285 research outputs found
An Inventive Framework of Micro-Electromechanical System (MEMS)
MEMS is an enabling technology allowing the development of smart products, enhancing the computational ability of microelectronics with the perception and control capabilities of micro sensors and micro actuators and expanding the space of possible designs and applications. MEMS is a relatively new technology which exploits the existing microelectronics infrastructure to create complex machines with micron feature sizes. MEMS promises to revolutionize nearly every product category by bringing together silicon based microelectronics with micro machining technology, making possible the realization of compl ete systems on a chip. Microelectromechanical systems (MEMS) technolog enable us to create various useful sensing and actuating devices integrated with other microelectronic, optoelectronic, microwave, thermal and mechanical devices for advanced Microsystem s. Micromachining and micro electro mechanical systems (MEMS) technologies can be used to produce complex structure, devices, and systems on the scale of micrometers. MEMS products based on piezoelectric and capacitance sensing now include pressure and flo w sensors, accelerometers, gyroscopes, microphones, digital light projectors, oscillators, and RF switches. MEMS devices are used in virtually all areas of industrial activity, health care, consumer products, construction, and milita ry and space hardware. The future of MEMS is multifaceted, complex, and subject to change, in response to the prevailing winds of investment by government and commercial entities. This diversification of product offerings and globalization of the industry has been accompanied by strong revenue growth and growing private investment. Much of the growth in MEMS business is expected to come from products that are in early stages of development or yet to be invented
Advancing the STMS genomic resources for defining new locations on the intraspecific genetic linkage map of chickpea (Cicer arietinum L.)
<p>Abstract</p> <p>Background</p> <p>Chickpea (<it>Cicer arietinum </it>L.) is an economically important cool season grain legume crop that is valued for its nutritive seeds having high protein content. However, several biotic and abiotic stresses and the low genetic variability in the chickpea genome have continuously hindered the chickpea molecular breeding programs. STMS (Sequence Tagged Microsatellite Sites) markers which are preferred for the construction of saturated linkage maps in several crop species, have also emerged as the most efficient and reliable source for detecting allelic diversity in chickpea. However, the number of STMS markers reported in chickpea is still limited and moreover exhibit low rates of both inter and intraspecific polymorphism, thereby limiting the positions of the SSR markers especially on the intraspecific linkage maps of chickpea. Hence, this study was undertaken with the aim of developing additional STMS markers and utilizing them for advancing the genetic linkage map of chickpea which would have applications in QTL identification, MAS and for <it>de novo </it>assembly of high throughput whole genome sequence data.</p> <p>Results</p> <p>A microsatellite enriched library of chickpea (enriched for <b>(</b>GT/CA)<sub>n </sub>and (GA/CT)<sub>n </sub>repeats) was constructed from which 387 putative microsatellite containing clones were identified. From these, 254 STMS primers were designed of which 181 were developed as functional markers. An intraspecific mapping population of chickpea, [ICCV-2 (single podded) Ă JG-62 (double podded)] and comprising of 126 RILs, was genotyped for mapping. Of the 522 chickpea STMS markers (including the double-podding trait, screened for parental polymorphism, 226 (43.3%) were polymorphic in the parents and were used to genotype the RILs. At a LOD score of 3.5, eight linkage groups defining the position of 138 markers were obtained that spanned 630.9 cM with an average marker density of 4.57 cM. Further, based on the common loci present between the current map and the previously published chickpea intraspecific map, integration of maps was performed which revealed improvement of marker density and saturation of the region in the vicinity of <it>sfl </it>(double-podding) gene thereby bringing about an advancement of the current map.</p> <p>Conclusion</p> <p>An arsenal of 181 new chickpea STMS markers was reported. The developed intraspecific linkage map defined map positions of 138 markers which included 101 new locations.Map integration with a previously published map was carried out which revealed an advanced map with improved density. This study is a major contribution towards providing advanced genomic resources which will facilitate chickpea geneticists and molecular breeders in developing superior genotypes with improved traits.</p
High density linkage mapping of genomic and transcriptomic SNPs for synteny analysis and anchoring the genome sequence of chickpea
This study presents genome-wide discovery of SNPs through next generation sequencing of the genome of Cicer reticulatum. Mapping of the C. reticulatum sequenced reads onto the draft genome assembly of C. arietinum (desi chickpea) resulted in identification of 842,104 genomic SNPs which were utilized along with an additional 36,446 genic SNPs identified from transcriptome sequences of the aforementioned varieties. Two new chickpea Oligo Pool All (OPAs) each having 3,072 SNPs were designed and utilized for SNP genotyping of 129 Recombinant Inbred Lines (RILs). Using Illumina GoldenGate Technology genotyping data of 5,041 SNPs were generated and combined with the 1,673 marker data from previously published studies, to generate a high resolution linkage map. The map comprised of 6698 markers distributed on eight linkage groups spanning 1083.93âcM with an average inter-marker distance of 0.16âcM. Utility of the present map was demonstrated for improving the anchoring of the earlier reported draft genome sequence of desi chickpea by ~30% and that of kabuli chickpea by 18%. The genetic map reported in this study represents the most dense linkage map of chickpea , with the potential to facilitate efficient anchoring of the draft genome sequences of desi as well as kabuli chickpea varieties
Disposition of youth in predicting sustainable development goals using the Neuro - fuzzy and random forest algorithms
This paper evaluates the inclination of Asian youth regarding the achievement of Sustainable Development
Goals (SDGs). As the young population of a country holds the key to its future development, the authors of this study aim to provide evidence of the successful application of machine learning techniques to highlight
their opinions about a sustainable future. This studyâs timing is critical due to rapid developments in technology which are highlighting gaps between policy and the actual aspirations of citizens. Several studies
indicate the superior predictive capabilities of neuro-fuzzy techniques. At the same time, Random Forest is
gaining popularity as an advanced prediction and classification tool. This study aims to build on the previous research and compare the predictive accuracy of the adaptive neuro-fuzzy inference system (ANFIS) and
Random Forest models for three categories of SGDs. The study also aims to explore possible differences of
opinion regarding the importance of these categories among Asian and Serbian youth. The data used in this study were collected from 425 youth respondents in India. The results of data analysis show that ANFIS is better at predicting SDGs than the Random Forest model. The SDG preference among Asian and Serbian youth was found to be highest for the environmental pillar, followed by the social and economic pillars. This paper makes both a theoretical and a practical contribution to deepening understanding of the predictive power of the two models and to devising policies for attaining the SDGs by 2030
On intermediate-term prediction of strong earthquakes in the himalayan arc region using pattern recognition algorithm M8
Seismicity of the Himalayan arc lying within the limits shown in figure 1 and covering the period 1964 to 1987 was scanned using M8 algorithm with a view to identifying the times of increased probabilities (TIPs) of the occurrence of earthquakes of magnitude greater than or equal to 7.0, during the period 1970 to 1987. In this period, TIPs occupy 18% of the space time considered. One of these precedes the only earthquake in this magnitude range which occurred during the period. Two numerical parameters used in the algorithm, namely the magnitude thresholds, had to be altered for the present study owing to incomplete data. Further monitoring of TIPs is however warranted, both for testing the predictive capability of this algorithm in the Himalayan region and for creating a base for the search of short-term precursors
The role of Pax2 in mouse prostate development
BACKGROUND Lossâofâfunction of Pax2 results in severe defects of the male reproductive system, and Pax2 expression is detected in mouse prostate lobes and human prostatic cancers. However, the role for Pax2 in prostate development remains poorly understood. METHODS The expression of Pax2 was examined by in situ hybridization at various developmental stages. Urogenital sinuses were dissected out at E18.5 from mouse Pax2 mutants and controls, cultured in vitro or grafted under the renal capsule of CD1 nude mice. The expression of prostate developmental regulatory factors was analyzed by semiâquantitative realâtime PCR or immuohistochemistry. RESULTS Pax2 is expressed in the epithelial cells of prostate buds. Lossâofâfunction of Pax2 does not affect the initiation of prostatic buds, but in vitro culture assays show that the prostates of Pax2 mutants are hypomorphic and branching is severely disrupted compared to controls. RTâPCR data from Pax2 mutant prostates demonstrate increased expression levels of dorsolateral prostate marker MSMB and ventral prostate marker SBP and dramatically reduced expression levels of anterior prostate marker TGM4. CONCLUSIONS Pax2 is essential for mouse prostate development and regulates prostatic ductal growth, branching, and lobeâspecific identity. These findings are important for understanding the molecular regulatory mechanisms in prostate development. Prostate 72:217â224, 2012. © 2011 Wiley Periodicals, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/89567/1/21424_ftp.pd
Specific microRNAs as novel biomarkers for combination chemotherapy resistance detection of colon adenocarcinoma
Expression analysis onto microarrays of randomly selected cDNA clones highlights HOXB13 as a marker of human prostate cancer
In a strategy aimed at identifying novel markers of human prostate cancer, we performed expression analysis using microarrays of clones randomly selected from a cDNA library prepared from the LNCaP prostate cancer cell line. Comparisons of expression profiles in primary human prostate cancer, adjacent normal prostate tissue, and a selection of other (nonprostate) normal human tissues, led to the identification of a set of clones that were judged as the best candidate markers of normal and/or malignant prostate tissue. DNA sequencing of the selected clones revealed that they included 10 genes that had previously been established as prostate markers: NKX3.1, KLK2, KLK3 (PSA), FOLH1 (PSMA), STEAP2, PSGR, PRAC, RDH11, Prostein and FASN. Following analysis of the expression patterns of all selected and sequenced genes through interrogation of SAGE databases, a further three genes from our clone set, HOXB13, SPON2 and NCAM2, emerged as additional candidate markers of human prostate cancer. Quantitative RTâPCR demonstrated the specificity of expression of HOXB13 in prostate tissue and revealed its ubiquitous expression in a series of 37 primary prostate cancers and 20 normal prostates. These results demonstrate the utility of this expression-microarray approach in hunting for new markers of individual human cancer types
Design and development of a fully synthetic MLPA-based probe mix for detection of copy number alterations in prostate cancer formalin-fixed, paraffin-embedded tissue samples
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