Feature Selection with Deep Learning Based Financial Risk Assessment Model

Due to global financial crisis, risk management has received significant attention to avoid loss and maximize profit in any business. Since the financial crisis prediction (FCP) process is mainly based on data driven decision making and intelligent models, artificial intelligence (AI) and machine learning (ML) models are widely utilized. This article introduces an intelligent feature selection with deep learning based financial risk assessment model (IFSDL-FRA). The proposed IFSDL-FRA technique aims to determine the financial crisis of a company or enterprise. In addition, the IFSDL-FRA technique involves the design of new water strider optimization algorithm based feature selection (WSOA-FS) manner to an optimum selection of feature subsets. Moreover, Deep Random Vector Functional Link network (DRVFLN) classification technique was applied to properly allot the class labels to the financial data. Furthermore, improved fruit fly optimization algorithm (IFFOA) based hyperparameter tuning process is carried out to optimally tune the hyperparameters of the DRVFLN model. For enhancing the better performance of the IFSDL-FRA technique, an extensive set of simulations are implemented on benchmark financial datasets and the obtained outcomes determine the betterment of IFSDL-FRA technique on the recent state of art approaches.     

Identification of Nanoscale Ingredients in Commercial Food Products and their Induction of Mitochondrially Mediated Cytotoxic Effects on Human Mesenchymal Stem Cells

Titanium dioxide (E171) and silicon dioxide (E551) are common additives found in food products, personal‐care products, and many other consumer products used in daily life. Recent studies have reported that these food additives (manufactured E171 and E551) contain nanosized particles of less than 100 nm. However, the particle size distribution and morphology of added TiO₂ and SiO₂ particles are not typically stated on the package label. Furthermore, there is an increasing debate regarding health and safety concerns related to the use of synthetic food additives containing nanosized ingredients in consumer products. In this study, we identified the size and morphology of TiO₂ and SiO₂ particles in commercially available food products by using transmission electron microscope (TEM). In addition, the in vitro toxicological effects of E171 and E551 on human mesenchymal stem cells (hMSCs), an adult stem cell‐based model, were assessed using the MTT assay and a flow cytometry‐based JC‐1 assay. Our TEM results confirmed the presence of nanoscale ingredients in food products, and the in vitro toxicology results indicated that the nanoscale E171 and E551 ingredients induced dose‐dependent cytotoxicity, changes in cellular morphology, and the loss of mitochondrial trans‐membrane potential in hMSCs. These preliminary results clearly demonstrated that the nanoscale E171 and E551 particles had adverse effects on hMSCs by inducing oxidative stress‐mediated cell death. Accordingly, further studies are needed to identify the specific pathway involved, with an emphasis on differential gene expression in hMSCs.     

Nitrogen-incorporated carbon nanotube derived from polystyrene and polypyrrole as hydrogen storage material

“Synthesis of nitrogen-doped carbon nanotubes from polymeric precursors (polystyrene and polypyrrole) by poly-condensation followed by carbonization under an inert atmosphere is reported. Three different carbonization temperatures (500 °C, 700 °C and 900 °C) were employed to synthesize three different carbon nanostructures with different morphologies. These were designated as NCNR-500 (nitrogen-doped carbon nanorods), NCBCT-700 (nitrogen-doped fused bead carbon nanotubes), and NCNT-900 (nitrogen-doped carbon nanotubes) according to morphology and carbonization temperature. Microstructure, morphology, porosity, and nitrogen content were characterized by several different techniques. The effects of carbonization temperature and the role of functional groups were also investigated. Total and excess hydrogen storage capacities of 2.0 wt% and 1.8 wt%, respectively, were measured at 298 K and 100 bar for the NCNT-900 material. This is higher than the capacities of the NCNR-500 and NCBCT-700 materials. NCNT-900 exhibited a porous structure with high specific surface area and total pore volume of 870 m/g and 0.62 cm³/g, respectively.     

Methicillin‐Resistant Staphylococcus aureus in Seafood: Prevalence,Laboratory Detection,Clonal Nature,and Control in Seafood Chain

Methicillin‐resistant Staphylococcus aureus (MRSA), a versatile pathogen bearing multiple virulence determinants, is increasingly being detected in various food‐producing animals, including fish. In addition, it is a potential food poisoning agent. MRSA is not an inherent microbiota of fish; its presence is attributed to pre‐ or postharvest contamination through fish handlers, water, ice, and processing equipment. Several reviews have been written on MRSA in clinical as well as the food animal‐producing sector, but information specific to MRSA in seafood is scant. This review puts forth insights on MRSA detection in seafood, antibiotic resistance, diversity of clones in seafood, and possible control measures in seafood production chain. Emphasis has been given on assessing the variations in the protocols employed for isolation and identification in different food matrices and lay the foundation for researchers to develop optimized procedure.     

Automatic Vehicle License Plate Recognition Using Optimal Deep Learning Model

The latest advancements in highway research domain and increase inthe number of vehicles everyday led to wider exposure and attention towards the development of efficient Intelligent Transportation System (ITS). One of the popular research areas i.e., Vehicle License Plate Recognition (VLPR) aims at determining the characters that exist in the license plate of the vehicles. The VLPR process is a difficult one due to the differences in viewpoint, shapes, colors, patterns, and non-uniform illumination at the time of capturing images. The current study develops a robust Deep Learning (DL)-based VLPR model using Squirrel Search Algorithm (SSA)-based Convolutional Neural Network (CNN), called the SSA-CNN model. The presented technique has a total of four major processes namely preprocessing, License Plate (LP) localization and detection, character segmentation, and recognition. Hough Transform (HT) is applied as a feature extractor and SSA-CNN algorithm is applied for character recognition in LP. The SSA-CNN method effectively recognizes the characters that exist in the segmented image by optimal tuning of CNN parameters. The HT-SSA-CNN model was experimentally validated using the Stanford Car, FZU Car, and HumAIn 2019 Challenge datasets. The experimentation outcome verified that the presented method was better under several aspects. The projected HT-SSA-CNN model implied the best performance with optimal overall accuracy of 0.983%.     

An investigation and comparison of machine learning approaches for intrusion detection in IoMT network

The Journal of Supercomputing - Internet of Medical Things (IoMT) is network of interconnected medical devices (smart watches, pace makers, prosthetics, glucometer, etc.), software applications,...     

Pyrene-modified quartz crystal microbalance for the detection of polynitroaromatic compounds

The synthesis of a dithiol-functionalized pyrene derivative is reported, together with studies of interactions between this receptor (and other related pyrenes) and nitroaromatic compounds (NACs), in both solution and in the solid state. Spectroscopic analysis in solution and X-ray crystallographic analysis of cocrystals of pyrene and NACs in the solid state indicate that supramolecular interactions lead to the formation of defined π-π stacked complexes. The dithiol-functionalized pyrene derivative can be used to modify the surface of a gold quartz crystal microbalance (QCM) to create a unique π-electron rich surface, which is able to interact with electron poor aromatic compounds. For example, exposure of the modified QCM surface to the nitroaromatic compound 2,4-dinitrotoluene (DNT) in solution results in a reduction in the resonant frequency of the QCM as a result of supramolecular interactions between the electron-rich pyrenyl surface layer and the electron-poor DNT molecules. These results suggest the potential use of such modified QCM surfaces for the detection of explosive NACs.     

First Insights into the Venom Composition of Two Ecuadorian Coral Snakes

Micrurus is a medically relevant genus of venomous snakes composed of 85 species. Bites caused by coral snakes are rare, but they are usually associated with very severe and life-threatening clinical manifestations. Ecuador is a highly biodiverse country with a complex natural environment, which is home to approximately 20% of identified Micrurus species. Additionally, it is on the list of Latin American countries with the highest number of snakebites. However, there is no local antivenom available against the Ecuadorian snake venoms, and the biochemistry of these venoms has been poorly explored. Only a limited number of samples collected in the country from the Viperidae family were recently characterised. Therefore, this study addressed the compositional patterns of two coral snake venoms from Ecuador, M. helleri and M. mipartitus, using venomics strategies, integrating sample fractionation, gel electrophoresis, and mass spectrometry. Chromatographic and electrophoretic profiles of these snake venoms revealed interspecific variability, which was ascertained by mass spectrometry. The two venoms followed the recently recognised dichotomic toxin expression trends displayed by Micrurus species: M. helleri venom contains a high proportion (72%) of phospholipase A₂, whereas M. mipartitus venom is dominated by three-finger toxins (63%). A few additional protein families were also detected in these venoms. Overall, these results provide the first comprehensive views on the composition of two Ecuadorian coral snake venoms and expand the knowledge of Micrurus venom phenotypes. These findings open novel perspectives to further research the functional aspects of these biological cocktails of PLA₂s and 3FTxs and stress the need for the preclinical evaluation of the currently used antivenoms for therapeutic purposes in Ecuador.     

Unraveling the physicochemical and toxicological properties of food product isolated E341/E171

Nanostructured materials have been extensively exploited in the food sector for nutrient delivery, sensing, packaging, and food additives. It has exhibited size, shape, chemical nature, and surface area-dependent physicochemical and biological properties. Currently, nanoscale ingredients are identified in approved food additives. Still, food-grade nanostructured material's impact on biological systems is unexplored well. Thus, in this study, we have identified and analyzed the physicochemical properties of nanoscale ingredients in commercial food product isolate E341 and E171 combinations. Also, we have evaluated the E341/E171 combination cytotoxic potential on human mesenchymal stem cells. The food isolated E341/E171 exhibits spherical nature with a 60–200 nm diameter. The E341 and E171 combination exposure increased the cell viability loss to ~36% at a high dose in human mesenchymal stem cells (hMSCs). The E341/E171 treatment-induced cellular and nuclear damage at a moderate dose. The mitochondrial membrane potential loss and ROS generation were observed in E341/E171 treated cells. The E341/E171 alters the gene expression pattern in hMSCs dose-dependently. The GSR and POR gene expression is upregulated significantly in E341/E171 treatment. Our study results revealed that E341/E171 induced toxicity in hMSCs at high concentrations. Thus, E341/E171 potential impact on the biological system should be reexamined for food industrial implications.