Toxicological effects of the chemical and green ZnO NPs on Cyprinus carpio L. observed under light and scanning electron microscopy

Nanoparticles in aquatic bodies cause serious harm to the aquatic organisms when accumulated in high amounts. However, green nanoparticles synthesized using plants can be less toxic as compared to chemical nanoparticles. Hence, we designed our study to investigate the toxicological effects of chemical and green zinc oxide nanoparticles (ZnO NPs) on the biological activity of juvenile Cyprinus carpio. The green ZnO NPs were synthesized from Solieria robusta, and chemical ZnO NPs were synthesized using zinc chloride solution and ammonium hydroxide. Characterization was done by using light microscopy, scanning electron microscope (SEM), Fourier transmission infrared radiation, and X-ray diffraction (XRD) techniques. The highest absorbance of nanoparticles was observed at 360 which confirmed the synthesis of ZnO. The SEM analysis showed that green nanoparticles were hexagonal while the chemical nanoparticles were spherical to cubic in shape. Definite peaks were observed in XRD of green and chemical NPs at 2θ angles 45.84° and 32.18°, respectively. Oxidative stress was determined by chemical analysis of catalase, glutathione S-transferase (GST), glutathione (GSH), and lipid peroxidation (LPO) activities. The toxicological effects of chemical ZnO NPs on the catalase, LPO, GST, and GSH activities were more than green ZnO NPs. The histopathological investigation proved that the effect of chemical nanoparticles was worse than green ZnO NPs. More tissue damage was found in chemical nanoparticles than green synthesized nanoparticles. It was concluded that chemical nanoparticles can be replaced by green nanoparticles, as green nanoparticles are eco-friendly with less toxicological effects. This replacement can limit the toxic effect of nanoparticles when they get accumulated in high amounts in water bodies.     

Zinc-based metal-organic frameworks: synthesis and recent progress in biomedical application

Journal of Inorganic and Organometallic Polymers and Materials - This review based on Zn-based MOF is summarized on new insights for targeted drug delivery of medicinal compounds and developed for...     

Development of imitated meat product by utilizing pea and lentil protein isolates

Imitated meat product (nuggets) has been a major influence on vegans since time immemorial. Pea protein isolates (PPIs) and lentil protein isolates (LPIs) are identified as ingredients for their indigenous color, flavor, taste, texture, and functional properties. This study was aimed to investigate the potential use of pea and lentil PI as a meat substitute in nugget preparation to replace meat usage. Chemical characteristics of pea and lentil powder and functional properties of PPI and LPI were determined. Furthermore, the nutritional profile, textural property, and sensory attributes of imitated meat products (nuggets) were compared with chicken-based nuggets. Results showed that functional properties of PPI and LPI were almost similar to each other, and NG₂ (40%PPI: 60%LPI) was selected as the most acceptable nugget with desired nutritional, textural, and sensory attributes. PPI and LPI can be successfully used nutritionally and functionally as valuable substitutes for meat-based nuggets, even in NG₂ (40%PPI: 60%LPI), without significant deterioration of overall acceptability of nuggets. PPI- and LPI-based nuggets could be introduced to the market as a potential marketable non-meat product with indigenous color, flavor, taste, texture, and overall acceptability.     

Efficient Facial Recognition Authentication Using Edge and Density Variant Sketch Generator

Image translation plays a significant role in realistic image synthesis, entertainment tasks such as editing and colorization, and security including personal identification. In Edge GAN, the major contribution is attribute guided vector that enables high visual quality content generation. This research study proposes automatic face image realism from freehand sketches based on Edge GAN. We propose a density variant image synthesis model, allowing the input sketch to encompass face features with minute details. The density level is projected into non-latent space, having a linear controlled function parameter. This assists the user to appropriately devise the variant densities of facial sketches and image synthesis. Composite data set of Large Scale CelebFaces Attributes (ClebA), Labelled Faces in the Wild (LFWH), Chinese University of Hong Kong (CHUK), and self-generated Asian images are used to evaluate the proposed approach. The solution is validated to have the capability for generating realistic face images through quantitative and qualitative results and human evaluation.     

Relevance of metal (Ca versus Mn) embedded C2N for energy-storage applications: Atomic-scale study

The suitability of embedding metal atoms (Ca versus Mn) in the pores of C₂N to be employed as the anode material for metal-ion battery applications is studied using density-functional theory. The effect of single-atom catalyst (SAC) versus dimer-atom catalyst (DAC) on the uptake catalyst capacity is put under focus. Our results show that both metal atoms exhibit very strong interactions with the pyridinic-nitrogen pore and show the ability of the pore to accommodate either a single Ca atom or a dimer of Mn atoms within its membrane-plane. While the theoretical irreducible capacitance in case of SAC Ca catalyst is limited to about 200 mAhg^?1, it can exceed this value in case of DAC-Mn catalyst to reach 1110 mAhg^?1. Regarding the adsorption, the H₂ molecule exhibits strong physisorption on Ca-catalyst and moderate chemisorption on Mn-catalyst, with an adsorption energy increasing from SAC to DAC cases. The SAC of Mn is found not only concurrent candidate to Ca for energy-storage applications but further promising for platform of reusable hydrogen gas-sensors with very low recovery time (i.e., τ « 1 s). Our findings are in good agreement with the available experimental data and theoretical results.     

An emotion-aware music recommender system: bridging the user’s interaction and music recommendation

Multimedia Tools and Applications - In emotion-aware music recommender systems, the user’s current emotion is identified and considered in recommending music to him. We have two motivations...     

Rouleaux red blood cells splitting in microscopic thin blood smear images via local maxima,circles drawing,and mapping with original RBCs

Splitting the rouleaux RBCs from single RBCs and its further subdivision is a challenging area in computer‐assisted diagnosis of blood. This phenomenon is applied in complete blood count, anemia, leukemia, and malaria tests. Several automated techniques are reported in the state of art for this task but face either under or over splitting problems. The current research presents a novel approach to split Rouleaux red blood cells (chains of RBCs) precisely, which are frequently observed in the thin blood smear images. Accordingly, this research address the rouleaux splitting problem in a realistic, efficient and automated way by considering the distance transform and local maxima of the rouleaux RBCs. Rouleaux RBCs are splitted by taking their local maxima as the centres to draw circles by mid‐point circle algorithm. The resulting circles are further mapped with single RBC in Rouleaux to preserve its original shape. The results of the proposed approach on standard data set are presented and analyzed statistically by achieving an average recall of 0.059, an average precision of 0.067 and F‐measure 0.063 are achieved through ground truth with visual inspection.     

Cloud‐based decision support system for the detection and classification of malignant cells in breast cancer using breast cytology images

The advancement of computer‐ and internet‐based technologies has transformed the nature of services in healthcare by using mobile devices in conjunction with cloud computing. The classical phenomenon of patient–doctor diagnostics is extended to a more robust advanced concept of E‐health, where remote online/offline treatment and diagnostics can be performed. In this article, we propose a framework which incorporates a cloud‐based decision support system for the detection and classification of malignant cells in breast cancer, while using breast cytology images. In the proposed approach, shape‐based features are used for the detection of tumor cells. Furthermore, these features are used for the classification of cells into malignant and benign categories using Naive Bayesian and Artificial Neural Network. Moreover, an important phase addressed in the proposed framework is the grading of the affected cells, which could help in grade level necessary medical procedures for patients during the diagnostic process. For demonstrating the e effectiveness of the proposed approach, experiments are performed on real data sets comprising of patients data, which has been collected from the pathology department of Lady Reading Hospital of Pakistan. Moreover, a cross‐validation technique has been performed for the evaluation of the classification accuracy, which shows performance accuracy of 98% as compared to physical methods used by a pathologist for the detection and classification of the malignant cell. Experimental results show that the proposed approach has significantly improved the detection and classification of the malignant cells in breast cytology images.     

Retinal imaging analysis based on vessel detection

With an increase in the advancement of digital imaging and computing power, computationally intelligent technologies are in high demand to be used in ophthalmology cure and treatment. In current research, Retina Image Analysis (RIA) is developed for optometrist at Eye Care Center in Management and Science University. This research aims to analyze the retina through vessel detection. The RIA assists in the analysis of the retinal images and specialists are served with various options like saving, processing and analyzing retinal images through its advanced interface layout. Additionally, RIA assists in the selection process of vessel segment; processing these vessels by calculating its diameter, standard deviation, length, and displaying detected vessel on the retina. The Agile Unified Process is adopted as the methodology in developing this research. To conclude, Retina Image Analysis might help the optometrist to get better understanding in analyzing the patient's retina. Finally, the Retina Image Analysis procedure is developed using MATLAB (R2011b). Promising results are attained that are comparable in the state of art.