ABSTRACT In the diagnosis of cardiac disorders Heart sound has a major role, and early detection is crucial to safeguard the patients. Computerized strategies of heart sound classification advocate intensive and more exact results in a quick and better manner. Using a hybrid optimization-controlled deep learning strategy this paper proposed an automatic heart sound classification module. The parameter tuning of the Deep Neural Network (DNN) classifier in a satisfactory manner is the importance of this research which depends on the Hybrid Sneaky optimization algorithm. The developed sneaky optimization algorithm inherits the traits of questing and societal search agents. Moreover, input data from the Phonocardiogram (PCG) database undergoes the process of feature extraction which extract the important features, like statistical, Heart Rate Variability (HRV), and to enhance the performance of this model, the features of Mel frequency Cepstral coefficients (MFCC) are assisted. The developed Sneaky optimization-based DNN classifier’s performance is determined in respect of the metrics, namely precision, accuracy, specificity, and sensitivity, which are around 97%, 96.98%, 97%, and 96.9%, respectively.

AbstractThis article presents a study that compares the performance and emission characteristics of a four‐stroke, four‐cylinder spark ignition (SI) engine fueled by gasoline and neat hydrogen. The engine was equipped with turbocharging to optimize ignition timing for power boosting and vaporized water–methanol injection to reduce emissions. Engine tests were conducted at speeds ranging from 2000 to 6000 rpm, with a fixed intake pressure and varying quantities of hydrogen and spark advance timings. The study compared the results of non‐turbocharged and turbocharged engines with water–methanol injection in terms of combustion, performance, and emissions. The findings showed that the turbocharged water–methanol hydrogen operation had a higher brake thermal efficiency (BTE) than its counterpart, while the brake power of the hydrogen engine operation increased with turbocharging but slightly decreased with water–methanol injection. Additionally, volumetric efficiency improved by 7% for turbocharged and 4% for water‐injected hydrogen engine operation compared to the counterpart. The cylinder pressure for turbocharging with water–methanol operation yielded 16.32% higher compared with counterpart gasoline engine operation. Finally, nitrogen oxides (NOx) emissions were reduced with turbocharging and water–methanol injection compared to the counterpart non‐turbocharged hydrogen engine operation.

The surface chemistry and decent morphology of electrode materials are highly desirable for high-performance energy storage/conversion devices. Bimetallic oxides especially nickel cobalt oxide (NCO) have gained substantial attention in energy storage/conversion devices owing to their exclusive electronic properties. Herein, flower-like nickel cobalt oxide (NiCo2O4) was prepared by a facile hydrothermal method for different reaction times. The properties of obtained samples were characterized through X-ray diffraction (XRD), EDS, field-emision scanning electron microscopy (FE-SEM), and high-resolution transmission electron microscopy (HR-TEM). The cyclic voltammogram (CV), Galvanostatic changing discharging (GCD), and electrochemical impedance spectroscopy (EIS) were employed for the evaluation of the electrochemical performances of the resultant product. The flower-like NiCo2O4 electrode exhibits high areal capacity (392 mF cm−2 at 0.5 mA cm−2) and the electrode shows an energy density of about 9.1 µWh cm−2 at power density 102 µW cm−2. The excellent electrochemical performance of the fabricated supercapacitor offers good areal capacitance and energy density that exceeds several carbon-based materials.

To fulfill the global energy demands, the growth of high-capacity electrochemical energy storage (EES) devices with advanced electrode materials is highly desirable. Supercapacitors (SCs), a perfect energy storage device, can significantly attain the objective of high energy along with high-power densities. Herein, we successfully prepare the binary metal oxide Co3V2O8 (CVO) by altering the concentrations of vanadium through the facile hydrothermal method. Various characterization tools such as XRD, SEM, TEM, and EDX have been utilized to explore the physicochemical properties of CVO. The electrochemical characterization of CVOs has been carried out with three-electrode geometry. The electrochemical investigation of the samples was executed in a 2M aqueous potassium hydroxide (KOH) electrolyte. The resultant electrodes show elevated values of the specific capacitance of about 224, 241, and 184 F/g, respectively at a persistent current density of 5 mA/cm2. The as-fabricated advanced supercapacitors exhibited excellent energy densities of about 4.88, , 4.99 , and 3.79 Wh/kg at power densities of about 80.41 , 80.42 , and 77.62 W/kg, respectively. The improvement in specific capacitance, higher energy density, and power density indicates Co3V2O8 could be an appealing material for SCs electrodes.

Curcuma longa L. (Turmeric) a perennial herb belongs to Zingiberaceae. It’s highly grown for its remarkable medicinal uses. Apart from medicinal properties and importance; Turmeric has not been emphasized much with respect to agricultural view. Sustainable agriculture is need of hour and hence it must be brought in practice on large scale. Arbuscular Mycorrhizal (AM) fungi has mutually beneficial relationship with the roots and support plants during biotic and abiotic stress. The function of AM fungi in different morphological parameters when Turmeric under biotic stress shows scanty records so far. Existing research studies are intended to evaluate an influence of AM fungi on Turmeric plant during biotic stress. During this investigation Turmeric plants were assessed for Growth and Vigour Index, relative mycorrhizal dependency, some biochemical contents and fresh weight of the rhizome. Statistical analysis of the results obtained showed strongly significant results.