Identification of phenolic profiles,fatty acid compositions,antioxidant activities,and enzyme inhibition effects of seven wheat cultivars grown in Turkey: A phytochemical approach for their nutritional value

In the present article, seven wheat cultivars (Ahmetaga, Bezostaya, Dagdas-94, Ekiz, Karahan-99, Konya-2002, and Tosunbey) grown in Turkey were compared for their phytochemical composition, antioxidant, and enzyme inhibitory activities. Antioxidant capacities and enzyme inhibitory effects were investigated with colorimetric methods. Total phenolic content ranged from 40.71 to 86.34 mg of gallic acid equivalent/100 g wheat grain. Tosunbey (92 mg Trolox equivalent/100 g wheat grain) and Ahmetaga (114.56 mg Trolox equivalent/100 g wheat grain) cultivars exhibited strong 2,2 azino-bis (3-ethylbenzothiazloine-6-sulfonic acid) and 1,1-diphenyl-2-picrylhydrazyl free radical scavenging activities. As compared to other wheat cultivars, Tosunbey cultivar had remarkable both antioxidant and enzyme inhibitory effects with the highest level of phenolics. Ferulic acid, chlorogenic acid, and apigenin were the major phenolics in extracts tested. This study suggested that an increased intake of wheat derived products could represent an effective strategy for the management of oxidative stress related chronic and degenerative diseases such as Alzheimers and diabetes mellitus.     

Effects of H2O Pretreatment on the Capacitance–Voltage Characteristics of Atomic-Layer-Deposited Al2O3 on Ga-Face GaN Metal–Oxide–Semiconductor Capacitors

Atomic layer deposition (ALD) of Al₂O₃ on Ga-face GaN is studied with respect to the effects of growth saturation, precursor injection sequence, and H₂O pretreatment. A metal–oxide–semiconductor capacitor (MOSCAP) structure is fabricated to measure the capacitance–voltage (C–V) characteristics. The origin of C–V hysteresis is explained by a model considering the different trapping behaviors of interface states and oxide border traps. The interface state density (D _it) is extracted as a function of band bending using an ultraviolet (UV)-assisted method. It is found that H₂O pretreatment followed by saturated ALD growth produces the best interface quality, with a reduced D _it compared with growth without H₂O pretreatment.     

pH Sensing Properties of Flexible,Bias‐Free Graphene Microelectrodes in Complex Fluids: From Phosphate Buffer Solution to Human Serum

Advances in techniques for monitoring pH in complex fluids can have a significant impact on analytical and biomedical applications. This study develops flexible graphene microelectrodes (GEs) for rapid (<5 s), very‐low‐power (femtowatt) detection of the pH of complex biofluids by measuring real‐time Faradaic charge transfer between the GE and a solution at zero electrical bias. For an idealized sample of phosphate buffer solution (PBS), the Faradaic current is varied monotonically and systematically with the pH, with a resolution of ≈0.2 pH unit. The current–pH dependence is well described by a hybrid analytical–computational model, where the electric double layer derives from an intrinsic, pH‐independent (positive) charge associated with the graphene–water interface and ionizable (negative) charged groups. For ferritin solution, the relative Faradaic current, defined as the difference between the measured current response and a baseline response due to PBS, shows a strong signal associated with ferritin disassembly and the release of ferric ions at pH ≈2.0. For samples of human serum, the Faradaic current shows a reproducible rapid (<20 s) response to pH. By combining the Faradaic current and real‐time current variation, the methodology is potentially suitable for use to detect tumor‐induced changes in extracellular pH.     

Modified Mackenzie Equation and CVOA Algorithm Reduces Delay in UASN

In Underwater Acoustic Sensor Network (UASN), routing and propagation delay is affected in each node by various water column environmental factors such as temperature, salinity, depth, gases, divergent and rotational wind. High sound velocity increases the transmission rate of the packets and the high dissolved gases in the water increases the sound velocity. High dissolved gases and sound velocity environment in the water column provides high transmission rates among UASN nodes. In this paper, the Modified Mackenzie Sound equation calculates the sound velocity in each node for energy-efficient routing. Golden Ratio Optimization Method (GROM) and Gaussian Process Regression (GPR) predicts propagation delay of each node in UASN using temperature, salinity, depth, dissolved gases dataset. Dissolved gases, rotational and divergent winds, and stress plays a major problem in UASN, which increases propagation delay and energy consumption. Predicted values from GPR and GROM leads to node selection and Corona Virus Optimization Algorithm (CVOA) routing is performed on the selected nodes. The proposed GPR-CVOA and GROM-CVOA algorithm solves the problem of propagation delay and consumes less energy in nodes, based on appropriate tolerant delays in transmitting packets among nodes during high rotational and divergent winds. From simulation results, CVOA Algorithm performs better than traditional DF and LION algorithms.     

HPWO-LS-based deep learning approach with S-ROA-optimized optic cup segmentation for fundus image classification

Neural Computing and Applications - Recently, automated retinal image processing has been considered a competitive field of research due to the low-accuracy results, complexity, and unacceptable...     

Accurate object recognition in the underwater images using learning algorithms and texture features

Underwater image processing is very challenging due to its environmental conditions and poor sunlight. Images captured from the ocean using autonomous vehicles are often non-uniformly illuminated and contain noise due to the underlying environment. Object recognition is a challenging task under water due to the variation in the environment, target shape and orientation. Traditional algorithms based on spatial information may not lead to accurate segmentation as the intensity variation is often less in underwater images. Texture information representing the characteristics of the object is needed. Statistical features like autocorrelation, sum average, sum variance and sum entropy were extracted. These were fed as input to learning algorithms and training was done to effectively classify the object of interest and background. Chain coding was further applied for object recognition. The proposed methodology achieved a maximum classification accuracy of 96%.     

An Efficient Code Domain NOMA Scheme with Enhanced Spectral and Energy Efficiency for Networks Beyond 5G

Wireless Personal Communications - Non-Orthogonal Multiple Access (NOMA) is an efficient multiple access scheme which augments the capacity and overall throughput in LTE and 5G networks. Tackling...     

Health monitoring and fault prediction using a lightweight deep convolutional neural network optimized by Levy flight optimization algorithm

Neural Computing and Applications - Agricultural machines (AMs) refer to equipment usually used in agriculture such as tractors, hand tools, and power tools. It reduces the labor work, increases...     

Streptococcus thermophilus strains: Multifunctional lactic acid bacteria

Streptococcus thermophilus has “Generally Recognized as Safe” status and is extensively used for the manufacture of several important fermented dairy foods, including yoghurt and some cheese varieties (Swiss, Limburger, Brick). S. thermophilus also has a number of functional activities such as production of extracellular polysaccharides, bacteriocins and vitamins. In addition, it also has potential as a probiotic, as demonstrated by various health effects, transient survival, and moderate adherence in the gastrointestinal tract. Therefore, the natural diversity among S. thermophilus strains with respect to their capacity to produce different metabolites has the potential to be exploited beyond fermentation for lactic acid production.