Evaluation of antioxidant level and protein oxidation of rainbow trout (Oncorhynchus mykiss) fillets during rigor and post-rigor

In this study, the relationship between stunning techniques and protein oxidation which are accepted as the main cause of food spoilage was investigated. For this purpose, the antioxidant status, in vivo myofibrillary protein (MP) oxidation and sensitivity, and postmortem oxidation (inducted with hydroxyl radical system) of rainbow trout (Oncorhynchus mykiss) fillets killed by hitting to head (T1), neck crushing (T2), and convulsion (T3) methods, were investigated. Statistically significant differences (p < .05) were found among all parameters examined and it was observed that the most stressing technique was the convulsion method. It was determined that in protein profiles myosin were influenced too much from stunning technique and in actin observed oxidation-induced reductions. Reductions in S-S and S-H were also found to be increased in carbonyl concentrations, but the most effective values in both processes were determined by the convulsive technique. Our results show that short-term stunning techniques (hitting to head, neck crushing) give better meat quality results in terms of O. mykiss welfare and low MP oxidation rates. In general, we can say that T3 group fillets are more sensitive to oxidative damage, while T1 and T2 groups give better results in maintaining meat quality with low MP oxidation rates.     

CFD SIMULATION OF THE GAS-SOLID FLOW IN THE RISER OF A CIRCULATING FLUIDIZED BED WITH SECONDARY AIR INJECTION

A comprehensive investigation was carried out to study hydrodynamics aspects of secondary air injection in circulating fluidized beds. This article presents modeling and results of computational fluid dynamics simulations of gas-solid flow in the riser section of a laboratory-scale (ID = 0.23 m, height = 7.6 m) circulating fluidized bed with a radial secondary air injector. The gas-solid flow model is based on the two-fluid (Eulerian-Eulerian) approach, where both gas and solids phases are treated as interpenetrating continua. A granular kinetic theory model is used to describe the solids phase stresses. The simulation results are compared with measured pressure drop and axial particle velocity profiles; reasonable agreement is obtained. Qualitatively, excellent agreement is obtained in predicting the increase in solids volume fraction below secondary air ports, the accumulation of solids around the center of the riser due to momentum of secondary air jets, and the absence of the solids down-flow near the wall above the secondary air injection ports, which are the prominent features of secondary air injection observed in the experiments.     

Detection of COVID-19 and its pulmonary stage using Bayesian hyperparameter optimization and deep feature selection methods

Since the first case of COVID-19 was reported in December 2019, many studies have been carried out on artificial intelligence for the rapid diagnosis of the disease to support health services. Therefore, in this study, we present a powerful approach to detect COVID-19 and COVID-19 findings from computed tomography images using pre-trained models using two different datasets. COVID-19, influenza A (H1N1) pneumonia, bacterial pneumonia and healthy lung image classes were used in the first dataset. Consolidation, crazy-paving pattern, ground-glass opacity, ground-glass opacity and consolidation, ground-glass opacity and nodule classes were used in the second dataset. The study consists of four steps. In the first two steps, distinctive features were extracted from the final layers of the pre-trained ShuffleNet, GoogLeNet and MobileNetV2 models trained with the datasets. In the next steps, the most relevant features were selected from the models using the Sine–Cosine optimization algorithm. Then, the hyperparameters of the Support Vector Machines were optimized with the Bayesian optimization algorithm and used to reclassify the feature subset that achieved the highest accuracy in the third step. The overall accuracy obtained for the first and second datasets is 99.46% and 99.82%, respectively. Finally, the performance of the results visualized with Occlusion Sensitivity Maps was compared with Gradient-weighted class activation mapping. The approach proposed in this paper outperformed other methods in detecting COVID-19 from multiclass viral pneumonia. Moreover, detecting the stages of COVID-19 in the lungs was an innovative and successful approach.     

Silver Nanoflower Decorated Graphene Oxide Sponges for Highly Sensitive Variable Stiffness Stress Sensors

Soft conductive materials should enable large deformation while keeping high electrical conductivity and elasticity. The graphene oxide (GO)‐based sponge is a potential candidate to endow large deformation. However, it typically exhibits low conductivity and elasticity. Here, the highly conductive and elastic sponge composed of GO, flower‐shaped silver nanoparticles (AgNFs), and polyimide (GO‐AgNF‐PI sponge) are demonstrated. The average pore size and porosity are 114 µm and 94.7%, respectively. Ag NFs have thin petals (8–20 nm) protruding out of the surface of a spherical bud (300–350 nm) significantly enhancing the specific surface area (2.83 m² g^?1). The electrical conductivity (0.306 S m^?1 at 0% strain) of the GO‐AgNF‐PI sponge is increased by more than an order of magnitude with the addition of Ag NFs. A nearly perfect elasticity is obtained over a wide compressive strain range (0–90%). The strain‐dependent, nonlinear variation of Young's modulus of the sponge provides a unique opportunity as a variable stiffness stress sensor that operates over a wide stress range (0–10 kPa) with a high maximum sensitivity (0.572 kPa^?1). It allows grasping of a soft rose and a hard bottle, with the minimal object deformation, when attached on the finger of a robot gripper.     

Experimental study of a micro-scale sloped solar chimney power plant

Journal of Mechanical Science and Technology - Solar chimney power plants (SCPP) are structures that have the potential to generate a significant amount of electrical energy without harming the...     

Anomaly localization in regular textures based on deep convolutional generative adversarial networks

Applied Intelligence - Pixel-level anomaly localization is a challenging problem due to the lack of abnormal training samples. The existing adversarial network methods attempt to segment anomalies...     

UV curable lens production using molecular weight controlled PEEK based acrylic oligomer (Ac-PEEK)

We produced UV curable lenses with properties blocking short wave UV light. In the UV-curable formulations, we used an oligomer (Ac-PEEK) with another urethan oligomer (Mw = 2000). Radically active, molecular weight controlled Ac-PEEK was obtained by reacting 2-hydroxyl ethyl methacrylate with molecular- weight- controlled and isocyanate terminated PEEK (Mn = 4500). We characterized all synthesized monomer, oligomer and optical materials with UV/Vis spectrophotometer with interferogram, elemental analyser, mass spectrophotometer, proton nuclear magnetic resonance, Fourier transform infrared spectroscopy, thermal gravimetric analyzer, differential scanning calorimeter, scanning electron microscopy and gas chromatography. Results suggested that newly synthesized oligomer with the structure of PEEK absorbs short wave UV-light. Ageing tests [ISO 11979-5, Ophthalmic implants—intraocular lenses (IOL)—Part 5: Biocompatibility] performed on the IOL materials were successful. High contact angle of the obtained lenses suggests that all lenses were hydrophobic and SEM results revealed that lenses are morphologically homogeneous. Based on all positive properties just mentioned, we safely conclude that the lenses produced in this study are very promising for IOL production.