Green preparation of bract extract (Musa acuminate) doped magnesium oxide nanoparticles and their bioefficacy

Magnesium oxide nanoparticles (MgONPs) synthesized by efficient green approach have unique physiochemical properties. In this study, MgONPs are synthesized with bract extract of Musa acuminate , an agro waste. The surface plasmon resonance at 450 nm in UV spectrum and FTIR peaks at 601 and 890 cm −1 confirmed the presence of MgONPs. XRD pattern revealed high crystallinity of the nanoparticles with an intense orientation peak at 111, and the size was 13 nm. The particles were spherical with an average size of 24.85 nm. The elemental percentage of magnesium and oxygen were 68.55% and 31.45%. MgONPs had antibacterial activity against Bacillus subtilis , Escherichia coli , Vibrio harveyi , Vibrio parahemolyticus , and Staphylococcus aureus with MIC, 6 μg/mL. The IC 50 value for MCF‐7 cell was 113.56 μg/mL, and the normal cell line was 785.69 μg/mL. The NPs also exhibited hemolytic features in a dose‐dependent manner. The MgONPs exhibited photocatalytic degradation of methyl violet, CBB G‐250, and malachite green in 60 min duration. MgONPs had promising antibacterial, cytotoxic, hemolytic, photocatalytic, and seed germination activity. They have the potential to serve as an additive in a variety of biological applications.Universidade de Vigo/CISU

Development of GCP Ontology for Sharing Crop Information

The Generation Challenge Programme (GCP – "http://www.generationcp.org":http://www.generationcp.org) is a globally distributed crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. GCP adopted the development paradigm of a ‘model-driven architecture’ to achieve the interoperability and integration of diverse GCP data types that are available through distributed data sources and consumed by end-user data analysis tools. Its objective is to ensure semantic compatibility across the Consortium that will lead to the creation of robust global public goods from GCP research results. 

The GCP scientific domain model is an object model that encapsulates key crop science concepts and is documented using Unified Modeling Language (see GCP Models on "http://pantheon.generationcp.org/index.php":http://pantheon.generationcp.org/index.php). 

At the core of the GCP architecture is a scientific domain model, which is heavily parameterized with GCP-indexed ontology terms. The GCP-indexed ontology reuses established international standards where available, converts other publicly available controlled vocabularies into formally managed ontology, and develops novel ontology if no public vocabularies yet exist. General and crop-specific GCP ontologies are being developed by crop teams involving GCP and external scientific experts – in particular, for crop-specific ontology relating to plant anatomy, developmental stage, trait and phenotype for selected GCP crops. Crop ontologies are being developed for chickpea, maize, Musa, potato, rice, sorghum and wheat. The Bioversity crop descriptor lists already loaded into OBO format files provide the primary structure to develop the crop ontologies. Then, terms to be mapped to the ontologies are extracted from the crop databases where trait values have been stored by crop scientists. These sources allow the ontology teams to identify the most commonly used concept names and their interrelations. Experts validate the selection of keywords that will build the controlled vocabulary. 

These GCP ontologies will allow researchers and end users to query keywords related to traits, plant structure, growth stage, and molecular function, and link them to associated phenotyping and genotyping data sets including data on germplasm, crop physiology, geographic information, genes, QTL, etc. To reach that stage, the crop ontologies will be integrated into the data-entry user interface or data templates as picklists facilitating data annotation and submission of new terms. In addition, the GCP ontologies will be integrated with Plant Ontology (PO) and Gramene (Trait Ontology, TO; Environment Ontology, EO) to develop a common, internationally shared crop trait and anatomy ontology. The team will initiate collaboration with SONet (Scientific Observations Network) and OBOE (Extensible Observation Ontology), which proposed to integrate the GCP ontology as a study case.
The Open Biomedical Ontologies (OBO) edit tool has been used to develop the ontologies for rice, wheat and maize traits, which are currently available at "http://cropforge.org/projects/gcpontology/":http://cropforge.org/projects/gcpontology/ . The crop-specific work plans and ontologies related to other materials are published at "http://pantheon.generationcp.org":http://pantheon.generationcp.org. 
The development and curation of general-purpose ontologies will be continued and made available on the Pantheon and CropForge websites

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making

The Generation Challenge Programme Platform: Semantic Standards and Workbench for Crop Science

The Generation Challenge programme (GCP) is a global crop research consortium directed toward crop improvement through the application of comparative biology and genetic resources characterization to plant breeding. A key consortium research activity is the development of a GCP crop bioinformatics platform to support GCP research. This platform includes the following: (i) shared, public platform-independent domain models, ontology, and data formats to enable interoperability of data and analysis flows within the platform; (ii) web service and registry technologies to identify, share, and integrate information across diverse, globally dispersed data sources, as well as to access high-performance computational (HPC) facilities for computationally intensive, high-throughput analyses of project data; (iii) platform-specific middleware reference implementations of the domain model integrating a suite of public (largely open-access/-source) databases and software tools into a workbench to facilitate biodiversity analysis, comparative analysis of crop genomic data, and plant breeding decision making.This is the publisher’s final pdf. The published article is copyrighted by the author(s) and published by Hindawi Publishing Corporation. The published article can be found at: http://www.hindawi.com/journals/ijpg/

Fish Science Research in China: How does it Compare with Fish Research in India?

Fish and aquaculture research in the Peopleâ s Republic of China over the six years 1994-1999 has been mapped using data from six databases â three abstracting services and three citation indexes. The results are compared with fish science research in India. During the six years China has published 2035 papers (roughly 4.5 â 5% of the world output) and India 2454. More than 95% of Chinaâ s papers are journal articles, compared to 82.8% of Indian papers. About 78% of Chinaâ s journal paper output has appeared in 143 domestic journals compared to 70% from India in 113 Indian journals. Less than one-eighth of the journal articles published by Chinese researchers are published in journals indexed in SCI, compared to 30% of journal articles by Indian researchers. Less than a dozen papers from each of these countries have appeared in journals of impact factor greater than 3.0. Fish research institutes and fishery colleges are the major contributors of the Chinese research output in this area. In India academic institutions are the leading contributors (61%), followed by central government institutions (>25%). Qingdao, Wuhan, Beijing and Shanghai are the cities and Shandong, Hubei and Fujian are the provinces contributing a large number of papers. As we do not have addresses of all authors in most of the papers, we are unable to estimate the extent of international collaboration. Although Chinaâ s research output and its citation impact are less than those of India, Chinaâ s fish production and export earnings are far higher than those of India. Probably China is better at bridging the gap between knowhow (research) and do-how (technology and creation of employment and wealth). China is pretty strong in extension

ISSN: 2454-132X Impact factor: 4.295 Maximum Solar Power Tracker Mechanically By Using Dual Axis Tracker

Abstract: To formulate a method for harvesting the maximum solar irradiance and thereby increase the output of the system. To reduce the energy expenditure by solar tracking system and conserve energy without any extra hardware components. The solar power is tracked mechanically in both the axis by using dual axis tracker efficiently to obtain maximum irradiance available from the sun

Anemia among hospitalized children at a multispecialty hospital, Bangalore (Karnataka), India

Background: Due to the limited availability of data related to anemia in hospitalized children, this research was conducted to study the occurrence, morphological patterns, distribution in different age groups, sex, and severity of anemia among children aged 6 months-12 years. Setting: Inpatients in department of pediatrics at a multispecialty hospital, Bangalore. Study Design: Descriptive cross sectional study from Oct, 2011 to Sep, 2012. Materials and Methods: Ethical clearance was obtained from the ethical committee of the hospital as per 1964 Declaration of Helsinki. Unrestricted random sampling method was used to select the study group consisting of 882 children between the age of 6 months and 12 years. After obtaining the consent, data were obtained and statistically analyzed using statistical tools like mean, median, standard deviation, and Chi-square test. Results: Out of 882 children selected, 642 (72.79%) were anemic, out of which a majority of 629 (98%) children suffered from nonhemoglobinopathies and a meagre 13 (2%) suffered from hemoglobinopathies. Children in the age group of 6 months-1 year were most affected with nonhemoglobinopathies (33%). Moderate degree of anemia (hemoglobin = 7-9.9 g/dL) was the commonest grade of anemia (80%), while microcytic hypochromic anemia was commonest morphological type of anemia (48%). Among hemoglobinopathies, thalassemia major was the most common (69%, that is 9 out of 13 patients). Conclusion: The occurrence of anemia among children aged between 6 months and 12 years is high and nonhemoglobinopathies predominate over the hemoglobinopathies