Uterine Lipoleiomyoma: a rare variant of benign uterine neoplasm

The lipomatous tumors are very rare benign neoplasms of the uterus. Lipoleiomyoma is a benign tumor which is variant of leiomyoma. It has similar clinical course and presentation like uterine leiomyoma and is typically found in postmenopausal women. Authors report a case of 45 years female presented with a complaint of increased frequency of menstrual cycles and generalized weakness since 5- 6 months. On ultrasonography abdomen - pelvis a single large lobulated hyperechoic mass was noted in the fundal myometrium measuring 5 x 4.6 cm. The finding was suggestive of fibroid uterus. On histopathological examination showed variable proportions of lobules of mature adipocytes and interlacing bundles of benign smooth muscle cells which was diagnostic of lipoleiomyoma. Authors are presenting this case for its rarity, clinical presentation, imaging and histopathological finding with differential diagnosis

Determinants of Recurrent Diarrhoea among Children

BackgroundAbout 2 million episodes of diarrhoea occur each year in India. Of the 6.6 million deaths among children aged 28 days to 5 year; deaths from diarrhoea are estimated to account for 1.87 million. An average Indian child less than 5 years of age can have 2-3 episodes of diarrhoea.  Mother's literacy, family income, feeding practices, environmental conditions are important determinants of the common childhood infection like diarrhoea. The present study was undertaken to study these important determinants of recurrent diarrhoea among children under five in a rural area of western Maharashtra, India.Method  A cross-sectional study was conducted in six randomly selected villages of Ahmednagar district in western Maharashtra, India. Three villages from two primary health centres and 652 children under five from these villages were chosen by a simple random sampling technique (every fifth child enrolled in Anganwadi). House-to-house survey was done and data was collected by interviewing the mothers of these children. Nutritional status was assessed by measuring the weight and mid-arm circumference of the child. Statistical analysis was done with Microsoft Excel and StatistiXL 1.8 using percentage, proportions and chi-square test wherever applicable.ResultsThe prevalence of recurrent diarrhoea was 9.81%. Recurrent diarrhoea was more common in the age group of 13 - 24 months (29.6%) and 25 – 36 months (23.4%) and children belonging to lower socioeconomic class (64%). Malnutrition was significantly associated with recurrent diarrhoea and 21% of malnourished children had the same. Recurrent diarrhoea was significantly more common (39.1%) among children with introduction of top-up feeds before four to six months.ConclusionLow socioeconomic status, bad sanitary practices, nutritional status and weaning practices significantly influence the prevalence of recurrent diarrhoea

Secure Mobile Based E-Voting System

The E-Voting means the voting process in election by using electronic device. In this proposed system described how the android mobile phones are efficient and can be used for voting. The android platform is used to develop an application. Our system support simultaneous voting due to the distributed nature of the database. During election electronic device is used for voting process. A voter may only need to register only once for a particular election and that does all, voter need to cast his /her vote without actually have to present at the voting cell. The registration process must be done at Booth application for once then voter is been given a facility to vote from his/her Android mobile phone irrespective of his/her location. This proposed system suppose to propose a new e-voting system, which ensures voter confidentiality and voting accuracy, thus providing an important framework that based on unique identification ADHAAR ID (U-ID) number. An online solution is very useful as the information about the voters and the election committee is also made available to the people in this system

Dynamic Query Forms for Non-Relational Database

With quick advancement of investigative databases and web data databases are turning out to be exceptionally colossal in size and complex in nature. These databases hold extensive and heterogeneous information, with huge number of relations and qualities. So it is exceptionally hard to outline an arrangement of static inquiry structures to answer different specially appointed database inquirieson these cutting edge databases. Along these lines there is need of such framework which create Query Forms powerfully as indicated by the clients need at run time. The proposed framework Dynamic Query Form i.e.DQF framework going to give an answer by the inquiry interface in extensive and complex databases. In proposed framework, the center idea is to catch client intrigues all through client associations and to adjust the inquiry sort iteratively. Each cycle comprises of 2 sorts of client collaborations: Query Form Enrichment and Query Execution. In Query Form Enrichment DQF would prescribe a positioned rundown of question structure part to client so he/she can choose sought structure segments into current inquiry structure. In Query Execution client fills current inquiry shape and submit question, DQF going to show result and take input from client on gave question results. A client would have office to fill the inquiry frame and submit questions to see the inquiry result at every cycle. So that a question structure could be progressively refined till the client fulfills with the inquiry results

Characterization of PvuRts1I endonuclease as a tool to investigate genomic 5–hydroxymethylcytosine

In mammalian genomes a sixth base, 5-hydroxymethylcytosine (hmC), is generated by enzymatic oxidation of 5-methylcytosine (mC). This discovery has raised fundamental questions about the functional relevance of hmC in mammalian genomes. Due to their very similar chemical structure, discrimination of the rare hmC against the far more abundant mC is technically challenging and to date no methods for direct sequencing of hmC have been reported. Here, we report on a purified recombinant endonuclease, PvuRts1I, which selectively cleaves hmC-containing sequences. We determined the consensus cleavage site of PvuRts1I as hmCN11–12/N9–10G and show first data on its potential to interrogate hmC patterns in mammalian genomes

Mapping cropland extent and areas of Australia at 30-m resolution using multi-year time-series Landsat data and Random Forest machine learning algorithm through Google Earth Engine (GEE) Cloud Computing

Mapping accurate, precise, and consistent cropland products is crucial for global food security analysis. Mapping croplands, including fallow areas, is an important measure to determine the quantity of food that is produced, where it is produced, and when it is produced (which season). Satellite based earth observation provides the best opportunity for globally consistent, spatially explicit, cost effective, objective, and efficient way to map croplands at various spatial resolutions. However, mapping cropland extent at finer (e.g., 30-m or finer) spatial resolution over very large areas such as continental, and global extent is challenging. This study developed a precise Landsat 30-m cropland extent map and calculated cropland areas of the Australian continent for the nominal year 2015 using a random forest (RF) machine learning algorithm (MLA) through Google Earth Engine (GEE) cloud computing platform. The process involved the use of 8 bands (blue, green, red, NIR, SWIR1, temp, NDVI and NDWI) of Landsat-8 every 16-day data for the years 2014 and 2015. Each band was a composited over 2-4 time-period using mean value compositing. Overall, there was a 48-layer data-cube on which we generated knowledge of croplands versus non-croplands, coded the knowledge into RF MLA and run on the GEE cloud to obtain cropland extent for all of Australia. An external independent evaluation team conducted an accuracy assessment using an independent validation data set collected from field survey and sub-meter to 5-m very high spatial resolution imagery. Results showed an overall accuracy of 97.56% with high producer’s accuracy of 98.7% and user’s accuracy of 89.0% for the cropland class. The study also determined how the cropland areas change with spatial resolution of imagery at 30-m, 250-m, and 1-km. We established that cropland location precision and map accuracies were significantly higher for 30-m. We also established that areas determined using 30-m were much more precise and reliable

NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security Support Analysis Data (GFSAD) Crop Mask 2010 Global 1 km V001

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security Support Analysis Data (GFSAD) Crop Mask Global 1 kilometer (km) dataset was created using multiple input data including: remote sensing such as Landsat, Advanced Very High Resolution Radiometer (AVHRR), Satellite Probatoire d'Observation de la Terre (SPOT) vegetation and Moderate Resolution Imaging Spectrometer (MODIS); secondary elevation data; climate 50-year precipitation and 20-year temperature data; reference sub-meter to 5-meter resolution ground data and country statistics data. The GFSAD1KCM provides spatial distribution of a disaggregated five class global cropland extent map derived for nominal 2010 at 1-km based on four major studies: Thenkabail et al. (2009a, 2011), Pittman et al. (2010), Yu et al. (2013), and Friedl et al. (2010). The GFSAD1KCM nominal 2010 product is based on data ranging from years 2007 through 2012

NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) Cropland Extent 2015 Australia, New Zealand, China, Mongolia 30 m V001

The NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) Global Food Security-support Analysis Data (GFSAD) data product provides cropland extent data over Australia, New Zealand, China, and Mongolia for nominal year 2015 at 30 meter resolution (GFSAD30AUNZCNMOCE). The monitoring of global cropland extent is critical for policymaking and provides important baseline data that are used in many agricultural cropland studies pertaining to water sustainability and food security. The GFSAD30AUNZCNMOCE data product uses the pixel-based supervised classifier Random Forest (RF) to retrieve cropland extent from a combination of Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. Each GFSAD30AUNZCNMOCE GeoTIFF file contains a cropland extent layer that defines areas of cropland, non-cropland, and water bodies over a 10⁰ by 10⁰ area

Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities

The precise estimation of the global agricultural cropland- extents, areas, geographic locations, crop types, cropping intensities, and their watering methods (irrigated or rainfed; type of irrigation) provides a critical scientific basis for the development of water and food security policies (Thenkabail et al., 2012, 2011, 2010). By year 2100, the global human population is expected to grow to 10.4 billion under median fertility variants or higher under constant or higher fertility variants (Table 1) with over three quarters living in developing countries, in regions that already lack the capacity to produce enough food. With current agricultural practices, the increased demand for food and nutrition would require in about 2 billion hectares of additional cropland, about twice the equivalent to the land area of the United States, and lead to significant increases in greenhouse gas productions (Tillman et al., 2011). For example, during 1960-2010 world population more than doubled from 3 billion to 7 billion. The nutritional demand of the population also grew swiftly during this period from an average of about 2000 calories per day per person in 1960 to nearly 3000 calories per day per person in 2010..

The Genome of the Stick Insect Medauroidea extradentata Is Strongly Methylated within Genes and Repetitive DNA

BACKGROUND: Cytosine DNA methylation has been detected in many eukaryotic organisms and has been shown to play an important role in development and disease of vertebrates including humans. Molecularly, DNA methylation appears to be involved in the suppression of initiation or of elongation of transcription. Resulting organismal functions are suggested to be the regulation of gene silencing, the suppression of transposon activity and the suppression of initiation of transcription within genes. However, some data concerning the distribution of methylcytosine in insect species appear to contradict such roles. PRINCIPAL FINDINGS: By comparison of MspI and HpaII restriction patterns in genomic DNA of several insects we show that stick insects (Phasmatodea) have highly methylated genomes. We isolated methylated DNA fragments from the Vietnamese Walking Stick Medauroidea extradentata (formerly known as Baculum extradentatum) and demonstrated that most of the corresponding sequences are repetitive. Bisulfite sequencing of one of these fragments and of parts of conserved protein-coding genes revealed a methylcytosine content of 12.6%, mostly found at CpG, but also at CpT and CpA dinucleotides. Corresponding depletions of CpG and enrichments of TpG and CpA dinucleotides in some highly conserved protein-coding genes of Medauroidea reach a similar degree as in vertebrates and show that CpG methylation has occurred in the germline of these insects. CONCLUSIONS: Using four different methods, we demonstrate that the genome of Medauroidea extradentata is strongly methylated. Both repetitive DNA and coding genes appear to contain high levels of methylcytosines. These results argue for similar functions of DNA methylation in stick insects as those already known for vertebrates