Inhibition of Xanthomonas fragariae, Causative Agent of Angular Leaf Spot of Strawberry, through Iron Deprivation.

In commercial production settings, few options exist to prevent or treat angular leaf spot (ALS) of strawberry, a disease of economic importance and caused by the bacterial pathogen Xanthomonas fragariae. In the process of isolating and identifying X. fragariae bacteria from symptomatic plants, we observed growth inhibition of X. fragariae by bacterial isolates from the same leaf macerates. Identified as species of Pseudomonas and Rhizobium, these isolates were confirmed to suppress growth of X. fragariae in agar overlay plates and in microtiter plate cultures, as did our reference strain Pseudomonas putida KT2440. Screening of a transposon mutant library of KT2440 revealed that disruption of the biosynthetic pathway for the siderophore pyoverdine resulted in complete loss of X. fragariae antagonism, suggesting iron competition as a mode of action. Antagonism could be replicated on plate and in culture by addition of purified pyoverdine or by addition of the chelating agents tannic acid and dipyridyl, while supplementing the medium with iron negated the inhibitory effects of pyoverdine, tannic acid and dipyridyl. When co-inoculated with tannic acid onto strawberry plants, X. fragariae's ability to cause foliar symptoms was greatly reduced, suggesting a possible opportunity for iron-based management of ALS. We discuss our findings in the context of 'nutritional immunity,' the idea that plant hosts restrict pathogen access to iron, either directly, or indirectly through their associated microbiota

TICO: a tool for postprocessing the predictions of prokaryotic translation initiation sites

Exact localization of the translation initiation sites (TIS) in prokaryotic genomes is difficult to achieve using conventional gene finders. We recently introduced the program TICO for postprocessing TIS predictions based on a completely unsupervised learning algorithm. The program can be utilized through our web interface at and it is also freely available as a commandline version for Linux and Windows. The latest version of our program provides a tool for visualization of the resulting TIS model. Although the underlying method is not based on any specific assumptions about characteristic sequence features of prokaryotic TIS the prediction rates of our tool are competitive on experimentally verified test data

BI APPLICATION IN FINANCIAL SECTOR -CREDIT SCORING OF RETAIL LOANS USING A HYBRID MODELING APPROACH

Retail Loans now-a-days form a major proportion of Loan Portfolio. Broadly they can be classified as (i) Loans for Small and medium Sector and (ii) Loans for Individuals. The objective of Credit Scoring is that we use enough of precaution before the sanction of the loan so that the loans do not go bad after disbursement. This will increase to the bottom line of the financial institution and also reduce the Credit Risk.Techniques used to perform Credit Scoring Varies for the above two classes of loans. In this paper, we concentrate on the application of Credit Scoring for individual or so called personal loans like – Auto loan, buying goods like Televisions, Refrigerators etc. Large numbers of loans are being disbursed in these areas. Though the size of the loan may be small, when compared to Small/Medium Scale Industry, if one does not control the defaults, the consequences will be disastrous.From the characteristics of borrower, product characteristics a Credit Score is computed for each applicant. If the Score exceeds a given threshold loan is sanctioned. If it is below the threshold, loan is sanctioned. If it is below the threshold, loan is rejected. In practice a buffer zone is created near the threshold so that those Credit Scores that fall in buffer zone, detailed investigation will be done before a decision is taken.Two broad classes of Scoring Model exists (i) Subjective Scoring and (ii) Statistical Scoring.Subjective Scoring is based on intuitive judgement. Subjective Scoring works but there is scope for improvement one limitation is prediction of risk is person dependent and focuses on few characteristics and may be mistakenly focusing on wrong characteristics.Statistical Scoring uses hardcore data of borrower characteristics, product characteristics and uses mathematical models to predict the risk. The relation is expressed in the form of an equation which finally gets converted to a score. Subjectivity will be reduced and variable(s) that are important to scoring are identified based on strong mathematical foundation.Different Models have been used in Credit Scoring like Regression, Decision Tree, Discriminate Analysis and Logistic Regression. Most of the times, a single model is used to compute the Credit Score. This method works well when the underlying decision rule is simple and when the rule becomes complex, the accuracy of the model diminishes very fast.In this Research Paper, a combination of Decision Tree and Logistic Regression is used to determine the weights that are to be assigned to different characteristics of the borrower. Decision Tree is used at first level of analysis to narrow down the importance of Variables and overall weights that needs to be assigned. It is also used for optimum groupings of numeric and non-numeric Variables. At second level, Logistic Regression is used to compute odd ratios a variant of probability, which in turn is used to assign weights for an attribute and to individual levels in an attribute.This has been tested on real life data and found to work better compared to methods using a single stage models. An accuracy of around 80% in decision is obtained which is good for any modeling study as there is no model which gives 100% accuracy.The next Section explains the Methodology, Data Used and Results.SPSS Software has been used for Model Building and Data Analysi

Global Symposium on Women in Fisheries

All over the world, women contribute in multiple ways to the production, processing, marketing and management of fish and other living aquatic resources. The first ever Global Symposium on Women in Fisheries, held in Kaohsiung, Taiwan on 29 November 2001 generated the present collection of papers on women in fisheries. The reader of this volume will find in it a wealth of information, albeit in a very heterogeneous form, that the authors have had to draw from many different sources. Some are primary research studies whereas most are historical reviews from first hand experience of the authors or derived from other written materials, often contained in reports of fisheries development projects, newspapers and source materials well outside the fish sectors.Women, Participation, Sustainability, Poverty, Fisheries, Development projects, Fishery technology

ENHANCING SECURITY AND PRIVACY IN THE CLOUD COMPUTING

ABSTRACT Cloud computing is current buzzword in the market. Security to this Service is an important issue. PKI (Public key Infrastructure), as a Service and its focus is to evaluate the possibility to deploy a Public Key Infrastructure as a Cloud service. This is interesting since more and more organizations are moving their services and infrastructure to the cloud to benefit from the possibilities and advantages of cloud services and avoid problems with having own infrastructures. It is also interesting since the cloud could utilize the distributed architecture of PKI and in this way increase the reliability and availability and decrease the response times for validation of certificates

Secure Single-Sit Data Sharing for Dynamic Groups in Cloud

Abstract-Cloud computing has emerged as a new type of commercial paradigm. Cloud and its services got wide popularity among the IT industry in a short span of time. With the character of low maintenance and ease of use cloud services are extended for resource sharing among cloud users. Sharing among group is still a challenging issue, due to frequent change of membership. The main issues are related to identity privacy and data privacy. Group sharing may not scale well for individual data access when sharing highly confidential and sensitive data in the group. In this paper, we propose a secure dynamic group sharing among several members of a group rather than individuals. Any user can share data with others in the group, but access available in the presence of minimum no of users only. The storage overhead and cryptography is independent of no of users in the group

Study on Security of Online Voting System Using Biometrics and Steganography

Abstract: It is very important to provide security to voting system and mostly which is online one. In this paper we provide security to online voting system with secure user authentication by providing biometric as well as password security to voter accounts. Basic idea behind this is to combine secret key with cover image on the basis of key image. As a result such new image is produced by system called stego image which is quite same as cover image. The key image is a biometric measure, such as a fingerprint image. Extraction of stego image is take place at server side to perform the voter authentication. The system minimizes the risk factor as hacker needs to find not only the template but also secret key and it is not possible. It makes election procedure to be secure against a variety of fraudulent behaviors. To improve speed SHA 256 used for hashing is replaced with MD5

Prediction of Lithology using the Ratios of Compressional and Shear Wave Velocities and their Travel Times

ABSTRACT The ratio of compressional wave to shear wave velocities, and the ratio of their travel times are important parameters for interpretation of geophysical field data. Recent studies have emphasized the role played by pore geometry in controlling ⁄ . To infer lithologies, the ratios of ⁄ and were cross-plotted. ⁄ ranges from 0.0706 to 2.568 m/s and varies from 0.483 to 1.655 m/s. These variations were due soil composition, total porosity and pore geometry. The various lithologies inferred through this study conformed to those obtained from the field