Biological Activity of Crude Extracts of Endophytic Fusarium Oxysporum and its Chemical Composition by Gas Chromatography–Mass Spectrometry
In this study, Fusarium oxysporum AUMC9264 was isolated from Lupinustermis L. which was identified by a morphological method and 18S rDNA sequence comparison. Potato Dextrose Agar (PDA) was used for activation and subcultures of the fungal isolate while, Potato Dextrose Broth medium (PDB) used for metabolite production. The fungal extracts were tested in vitro for their Antimicrobial effects against some strains of bacteria and fungi. Ergosterol was isolated from the crude extract and elucidate according to 1H-NMR and its mass spectrometry analysis, n-Hexan fraction was identified by gas chromatography– mass spectrometry.
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Spatial Assessment of Severe Malaria Incidence in Kano Sate Using Multivariate Statistical Technique
Severe malaria continues to be one of the most common and serious life-threatening disease causing high morbidity and mortality world-wide. Multivariate statistical techniques including principal component analysis (PCA) and hierarchical agglomerative cluster analysis (HCA) were applied to the raw data of severe malaria cases. PCA results identified two varifactors which were responsible for about 53% of the total variance in the data set. Rainfall possesses the highest strong positive loading (0.718) among the variables. HCA identified three spatial clusters representing high, moderate and low incidence zones. The study suggest prompt reporting of malaria cases to modern healthcare centres for proper attention so as to reduce the mortality rate attached to the disease.
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Leap-Frogging Challenges & Possibilities for Renewable Energy Transition in Developing Countries
Shifting to new energy as well as other low carbon solutions was conceived and viewed as serious challenge even to the most developed countries in the world. Hence, with the disadvantaged position of the least developing countries, whom, in most locations around the world are at the highest risk of climate change effect, the challenges will be even more higher. These are from the perspective of technology, finance and policies of ensuring smooth renewable energy transition in these countries. However, within this challenge, there is opportunity to start enjoying new energy particularly in areas where not much investment is done in the fossil technologies. The study highlights these challenges as they are posed by climate change and the opportunities by way of estimating the investment requirements and environmental vis economic benefits of leapfrogging in West African sub-region. Reasons for slow to non-adoption of RE in developing countries as well as arguments for the possibilities of leap-frogging to renewables are also reviewed, so also the challenges/barriers associated with the process of leap-frogging are highlighted. At the end, a simple Emission/Energy Demand Based Strategy depending on energy intensity and necessity is proposed and a very good case-study of leap-frogging to renewables in developing countries is discussed. It is established that, slowly developing countries can and should choose not to be only victims of, but take the opportunity presented by climate change.
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Short Term Load Forecasting Using Time Series Neural Network
Short term load forecasting is very essential for daily planning in an electrical system. Power demand for the next few hours or days need to be predicted for smooth and economical running of a power system. Prior data is essential to make the prediction. There are different methods to do the forecasting or prediction based on previous data. This paper analyses the time series method of forecasting.
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An Automation in Indian Railways for Lavatory and Coach Electricity Management
The idea behind this study is to provide a solution on some problems faced in Indian Railways. Points taken in concern while working on this study are Cleanliness & power generation. Those it has been mentioned everywhere to do not use lavatories while train is at station, still it is observed that such notice is merely followed. Using some techniques like piezoelectric sensors for power generation and RFID for lavatory door locking automation, we can solve the problem faced.
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A Survey on Image Hiding Scheme Using Haar DWT, Data Compression and Encryption Techniques
Steganography techniques are helpful to hide the secret information in cover media and thus aid in enhancing the security of sensitive data during transmission and storage. Applying discrete wavelet transform helps to convert the image to the frequency domain. Haar wavelet transform is used to obtain the low frequency approximate (LL) detail and three high frequency detailed (LH, HL, HH) details. As the detailed sub bands have less sensitive information these are used for embedding the secret information. The secret information in the form of image can be reduced to one fourth size using haar transform. Encoding methods can be used to reduce the size of the image and encrypting the compressed data with the known key can help to enhance the security. The quality of stegoimage is measured using PSNR. The hiding capacity can be measured to compare with the other techniques of steganography.
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Digital Image Forgery Detection Using Passive Techniques by Means of Keypoint Classification
In today’s era manipulation of image has become a simple task because of advanced photo editing software packages as well as the capturing devices having high resolution. Verification of the truthfulness of images as well as detection of tampering without having the extra prior knowledge of image content is a significant research field. An attempt is made to review the recent developments in digital image forgery detection. Passive methods do not require prior information about the image. In this paper first various image forgery detection techniques are classified and then its general structure is developed. Passive image authentication overview is presented and the existing passive forgery detection techniques are reviewed. The present status of image forgery detection technique is discussed along with a recommendation for future research. In this paper the effort has been made for finding the best forgery detection algorithm such as SIFT for identifying the manipulated region. The common scenario has been considered where the goal is to remove the features. The attacks conceived so far against SIFT-based forensic techniques implicitly assume that all SIFT keypoints have similar properties. It is better to use SIFT classification scheme based on the gray scale histogram of the neighborhood of SIFT keypoints.
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The EM Algorithm and Some Expressive Properties for Logistic Mixtures
The Expectation-Maximization (EM) algorithm is a parameter estimation method which performs to the general data frame of maximum-likelihood estimation, including some applications to data analysis and statistics. There is the work by Dempster, Laird and Rubin (1977) on the key features of defining the EM algorithm. Logistic mixtures, unlike normal mixtures, have not been studied for the EM algorithm. In this paper, we express the theorem about a relationship between the gradient of the log likelihood and the step in parameter space taken by the EM algorithm in their multivariate extension for the mixture logistic distribution (see Malik and Abraham (1973)). The literature on determination of the number of modes in logistic mixture models has focused primarily on univariate mixtures. In fact, there is a simple description of modality when one is mixing two univariate components. In particular, an analogue of the techniques such as the paper written by Robertson and Fryer (1969) allows to attain the results in the case of the convex combination of two item response functions (IRFs) for the unidimensional dichotomous 1-parameter to 4-parameter logistic (1PL to 4PL) item response theory (IRT) models.
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Policy perception and personality features relationship modeling on knowledge sharing
Knowledge is a key source for today organizations. All of the organizations today found that knowledge is a competitive advantages resource and intangible wealth of organizations. Humans activities like knowledge sharing among organization members , is the base of productivity process from knowledge in organizations. In this direction , present research is studying personality features and policy perception on knowledge sharing and determines job satisfaction intermediacy role. Statistical sample of the study is 108 individuals from women principles of 3-area Mashhad education ,that has been randomly selected. For gathering data , questionnaire was used (with content approval in content and facto analysis and reliability method with Kronbakh Alfa coefficient computation). In order to analysis of data and hypothesis tests, structural equations was used . Results showed that policy perception in organization don’t have meaningful effect in knowledge sharing, personality features has meaningful effect in knowledge sharing and job satisfaction has intermediacy role in relation between personality features on knowledge sharing.
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An uncommon presentation of Brain Metastasis from Nasopharyngeal Carcinoma: A Case Report and literature review
Brain metastases from nasopharyngeal carcinoma, either through a hematogenous route or through the cerebrospinal fluid, are uncommon. Imaging is crucial in evaluating the local extension. It also allows to determinate the irradiation field, to monitor the lesions progression or recession and to detect treatment complications. We aim to expose the case of a patient with metastatic undifferentiated nasopharyngeal carcinoma presenting a recurrence in central nervous system revealed by hemiparesis.
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