Meteor radar measurements of MLT winds near the equatorial electro jet region over Thumba (8.5° N, 77° E): comparison with TIDI observations

The All-Sky interferometric meteor (SKYiMET) radar (MR) derived winds in the vicinity of the equatorial electrojet (EEJ) are discussed. As Thumba (8.5° N, 77° E; dip lat. 0.5° N) is under the EEJ belt, there has been some debate on the reliability of the meteor radar derived winds near the EEJ height region. In this regard, the composite diurnal variations of zonal wind profiles in the mesosphere-lower thermosphere (MLT) region derived from TIMED Doppler Interferometer (TIDI) and ground based meteor radar at Thumba are compared. In this study, emphasis is given to verify the meteor radar observations at 98 km height region, especially during the EEJ peaking time (11:00 to 14:00 LT). The composite diurnal cycles of zonal winds over Thumba are constructed during four seasons of the year 2006 using TIDI and meteor radar observations, which showed good agreement especially during the peak EEJ hours, thus assuring the reliability of meteor radar measurements of neutral winds close to the EEJ height region. It is evident from the present study that on seasonal scales, the radar measurements are not biased by the EEJ. The day-time variations of HF radar measured E-region drifts at the EEJ region are also compared with MR measurements to show there are large differences between ionospheric drifts and MR measurements. The significance of the present study lies in validating the meteor radar technique over Thumba located at magnetic equator by comparing with other than the radio technique for the first time

Beneficial Image Preprocessing by Contrast Enhancement Techniquefor SEM Images

In this paper a morphological filtering algorithm using an exposure thresholding and measures of central tendency hasbeen proposed for solving the low contrast of Scanning Electron Microscopic (SEM) images of composite materials foraccurate Filler Content Estimation. SEM image of a composite material comprises visible morphological structures likefillers such as silica nanoparticles. The SEM image analysis via segmentation will assist in the study of distribution of thesestructures. The estimation of the filler content is more accurate only when the SEM images have proper contrast for analysisif not the results lead to less accuracy. To overcome this drawback, we have proposed a preprocessing technique to increasethe contrast of SEM images. So that the preprocessed image can be used for post processing namely segmentation and hencethe error is less for filler content estimation. We introduced the transformations using morphological processing to extractthe bright and darker features of the images. The optimum threshold value is determined by the image exposure. A detailedcomparative analysis with other existing techniques has been performed to prove the superior performance of the proposedmethod

Granite classification using machine learning and edge computing [version 1; peer review: 1 approved, 2 approved with reservations]

Background: The outlook and the aura of any place are highly dependent on how a place is decorated and what materials are used in designing it. Granite is such a kind of rock which is vastly used for this purpose. Granite flooring and counters have a major influence on the interior d ́ecor which is essential to set the mood and ambience of a house. A system is needed to help the end users differentiate between granites, which enhance the grandeur of their house and also check the frauds of different color granite being sent by the merchant as compared to what was selected by the end user. Several models have been developed for this cause using CNN and other image processing techniques. However, a solution for this purpose must be precise and computationally efficient. Methods: For this purpose,researchers in this work developed a machine learning based granite classifier using Edge Computing and a website to help users in choosing which granite would go well with their d ́ecor is also built. The developed system consists of a color sensor [TCS3200] integrated with an ESP8266 board. The data pertaining to RGB contrasts of different rocks is acquired by using the color sensor from a dealership.This data is used to train a Machine Learning algorithm to classify the rock into different granite types from a granite dealer and yield the category prediction. Results: The proposed system yields a result of 94% accuracy when classified using Random Forest Algorithm. Conclusion: Thus, this system provides an upper hand for the end users in differentiating between different types of granites

Global gene expression analysis of human erythroid progenitors

This article is available open access through the publisher’s website. Copyright @ 2011 American Society of Hematology. This article has an erratum: http://bloodjournal.hematologylibrary.org/content/118/26/6993.3.Understanding the pattern of gene expression during erythropoiesis is crucial for a synthesis of erythroid developmental biology. Here, we isolated 4 distinct populations at successive erythropoietin-dependent stages of erythropoiesis, including the terminal, pyknotic stage. The transcriptome was determined using Affymetrix arrays. First, we demonstrated the importance of using defined cell populations to identify lineage and temporally specific patterns of gene expression. Cells sorted by surface expression profile not only express significantly fewer genes than unsorted cells but also demonstrate significantly greater differences in the expression levels of particular genes between stages than unsorted cells. Second, using standard software, we identified more than 1000 transcripts not previously observed to be differentially expressed during erythroid maturation, 13 of which are highly significantly terminally regulated, including RFXAP and SMARCA4. Third, using matched filtering, we identified 12 transcripts not previously reported to be continuously up-regulated in maturing human primary erythroblasts. Finally, using transcription factor binding site analysis, we identified potential transcription factors that may regulate gene expression during terminal erythropoiesis. Our stringent lists of differentially regulated and continuously expressed transcripts containing many genes with undiscovered functions in erythroblasts are a resource for future functional studies of erythropoiesis. Our Human Erythroid Maturation database is available at https://cellline.molbiol.ox.ac.uk/eryth/index.html.National Health Service Blood and Transplant, National Institute for Health Research Biomedical Research Center Program, and National Institute for Health Research

Cross-platform expression profiling demonstrates that SV40 small tumor antigen activates Notch, Hedgehog, and Wnt signaling in human cells

BACKGROUND: We previously analyzed human embryonic kidney (HEK) cell lines for the effects that simian virus 40 (SV40) small tumor antigen (ST) has on gene expression using Affymetrix U133 GeneChips. To cross-validate and extend our initial findings, we sought to compare the expression profiles of these cell lines using an alternative microarray platform. METHODS: We have analyzed matched cell lines with and without expression of SV40 ST using an Applied Biosystems (AB) microarray platform that uses single 60-mer oligonucleotides and single-color quantitative chemiluminescence for detection. RESULTS: While we were able to previously identify only 456 genes affected by ST with the Affymetrix platform, we identified 1927 individual genes with the AB platform. Additional technical replicates increased the number of identified genes to 3478 genes and confirmed the changes in 278 (61%) of our original set of 456 genes. Among the 3200 genes newly identified as affected by SV40 ST, we confirmed 20 by QRTPCR including several components of the Wnt, Notch, and Hedgehog signaling pathways, consistent with SV40 ST activation of these developmental pathways. While inhibitors of Notch activation had no effect on cell survival, cyclopamine had a potent killing effect on cells expressing SV40 ST. CONCLUSIONS: These data show that SV40 ST expression alters cell survival pathways to sensitize cells to the killing effect of Hedgehog pathway inhibitors

Analysis of promoter regions of co-expressed genes identified by microarray analysis

BACKGROUND: The use of global gene expression profiling to identify sets of genes with similar expression patterns is rapidly becoming a widespread approach for understanding biological processes. A logical and systematic approach to study co-expressed genes is to analyze their promoter sequences to identify transcription factors that may be involved in establishing specific profiles and that may be experimentally investigated. RESULTS: We introduce promoter clustering i.e. grouping of promoters with respect to their high scoring motif content, and show that this approach greatly enhances the identification of common and significant transcription factor binding sites (TFBS) in co-expressed genes. We apply this method to two different dataset, one consisting of micro array data from 108 leukemias (AMLs) and a second from a time series experiment, and show that biologically relevant promoter patterns may be obtained using phylogenetic foot-printing methodology. In addition, we also found that 15% of the analyzed promoter regions contained transcription factors start sites for additional genes transcribed in the opposite direction. CONCLUSION: Promoter clustering based on global promoter features greatly improve the identification of shared TFBS in co-expressed genes. We believe that the outlined approach may be a useful first step to identify transcription factors that contribute to specific features of gene expression profiles

Lessons learned in developing reference data sets with the contribution of citizens: the Geo-Wiki experience

The development of remotely sensed products such as land cover requires large amounts of high-quality reference data, needed to train remote sensing classification algorithms and for validation. However, due to the lack of sharing and the high costs associated with data collection, particularly ground-based information, the amount of reference data available has not kept up with the vast increase in the availability of satellite imagery, e.g. from Landsat, Sentinel and Planet satellites. To fill this gap, the Geo-Wiki platform for the crowdsourcing of reference data was developed, involving visual interpretation of satellite and aerial imagery. Here we provide an overview of the crowdsourcing campaigns that have been run using Geo-Wiki over the last decade, including the amount of data collected, the research questions driving the campaigns and the outputs produced such as new data layers (e.g. a global map of forest management), new global estimates of areas or percentages of land cover/land use (e.g. the amount of extra land available for biofuels) and reference data sets, all openly shared. We demonstrate that the amount of data collected and the scientific advances in the field of land cover and land use would not have been possible without the participation of citizens. A relatively conservative estimate reveals that citizens have contributed more than 5.3 years of the data collection efforts of one person over short, intensive campaigns run over the last decade. We also provide key observations and lessons learned from these campaigns including the need for quality assurance mechanisms linked to incentives to participate, good communication, training and feedback, and appreciating the ingenuity of the participants