The effect of DL alpha-lipoic acid on the nephrotoxic potential of gentamicin was examined. Intraperitoneal injection of gentamicin (100 mg/kg/day) to rats resulted in decreased activity of the glycolytic enzymes-hexokinase, phosphoglucoisomerase, aldolase and lactate dehydrogenase. The two gluconeogenic enzymes--glucose-6-phosphatase and fructose-1,6-diphosphatase, the transmembrane enzymes namely the Na+, K(+)-ATPase, Ca(2+)-ATPase, Mg(2+)-ATPase and the brushborder enzyme alkaline phosphatase, also showed decreased activities. This decrease in the activities of ATPases and alkaline phosphatase suggests basolateral and brush border membrane damage. Decreased activity of the TCA cycle enzymes isocitrate dehydrogenase (ICDH), succinate dehydrogenase (SDH) and malate dehydrogenase (MDH), suggests a loss in mitochondrial integrity. These biochemical disturbances were effectively counteracted by lipoic acid administration. Lipoic acid administration by gastric intubation at two different concentrations (10 mg and 25 mg/kg/day) brought about an increase in the activity of the glycolytic enzymes, ATPases and the TCA cycle enzymes. The gluconeogenic enzymes however showed a further decrease in their activities at both the concentrations of lipoic acid administered. These observations shed light on the nephroprotective action of lipoic acid against experimental aminoglycoside toxicity and the protection afforded at 25 mg/kg/day of lipoic acid was noted to be higher than that at 10 mg level.
Speaker recognition in an emotive environment is a bit challenging task because of influence of emotions in a speech. Identifying the speaker from the speech can be done by analyzing the features of the speech signal. In normal conditions, identifying a speaker is not a tedious task. Whereas, identifying the speaker in an emotional environment such as happy, sad, anger, surprise, sarcastic, fear etc. is really challenging, since speech becomes altered under emotions and noise. The spectral features of speech signal include Mel Frequency Cepstral Coefficients(MFCC), Shifted Delta Cepstral Coefficients (SDCC), spectral centroid, spectral roll off, spectral flatness, spectral contrast, spectral bandwidth, chroma-stft, zero crossing rate, root mean square energy, Linear Prediction Cepstral Coefficients (LPCC), spectral subband centroid, Teager energy based MFCC, line spectral frequencies, single frequency cepstral coefficients, formant frequencies, Power Normalized Cepstral Coefficients (PNCC), etc. The features that are extracted from the speech signal are classified using classifiers. Support Vector Machine(SVM), Gaussian Mixture Model, Gaussian Naive Bayes, K-Nearest Neighbour, Random Forest and a simple Neural Network using Keras is used for classification. The important application include security systems in which a person can be identified by biometrics that is voice of the person. The work aims to identify the speaker in an emotional environment using spectral features and classify using any of the classification techniques and to achieve a high speaker recognition rate. Feature combinations can also be used to improve accuracy. The proposed model performed better than most of the state-of-the-art methods.
The intraperitoneal administration of gentamicin (100 mg kg ؊1 day ؊1 ) to rats is associated with an increased production of malondialdehyde (MDA), which is an end product of lipid peroxidation in the kidney. The level of glutathione (GSH) and the activity of three antioxidant systems-superoxide dismutase (SOD), catalase (CAT) and glutathione peroxidase (GPx)-were also decreased in the kidney. The liver, however, did not show any such alterations.Gentamicin (100 mg kg ؊1 day ؊1 ) plus lipoic acid administration (25 mg kg −1 day −1 ) by gastric intubation brought about a decrease in the degree of lipid peroxidation. An increase in the GSH level and in the activity of SOD, CAT and GPx was also observed. From these observations it can be concluded that administration of DL-␣-lipoic acid prevents lipid peroxidation, which may, at least partly, play an important role in the injury cascade of gentamicin-induced nephrotoxicity.
Due to the advance in network technologies, the number of network users is growing rapidly, which leads to the generation of large network traffic data. This large network traffic data is prone to attacks and intrusions. Therefore, the network needs to be secured and protected by detecting anomalies as well as to prevent intrusions into networks. Network security has gained attention from researchers and network laboratories. In this paper, a comprehensive survey was completed to give a broad perspective of what recently has been done in the area of anomaly detection. Newly published studies in the last five years have been investigated to explore modern techniques with future opportunities. In this regard, the related literature on anomaly detection systems in network traffic has been discussed, with a variety of typical applications such as WSNs, IoT, high-performance computing, industrial control systems (ICS), and software-defined network (SDN) environments. Finally, we underlined diverse open issues to improve the detection of anomaly systems.
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