EFFECTS OF NIPAH VIRUS IN TODAY’S WORLD

The effect of Nipah Virus Infection is increasing day by day in today’s scenario and more number of cases are found in various countries. In India it was discovered in Sikkim, Siliguri and West Bengal. It is near borders with China, Bangladesh, Nepal, and Sikkim. The primary pathways of transmission is from bats to people, in Bangladesh its transformed via contamination of raw date palm sap by bats with subsequent consumption by humans and through infection of domestic animals (cattle, pigs, and goats), presumably from consumption of food contaminated with bat saliva or urine with subsequent transmission to people. It is found in both species of humans as well as animals more number of deaths was found in the both spices, hence zoonotics. Laboratory investigations at the time of the outbreak did not show or identify an infectious agent. Approximately half of recognized Nipah cases in Bangladesh developed their disease following person to person transmission of the virus. Efforts to prevent transmission should focus on decreasing bat access to date palm sap and reducing family members' and friends' exposure to infected patients' saliva or body fluids

An efficient hybrid approach for medical images enhancement

Medical images have various critical usages in the field of medical science and healthcare engineering. These images contain information about many severe diseases. Health professionals identify various diseases by observing the medical images. Quality of medical images directly affects the accuracy of detection and diagnosis of various diseases. Therefore, quality of images must be as good as possible. Different approaches are existing today for enhancement of medical images, but quality of images is not good. In this literature, we have proposed a novel approach that uses principal component analysis (PCA), multi-scale switching morphological operator (MSMO) and contrast limited adaptive histogram equalization (CLAHE) methods in a unique sequence for this purpose. We have conducted exhaustive experiments on large number of images of various modalities such as MRI, ultrasound, and retina. Obtained results demonstrate that quality of medical images processed by proposed approach has significantly improved and better than other existing methods of this field

Business Decision Making by Big Data Analytics

Information is the key component towards success when it comes to controlling the decision-makers performance with the quality of a decision. In the modern era, an absolute amount of data is available to organizations for analysis usage. Data is the most important component of the business in the 21st century and a significant number of devices are already equipped with the internet. Based on this the solutions should be studied in order to control and capture the knowledge value pair out of the datasets. Following this, the decision-makers should have access to insightful and valuable data based on the dynamic high volume & velocity using big data analytics. Our research focuses on how to integrate big data analytics into the decision-making process. The B-DAD (big data analytics and decision) framework was created to map the big data tools, its architecture, and analytics for the several decision-making steps by the adoption of methodology based on design science. The ideal goal and offerings of the framework are adopting big data analytics in order to intensify & aid decision making for the organization using an integration of big data analytics into the corresponding decision-making process. Thus, the experiment was carried out in the retail domain to test the framework. As an end result, the results showcased the value-added if big data analytics is integrated with corresponding decision-making activity

Genic non-coding microsatellites in the rice genome: characterization, marker design and use in assessing genetic and evolutionary relationships among domesticated groups

<p>Abstract</p> <p>Background</p> <p>Completely sequenced plant genomes provide scope for designing a large number of microsatellite markers, which are useful in various aspects of crop breeding and genetic analysis. With the objective of developing genic but non-coding microsatellite (GNMS) markers for the rice (<it>Oryza sativa </it>L.) genome, we characterized the frequency and relative distribution of microsatellite repeat-motifs in 18,935 predicted protein coding genes including 14,308 putative promoter sequences.</p> <p>Results</p> <p>We identified 19,555 perfect GNMS repeats with densities ranging from 306.7/Mb in chromosome 1 to 450/Mb in chromosome 12 with an average of 357.5 GNMS per Mb. The average microsatellite density was maximum in the 5' untranslated regions (UTRs) followed by those in introns, promoters, 3'UTRs and minimum in the coding sequences (CDS). Primers were designed for 17,966 (92%) GNMS repeats, including 4,288 (94%) hypervariable class I types, which were bin-mapped on the rice genome. The GNMS markers were most polymorphic in the intronic region (73.3%) followed by markers in the promoter region (53.3%) and least in the CDS (26.6%). The robust polymerase chain reaction (PCR) amplification efficiency and high polymorphic potential of GNMS markers over genic coding and random genomic microsatellite markers suggest their immediate use in efficient genotyping applications in rice. A set of these markers could assess genetic diversity and establish phylogenetic relationships among domesticated rice cultivar groups. We also demonstrated the usefulness of orthologous and paralogous conserved non-coding microsatellite (CNMS) markers, identified in the putative rice promoter sequences, for comparative physical mapping and understanding of evolutionary and gene regulatory complexities among rice and other members of the grass family. The divergence between long-grained aromatics and subspecies <it>japonica </it>was estimated to be more recent (0.004 Mya) compared to short-grained aromatics from <it>japonica </it>(0.006 Mya) and long-grained aromatics from subspecies <it>indica </it>(0.014 Mya).</p> <p>Conclusion</p> <p>Our analyses showed that GNMS markers with their high polymorphic potential would be preferred candidate functional markers in various marker-based applications in rice genetics, genomics and breeding. The CNMS markers provided encouraging implications for their use in comparative genome mapping and understanding of evolutionary complexities in rice and other members of grass family.</p

Information Diffusion and Summarization in Social Networks

Social networks are web-based services that allow users to connect and share information. Due to the huge size of social network graph and the plethora of generated content, it is difficult to diffuse and summarize the social media content. This thesis thus addresses the problems of information diffusion and information summarization in social networks. Information diffusion is a process by which information about new opinions, behaviors, conventions, practices, and technologies flow from person-to-person through a social network. Studies on information diffusion primarily focus on how information diffuses in networks and how to enhance information diffusion. Our aim is to enhance the information diffusion in social networks. Many factors affect information diffusion, such as network connectivity, location, posting timestamp, post content, etc. In this thesis, we analyze the effect of three of the most important factors of information diffusion, namely network connectivity, posting time and post content. We first study the network factor to enhance the information diffusion, and later analyze how time and content factors can diffuse the information to a large number of users. Network connectivity of a user determines his ability to disseminate information. A well-connected authoritative user can disseminate information to a more wider audience compared to an ordinary user. We present a novel algorithm to find topicsensitive authorities in social networks. We use the topic-specific authoritative position of the users to promote a given topic through word-of-mouth (WoM) marketing. Next, the lifetime of social media content is very short, which is typically a few hours. If post content is posted at the time when the targeted audience are not online or are not interested in interacting with the content, the content will not receive high audience reaction. We look at the problem of finding the best posting time(s) to get high information diffusion. Further, the type of social media content determines the amount of audience interaction, it gets in social media. Users react differently to different types of content. If a post is related to a topic that is more arousing or debatable, then it tends to get more comments. We propose a novel method to identify whether a post has high arousal content or not. Furthermore, the sentiment of post content is also an important factor to garner users’ attention in social media. Same information conveyed with different sentiments receives a different amount of audience reactions. We understand to what extent the sentiment policies employed in social media have been successful to catch users’ attention. Finally, we study the problem of information summarization in social networks. Social media services generate a huge volume of data every day, which is difficult to search or comprehend. Information summarization is a process of creating a concise readable summary of this huge volume of unstructured information. We present a novel method to summarize unstructured social media text by generating topics similar to manually created topics. We also show a comprehensive topical summary by grouping semantically related topics

Fabrication of prototype connecting rod of PLA plastic material using FDM prototype technology

Rapid prototyping (RP) have been attracting attention in the manufacturing community because of their capability to reduce the lead time of product development. Present work is an effort to understand the influence of process variables like infill pattern, layer thickness, build orientation and infill density on dimensional accuracy (DA), flatness and cylindricity. Taguchi method orthogonal array L9 was used for the conduction of experiments. MakerBot Replicator-2 was used for the fabrication of scaled prototype connecting rod of polylactic acid (PLA) material. DA, flatness and cylindricity of the component were measured by using coordinate measuring machine (CMM). Analysis of variance (ANOVA) was employed to find out the significance of process parameters. A regression model was developed to predict the DA, flatness and cylindricity. The results reveal that the optimum process parameters for the DA, flatness and cylindricity were different. Utility Theory was used to find out the best process parameter condition. The best process parameters for the DA, flatness and cylindricity was found to be layer thickness 100 μm, linear infill pattern, inclined at 45ºorientation and 20% infill density. A confirmation test was conducted for checking the goodness of the model, which reveals that results were within the confidence limit

Fabrication of prototype connecting rod of PLA plastic material using FDM prototype technology

333-343Rapid prototyping (RP) have been attracting attention in the manufacturing community because of their capability to reduce the lead time of product development. Present work is an effort to understand the influence of process variables like infill pattern, layer thickness, build orientation and infill density on dimensional accuracy (DA), flatness and cylindricity. Taguchi method orthogonal array L9 was used for the conduction of experiments. MakerBot Replicator-2 was used for the fabrication of scaled prototype connecting rod of polylactic acid (PLA) material. DA, flatness and cylindricity of the component were measured by using coordinate measuring machine (CMM). Analysis of variance (ANOVA) was employed to find out the significance of process parameters. A regression model was developed to predict the DA, flatness and cylindricity. The results reveal that the optimum process parameters for the DA, flatness and cylindricity were different. Utility Theory was used to find out the best process parameter condition. The best process parameters for the DA, flatness and cylindricity was found to be layer thickness 100 µm, linear infill pattern, inclined at 45º orientation and 20% infill density. A confirmation test was conducted for checking the goodness of the model, which reveals that results were within the confidence limit