Numerical investigation of nanostructured silica PCFs for sensing applications.

Photonic crystal fibers (PCFs) developed using nanostructured composite materials provide special optical properties. PCF light propagation and modal characteristics can be tailored by modifying their structural and material parameters. Structuring and infusion of liquid crystal materials enhances the capabilities of all silica PCFs, facilitating their operation in different spectral regimes. The wavelength tunability feature of nanostructured PCFs can be utilized for many advanced sensing applications. This paper discusses a new approach to modify the optical properties of PCFs by periodic nanostructuring and composite material (liquid crystal-silica) infiltration. PCF characteristics like confinement wavelength, confinement loss, mode field diameter (MFD) and bandwidth are investigated by varying the structural parameters and material infiltrations. Theoretical study revealed that composite material infusion resulted in a spectral band shift accompanied by an improvement in PCF bandwidth. Moreover, nanostructured PCFs also achieved reduced confinement losses and improved MFD which is very important in long-distance remote sensing applications

Respiratory-gated (4D) contrast-enhanced FDG PET-CT for radiotherapy planning of lower oesophageal carcinoma: Feasibility and impact on planning target volume

Background: To assess the feasibility and potential impact on target delineation of respiratory-gated (4D) contrast-enhanced 18 Fluorine fluorodeoxyglucose (FDG) positron emission tomography - computed tomography (PET-CT), in the treatment planning position, for a prospective cohort of patients with lower third oesophageal cancer. Methods: Fifteen patients were recruited into the study. Imaging included 4D PET-CT, 3D PET-CT, endoscopic ultrasound and planning 4D CT. Target volume delineation was performed on 4D CT, 4D CT with co-registered 3D PET and 4D PET-CT. Planning target volumes (PTV) generated with 4D CT (PTV 4DCT), 4D CT co-registered with 3D PET-CT (PTV 3DPET4DCT) and 4D PET-CT (PTV 4DPETCT ) were compared with multiple positional metrics. Results: Mean PTV 4DCT , PTV 3DPET4DCT and PTV 4DPETCT were 582.4 ± 275.1 cm 3 , 472.5 ± 193.1 cm 3 and 480.6 ± 236.9 cm 3 respectively (no significant difference). Median DICE similarity coefficients comparing PTV 4DCT with PTV 3DPET4DCT, PTV 4DCT with PTV 4DPETCT and PTV 3DPET4DCT with PTV 4DPETCT were 0.85 (range 0.65-0.9), 0.85 (range 0.69-0.9) and 0.88 (range 0.79-0.9) respectively. The median sensitivity index for overlap comparing PTV 4DCT with PTV 3DPET4DCT, PTV 4DCT with PTV 4DPETCT and PTV 3DPET4DCT with PTV 4DPETCT were 0.78 (range 0.65-0.9), 0.79 (range 0.65-0.9) and 0.89 (range 0.68-0.94) respectively. Conclusions: Planning 4D PET-CT is feasible with careful patient selection. PTV generated using 4D CT, 3D PET-CT and 4D PET-CT were of similar volume, however, overlap analysis demonstrated that approximately 20% of PTV 3DPETCT and PTV 4DPETCT are not included in PTV 4DCT , leading to under-coverage of target volume and a potential geometric miss. Additionally, differences between PTV 3DPET4DCT and PTV 4DPETCT suggest a potential benefit for 4D PET-CT. Trial registration: ClinicalTrials.gov Identifier - NCT02285660(Registered 21/10/2014)

MTar: a computational microRNA target prediction architecture for human transcriptome

<p>Abstract</p> <p>Background</p> <p>MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.</p> <p>Results</p> <p>We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.</p> <p>Conclusion</p> <p>MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.</p

Geographical location of Vedic Irina in Southern Rajasthan

Vedic literature refers to a place or region by name Irina. In the Rgveda it appears as a locale frequented by a particular wild animal for drinking water. But with the passage of time, in the Yajurveda texts, the word acquires a negative meaning as a desert or a place devoid of water. Gradually, in the ritualistic Vedic texts Irina gets more and more associated with disaster or misfortune. The physical features associated with Irina, as described metaphorically in the Vedic texts, are analysed to identify its probable location. It is possible the word Irina is the progenitor of the Greek name (gulf of) Eirinon of Periplus which is presently designated as the Ran-of-Kutch. During the Rgveda period Irina was in all probability, situated a little north of the Ran-of-Kutch. Available data indicates its location in the Luni-Jawai plains west of the Aravallis, in Rajasthan. The small town Erinpura (25 degrees 5'N, 73 degrees 3'E) appears to retain memories of the Vedic Irina

Evolution of the Western Coastline of India and the probable location of Dwaraka of Krsna: Geological perspectives

A description of Dwaraka and its environs, its growth and final destruction as narrated in the ancient classics of Mahabhratha, Hari-vamsa, Skanda Purana and Visnu Purana is presented and it is shown that the Dwaraka built by Krsna could not be the Dwaaka located at the western tip of Saurashtra. Geological evidence shows (1) that the coastline of India is a rifted margin with present day Saurashtra, Kachchh, Pacham, Wagir, Bela and other isolated masses occurring as islands off the rifted western margin; (2) the greater part of Saurashtra formed an island of explosive volcanic activity not directly connected with the Deccan trap of the mainland; (3) the existence of the Cambay basin, a long linear sedimentary basin, more than 500 km long with an average width of 50 kin and maximum depth of 7 kin linked the basin with the Gulfs of Cambay and Kachchh maintaining marine connection from early Cretaceous to late Pleistocene and early Holocene (5000 years ago); (4) filling up of the basin with enormous amount of alluvium brought by the rivers Saraswati, Luni, Sabarmati and others - are presented as evidences lending support to the view that the present day Dwaraka, isolated and far removed from Mathura. could not be the original Dwaraka (Ur-Dwaraka) of Krsna. Ur-Dwaraka was nearer to Mathura. and could be reached via Pushkara (near Ajmer) and Mt. Abu and in all probability was located on the eastern margin of the Cambay basin. The city either was drowned or washed away by the sea around 1400 BC. West coast of Gujarat lies at the junction of the African, Asian and Indian plates and is riddled with many active faults and has been an active seismic zone. Authors make a strong plea for a multidisciplinary study by a group consisting of oceanographers, geologists, geophysicists, sedimentologists, engineers and meteorologists to make an intensive study of the region and elucidate the history of development of this terrain and incidentally solve the problem of the location of Ur-Dwaraka