RESUMEN
Pneumonia is a lung infection caused by bacteria, viruses and fungi. In this infection, the air sac (alveoli) of the lungs gets inflamed and breathing becomes difficult which causes mild to severe illness among people. They are diagnosed by performing chest X-ray, blood test, pulse oximetry. Pneumonia can also be identified using lung sounds that are recorded in the digital stethoscope. In this proposed work, a software is developed to diagnose pneumonia from the lung sound using gradient boosting algorithm. Lung sounds give enough symptoms for pneumonia identification. Lung sounds are recorded by doctors using Electronic Stethoscope. The recorded lung sounds are processed using audacity software. This software separates the required sound from unwanted noises. The healthy individual's audio files are labelled as 0 and the pneumonia patient's audio files are labelled as 1 for training the algorithm. During diagnosis study and the performance evaluation with various machine learning algorithms like support vector machine and k-nearest neighbours (KNN) algorithms, it was observed that the gradient boosting algorithm exhibits good identification property with 97 percent accuracy. This proposed method also reveals excellent diagnoses of pneumonia over other artificial intelligence and deep learning techniques. This method can also be used to predict Covid affected lungs sounds.
RESUMEN
In this work, graphene oxide-p-Phenylenediamine nanocomposites of two different ratios of Graphene oxide: p-Phenylenediamine (1:1 and 1:5) were prepared and characterized by using analytical, spectroscopic and microscopic studies (GO-pPD 11 and GO-pPD 15). These nanocomposites were employed as fluorescent chemosensors for sensing potential cations. Remarkably, graphene oxide-p-Phenylenediamine nanocomposites of ratio 1:1 (GO-pPD 15) was selective and sensitive to Ag+ ions, whereas the graphene oxide-p-Phenylenediamine nanocomposites of ratio 1:5 (GO-pPD 15) was selective to Ce3+ions. A possible mechanism as switch "off-on" is proposed built on the inhibition of the photo induced electron transfer process in both the fluorescent probes in detecting the metal ions. In addition, interference studies were performed with the help of competitive complexation analysis and no significant interference were found by other potentially competing cations. The pH studies revealed that both the chemosensors can be used at the physiological pH for the ion detection and also the detection time was within 2-3 min. Both the chemosensors show good reversibility and hence the sensors can be used for multiple times. The newer nanocomposites were then utilized in the real water sample analysis as to check its real level application purpose.
Asunto(s)
Grafito , Nanocompuestos , Iones , FenilendiaminasRESUMEN
In this report, a new design is proposed for the detection of silver ions using Graphene Oxide-Titanium oxide (GO/TiO2) composite. The GO was synthesized by modified Hummers method and the composite is synthesized by chemical reflux method. The surface morphology of the composite was analyzed using a scanning electron microscope (SEM), and it is clearly observed that TiO2 spheres are adsorbed on the surface of GO in a disordered manner. X-ray Diffraction (XRD) results confirm the presence of TiO2 on GO. Photoluminescence (PL) spectra show the reduced recombination of charge carriers in the (GO/TiO2) composite. The resulting composite selectively detects silver ions over other potentially competing metal ions with no notable interference monitored by fluorescence.
RESUMEN
In the present work, ZnO nanorods and ZnO/GO/CNT nanocomposite have been prepared by microwave assisted method using various time of incorporation of GO/CNT. The structural and optical characterizations were performed by X-ray diffraction (XRD), Scanning electron microscope (SEM), UV-Visible spectrometer (UV-Vis) and Photoluminescence (PL). The XRD data showed that the most intense peak at 36° belong to (101) plane of ZnO nanorods. SEM results showed the formation of nano rods assembled in flower like structure. UV spectra shows that the samples absorb ultraviolet light and had a band gap value of 3.1-3.2 eV. The PL spectra showed the lowest PL intensity band for ZnO/GO/CNT-A. Higher photocatalytic degradation of 91% was determined in ZnO/GO/CNT composite when GO/CNT was added at the end of the procedure.
RESUMEN
Visible light induced photocatalyst BiVO4 with monoclinic scheelite structure has been synthesised via sol gel method assisted by ultrasonication. The prepared samples were characterised using X-ray diffraction (XRD), scanning electron microscope (SEM), UV-Vis diffused reflectance spectroscopy (DRS) techniques. The photocatalytic efficiency was evaluated by decolourisation of MB under visible light irradiation. The effect of ultrasound output power on the properties of BiVO4 during and after preparation by sol-gel method has been compared with normal agitated sample (As prepared). The power of ultrasonic vibration has been varied and an ideal output power which yields better catalytic efficiency is determined. BiVO4 sonicated with 80â¯W during preparation 80â¯W (D) exhibited relatively high surface area, better surface morphology and better catalytic efficiency compared to other samples which were sonicated with 100, 160 and 200â¯W. The results signify that the photodegradation rate of BiVO4 80â¯W (D) sample is high up to 96% in 90â¯min compared to other samples. Change in morphology leading to better catalytic efficiency was obtained just by exposing the sample to ultrasonic radiation without addition of any surfactant. The recovery test showed that the sample was stable for four consecutive cycles. Using radical test, a reasonable mechanism for photodegradation has been proposed.