TEC Response and Subsequent GPS Error Caused by the Most severe Geomagnetic Storm of Solar Cycle 24 at India

339-348This paper presents the response of low-latitude and mid-latitude ionosphere to a severe geomagnetic storm that occurred on 17 March 2015 at 0445 UT, and the subsequent effect of this storm on GPS error in the East-West (E-W) and North-South (N-S) directions. The Vertical Total Electron Content (VTEC) data has been analysed from three dual frequency GPS receivers, which were installed under the framework of the International GNSS Service (IGS). For each day of the year, the data is downloadable as a single file in the Receiver Independent Exchange Format (RINEX) from the IGS data portal. The VTEC values from the IGS are obtained at one minute intervals. Results show the variations in GPS derived VTEC during the severe geomagnetic storm. Negative ionospheric storms caused by composition changes are observed at mid-latitude region of Lucknow, while positive ionospheric storms caused by magnetospheric convection and Equatorial Ionospheric Anomaly (EIA) are prominent at low-latitude regions of Bangalore and Hyderabad. The maximum depletion in VTEC peak at mid-latitude region of Lucknow when compared to the quiet day mean VTEC was 61 percent during a negative ionospheric storm that occurred on 18 March 2015, and maximum enhancement in VTEC peak at low-latitude region of Bangalore and Hyderabad when compared to the quiet day mean VTEC was 26 percent and 21 percent respectively during an early positive ionospheric storm on 18 March 2015. Positive ionospheric storms caused by enhanced EIA and Prompt Penetration Electric Fields (PPEF) are prominent at low-latitudes. The highest GPS error during storm time was +7.2m and +11.3m in E-W and N-S directions respectively at Lucknow. The average GPS error in E-W and N-S directions during storm time was higher at the mid-latitude station of Lucknow

TEC Response and Subsequent GPS Error Caused by the Most severe Geomagnetic Storm of Solar Cycle 24 at India

This paper presents the response of low-latitude and mid-latitude ionosphere to a severe geomagnetic storm that occurred on 17 March 2015 at 0445 UT, and the subsequent effect of this storm on GPS error in the East-West (E-W) and North-South (N-S) directions. The Vertical Total Electron Content (VTEC) data has been analysed from three dual frequency GPS receivers, which were installed under the framework of the International GNSS Service (IGS). For each day of the year, the data is downloadable as a single file in the Receiver Independent Exchange Format (RINEX) from the IGS data portal. The VTEC values from the IGS are obtained at one minute intervals. Results   show the variations in GPS derived VTEC during the severe geomagnetic storm. Negative ionospheric storms caused by composition changes are observed at mid-latitude region of Lucknow, while positive ionospheric storms caused by magnetospheric convection and Equatorial Ionospheric Anomaly (EIA) are prominent at low-latitude regions of Bangalore and Hyderabad. The maximum depletion in VTEC peak at mid-latitude region of Lucknow when compared to the quiet day mean VTEC was 61 percent during a negative ionospheric storm that occurred on 18 March 2015, and maximum enhancement in VTEC peak at low-latitude region of Bangalore and Hyderabad when compared to the quiet day mean VTEC was 26 percent and 21 percent respectively during an early positive ionospheric storm on 18 March 2015. Positive ionospheric storms caused by enhanced EIA and Prompt Penetration Electric Fields (PPEF) are prominent at low-latitudes. The highest GPS error during storm time was +7.2 m and +11.3 m in E-W and N-S directions respectively at Lucknow. The average GPS error in E-W and N-S directions during storm time was higher at the mid-latitude station of Lucknow

Genome-wide analysis of regions similar to promoters of histone genes

Background: The purpose of this study is to: i) develop a computational model of promoters of human histone-encoding genes (shortly histone genes), an important class of genes that participate in various critical cellular processes, ii) use the model so developed to identify regions across the human genome that have similar structure as promoters of histone genes; such regions could represent potential genomic regulatory regions, e.g. promoters, of genes that may be coregulated with histone genes, and iii/ identify in this way genes that have high likelihood of being coregulated with the histone genes. Results: We successfully developed a histone promoter model using a comprehensive collection of histone genes. Based on leave-one-out cross-validation test, the model produced good prediction accuracy (94.1% sensitivity, 92.6% specificity, and 92.8% positive predictive value). We used this model to predict across the genome a number of genes that shared similar promoter structures with the histone gene promoters. We thus hypothesize that these predicted genes could be coregulated with histone genes. This hypothesis matches well with the available gene expression, gene ontology, and pathways data. Jointly with promoters of the above-mentioned genes, we found a large number of intergenic regions with similar structure as histone promoters. Conclusions: This study represents one of the most comprehensive computational analyses conducted thus far on a genome-wide scale of promoters of human histone genes. Our analysis suggests a number of other human genes that share a high similarity of promoter structure with the histone genes and thus are highly likely to be coregulated, and consequently coexpressed, with the histone genes. We also found that there are a large number of intergenic regions across the genome with their structures similar to promoters of histone genes. These regions may be promoters of yet unidentified genes, or may represent remote control regions that participate in regulation of histone and histone-coregulated gene transcription initiation. While these hypotheses still remain to be verified, we believe that these form a useful resource for researchers to further explore regulation of human histone genes and human genome. It is worthwhile to note that the regulatory regions of the human genome remain largely un-annotated even today and this study is an attempt to supplement our understanding of histone regulatory regions.Statistic

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs

Variations of total electron content in the equatorial anomaly region in Thailand

Advances in Space Research551231-24

Characterization of GPS-TEC in a low-latitude region over Thailand during 2010-2012

This paper presents the first results of vertical total electron content (VTEC) data from (1) a dual-frequency GPS receiver installed at the Chiang Mai University in Chiang Mai (CHGM, 18.480 N, 98.570 E) as part of SCINDA (Scintillation Network and Decision Aid) and (2) the International GNSS Service (IGS) station Pathum Wan (CUSV, 13.735 N, 100.533 E) with magnetic latitude of 8.69°N and 3.92°N respectively in Thailand, from August 2010 to July 2012. In the equatorial ionization anomaly (EIA) region, these two stations are separated at a distance of 668 km. Observed GPS-TEC values were found to be the highest between 1500 and 1900 Local Time (LT) throughout the study period at both the stations. The GPS-TEC data from both the stations was plotted diurnal, monthly and seasonal analyses were performed. The equinox (March, April, September, and October) and solstice (January, February, June, July, and December) periods had maximum and minimum diurnal peak variations, respectively, of the GPS-TEC. High TEC values are attributed to extreme solar ultra-violet ionization coupled with upward vertical E×B drift. A comparison of the GPS-TEC data from both the stations for the study period shows that the CHGM station recorded higher values of TEC than the CUSV station because of the formation of an ionization crest over the CHGM station. The GPS-TEC values also exhibited an increasing trend-because of the approach of solar cycle 24. For data validation, the diurnal, monthly, and seasonal variations in the measured TEC were compared with the TEC modelled in the International Reference Ionosphere (IRI) models (IRI-2007 and the recently released IRI-2012 model). The IRI-2007 shows good agreement with the data from 2010 to 2011 from both stations and IRI-2012 agrees well with the data from 2012 onwards compared to IRI-2007