Coinciding Diabetic Retinopathy and Diabetic Macular Edema Grading With Rat Swarm Optimization Algorithm for Enhanced Capsule Generation Adversarial Network.

In the worldwide working-age population, visual disability and blindness are common conditions caused by diabetic retinopathy (DR) and diabetic macular edema (DME). Nowadays, due to diabetes, many people are affected by eye-related issues. Among these, DR and DME are the two foremost eye diseases, the severity of which may lead to some eye-related problems and blindness.

Identification of novel inhibitor against human phosphoethanolamine cytidylyltransferase from phytochemicals of Citrus sinensis peel extract by in vitro and in silico approach.

Kidney stone is a major global menace that demands research on nonsurgical treatment involving biological compounds for the benefit of the patients. Among the biological extracts, citric acid is traditionally used to dissolve kidney stones. The current research focuses on evaluating the in vitro anti-urolithiatic activity and in silico study of ethanolic extract of Citrus sinensis (ECS) peel against c: phosphoethanolamine cytidylyltransferase (PCYT).

Synthesize and characterization of CaOx crystals against various citrus waste peel extracts: an study.

Citrus fruits have been consumed by world's population for several centuries. Since it's an edible source possesses various uses in treating many diseases. Among various diseases urolithiasis is one of the major issues globally demands in painless surgical treatment.

A new design of multimedia big data retrieval enabled by deep feature learning and Adaptive Semantic Similarity Function.

Nowadays, multimedia big data have grown exponentially in diverse applications like social networks, transportation, health, and e-commerce, etc. Accessing preferred data in large-scale datasets needs efficient and sophisticated retrieval approaches. Multimedia big data consists of the most significant features with different types of data.

CAD system for lung nodule detection using deep learning with CNN.

The early detection of pulmonary nodules using computer-aided diagnosis (CAD) systems is very essential in reducing mortality rates of lung cancer. In this paper, we propose a new deep learning approach to improve the classification accuracy of pulmonary nodules in computed tomography (CT) images. Our proposed CNN-5CL (convolutional neural network with 5 convolutional layers) approach uses an 11-layer convolutional neural network (with 5 convolutional layers) for automatic feature extraction and classification.

Effect of nanoparticle-blended biodiesel mixtures on diesel engine performance, emission, and combustion characteristics.

The research work investigates the combustion, performance, and emission characteristics of a CI engine using neat biodiesel (B100: 100% rubber seed oil methyl ester) mixed with alumina and titanium oxide nanoparticles in the proportions of 25 ppm and 50 ppm separately. Nanoparticles (alumina and titanium dioxide) in different proportions like 25 ppm and 50 ppm were mixed with the neat biodiesel, and 2% of surfactant (Span80) was added, and the mixtures were agitated by an ultrasonicator to achieve uniform particle dispersion in the blend. The nanoparticle-blended biodiesel mixtures are designated as B100A25 (B100 + 25 ppm of alumina), B100A50 (B100 + 50 ppm of alumina), B100T25 (B100 + 25 ppm of TiO), and B100T50 (B100 + 50 ppm of TiO).

Automatic Detection and Classification of Lung Nodules in CT Image Using Optimized Neuro Fuzzy Classifier with Cuckoo Search Algorithm.

The Lung nodules are very important to indicate the lung cancer, and its early detection enables timely treatment and increases the survival rate of patient. Even though lots of works are done in this area, still improvement in accuracy is required for improving the survival rate of the patient. The proposed method can classify the stages of lung cancer in addition to the detection of lung nodules.

Growth of N-Glycyl-L-Valine (GV) single crystal and its spectral, thermal and optical characterization.

A nonlinear optical crystal of N-Glycyl-L-Valine (GV) single crystals was grown by slow evaporation solution growth technique from an aqueous solution. The unit cell parameters and the crystal structure were determined by single crystal X-ray diffraction study. The Fourier transform infrared (FTIR) and proton nuclear magnetic resonance ((1)H NMR) spectral studies were carried out to identify the functional groups of the grown crystals.