A Study of the Dynamics of Dust from the Kuiper Belt: Spatial Distribution and Spectral Energy Distribution

The dust produced in the Kuiper Belt (KB) spreads throughout the Solar System forming a dust disk. We numerically model the orbital evolution of KB dust and estimate its equilibrium spatial distribution and its brightness and spectral energy distributions (SED), assuming greybody absorption and emission by the dust grains. We show that the planets modify the KB disk SED, so potentially we can infer the presence of planets in spatially unresolved debris disks by studying the shape of their SEDs. We point out that there are inherent uncertainties in the prediction of structure in the dust disk, owing to the chaotic dynamics of dust orbital evolution imposed by resonant gravitational perturbations of the planets.Comment: 19 pages, 14 figures in jpg, accepted to A

Magnetomotive Molecular Nanoprobes

Tremendous developments in the field of biomedical imaging in the past two decades have resulted in the transformation of anatomical imaging to molecular-specific imaging. The main approaches towards imaging at a molecular level are the development of high resolution imaging modalities with high penetration depths and increased sensitivity, and the development of molecular probes with high specificity. The development of novel molecular contrast agents and their success in molecular optical imaging modalities have lead to the emergence of molecular optical imaging as a more versatile and capable technique for providing morphological, spatial, and functional information at the molecular level with high sensitivity and precision, compared to other imaging modalities. In this review, we discuss a new class of dynamic contrast agents called magnetomotive molecular nanoprobes for molecular-specific imaging. Magnetomotive agents are superparamagnetic nanoparticles, typically iron-oxide, that are physically displaced by the application of a small modulating external magnetic field. Dynamic phase-sensitive position measurements are performed using any high resolution imaging modality, including optical coherence tomography (OCT), ultrasonography, or magnetic resonance imaging (MRI). The dynamics of the magnetomotive agents can be used to extract the biomechanical tissue properties in which the nanoparticles are bound, and the agents can be used to deliver therapy via magnetomotive displacements to modulate or disrupt cell function, or hyperthermia to kill cells. These agents can be targeted via conjugation to antibodies, and in vivo targeted imaging has been shown in a carcinogeninduced rat mammary tumor model. The iron-oxide nanoparticles also exhibit negative T2 contrast in MRI, and modulations can produce ultrasound imaging contrast for multimodal imaging application

IIT-Hyderabad incubated start-up develops IoT-enabled, low-cost ventilator

Aerobiosys Innovations, a start-up incubated at The Center for Healthcare Entrepreneurship (CfHE) in the Indian Institute of Technology-Hyderabad (IIT-H), has developed a low-cost, portable ventilator

The Dynamics of Known Centaurs

We have numerically investigated the long term dynamical behavior of known Centaurs. This class of objects is thought to constitute the transitional population between the Kuiper Belt and the Jupiter-family comets (JFCs). In our study, we find that over their dynamical lifetimes, these objects diffuse into the JFCs and other sinks, and also make excursions into the Scattered Disk, but (not surprisingly) do not diffuse into the parameter space representing the main Kuiper Belt. These Centaurs spend most of their dynamical lifetimes in orbits of eccentricity 0.2-to-0.6 and perihelion distance 12-to-30 AU. Their orbital evolution is characterized by frequent close encounters with the giant planets. Most of these Centaurs will escape from the solar system (or enter the Oort Cloud), while a fraction will enter the JFC population and a few percent will impact a giant planet. Their median dynamical lifetime is 9 Myr, although there is a wide dispersion in lifetimes, ranging from less than 1 Myr to more than 100 Myr. We find the dynamical evolution of this sample of Centaurs to be less orderly than the planet-to-planet "hand-off" described in previous investigations. We discuss the implications of our study for the spatial distribution of the Centaurs as a whole.Comment: 13 pages, 11 figures, revised version in press at A

Case report on interstitial pregnancy in a post adenomyomectomy woman

Intramural pregnancy is a rare form of ectopic pregnancy with early diagnosis essential for prevention of severe hemorrhage and uterine rupture. We report a rare case of an interstitial ectopic pregnancy at 09 weeks gestation in a woman 3 year post laparoscopic adenomyomectomy. 3D transvaginal ultrasound was utilized as diagnostic aids in this case. Due to the size and location of the gestational sac, and early diagnosis made this case undergo conservative surgical management saving her uterus for future pregnancy

Applications of Support Vector Machines as a Robust tool in High Throughput Virtual Screening

Chemical space is enormously huge but not all of it is pertinent for the drug designing. Virtual screening methods act as knowledge-based filters to discover the coveted novel lead molecules possessing desired pharmacological properties. Support Vector Machines (SVM) is a reliable virtual screening tool for prioritizing molecules with the required biological activity and minimum toxicity. It has to its credit inherent advantages such as support for noisy data mainly coming from varied high-throughput biological assays, high sensitivity, specificity, prediction accuracy and reduction in false positives. SVM-based classification methods can efficiently discriminate inhibitors from non-inhibitors, actives from inactives, toxic from non-toxic and promiscuous from non-promiscuous molecules. As the principles of drug design are also applicable for agrochemicals, SVM methods are being applied for virtual screening for pesticides too. The current review discusses the basic kernels and models used for binary discrimination and also features used for developing SVM-based scoring functions, which will enhance our understanding of molecular interactions. SVM modeling has also been compared by many researchers with other statistical methods such as Artificial Neural Networks, k-nearest neighbour (kNN), decision trees, partial least squares, etc. Such studies have also been discussed in this review. Moreover, a case study involving the use of SVM method for screening molecules for cancer therapy has been carried out and the preliminary results presented here indicate that the SVM is an excellent classifier for screening the molecules