4,8-Dimethyl­pyrano[2,3-a]carbazol-2(11H)-one

The mol­ecule of the title compound, C17H13NO2, is nearly planar, the r.m.s. deviation for all non-H atoms excluding the two methyl C atoms being 0.089 Å. Inter­molecular N—H⋯O and C—H⋯O hydrogen bonds are found in the crystal structure. C—H⋯π inter­actions are also found. The H atoms of the methyl group attached to the benzene ring are disordered equally over two positions

Expected time to recruitment in a single grade manpower system with two thresholds

In this paper, a single graded marketing organization which is subject to loss of manpower due to its policy decisions is considered. A mathematical model is constructed using an univariate recruitment policy based on the shock model approach involving two thresholds (one is optional and the another one is mandatory) via order statistics for interdecision time. The performance measures of the time to recruitment are obtained. Also the new findings are verified with numerical illustration

Spatial heterogeneity in the radiogenic activity of the lunar interior: Inferences from CHACE and LLRI on Chandrayaan-1

In the past, clues on the potential radiogenic activity of the lunar interior have been obtained from the isotopic composition of noble gases like Argon. Excess Argon (40) relative to Argon (36), as compared to the solar wind composition, is generally ascribed to the radiogenic activity of the lunar interior. Almost all the previous estimates were based on, 'on-the-spot' measurements from the landing sites. Relative concentration of the isotopes of 40Ar and 36Ar along a meridian by the Chandra's Altitudinal Composition Explorer (CHACE) experiment, on the Moon Impact Probe (MIP) of India's first mission to Moon, has independently yielded clues on the possible spatial heterogeneity in the radiogenic activity of the lunar interior in addition to providing indicative 'antiquity' of the lunar surface along the ground track over the near side of the moon. These results are shown to broadly corroborate the independent topography measurements by the Lunar Laser Ranging Instrument (LLRI) in the main orbiter Chandrayaan-1. The unique combination of these experiments provided high spatial resolution data while indicating the possible close linkages between the lunar interior and the lunar ambience

Remedial Measures to a Building Settlement Problem

A ten storeyed building, built on a subsoil of an onshore marine soil, was observed to be tilting away from the vertical. Extensive field and laboratory investigations were carried out to establish the reasons for the differential settlement causing the tilting. Though, nearly uniform pressure has been achieved at the foundation level, presence of a soft marine clay layer with varied thickness and location has caused the differential settlement. To arrest further increase in differential settlement, micropiling in the zone of higher settlement and additional loading and lowering of water table in the zone of lower settlement have been carried out as remedial measures. Controlled removal of the silty soil from below the foundation in the low settlement zone has reduced the differential settlement. The performance of the remedial measures has been monitored for more than two years

Precise Null Pointer Analysis Through Global Value Numbering

Precise analysis of pointer information plays an important role in many static analysis techniques and tools today. The precision, however, must be balanced against the scalability of the analysis. This paper focusses on improving the precision of standard context and flow insensitive alias analysis algorithms at a low scalability cost. In particular, we present a semantics-preserving program transformation that drastically improves the precision of existing analyses when deciding if a pointer can alias NULL. Our program transformation is based on Global Value Numbering, a scheme inspired from compiler optimizations literature. It allows even a flow-insensitive analysis to make use of branch conditions such as checking if a pointer is NULL and gain precision. We perform experiments on real-world code to measure the overhead in performing the transformation and the improvement in the precision of the analysis. We show that the precision improves from 86.56% to 98.05%, while the overhead is insignificant.Comment: 17 pages, 1 section in Appendi

A Generative-Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data

We propose a matrix factorization technique that decomposes the resting state fMRI (rs-fMRI) correlation matrices for a patient population into a sparse set of representative subnetworks, as modeled by rank one outer products. The subnetworks are combined using patient specific non-negative coefficients; these coefficients are also used to model, and subsequently predict the clinical severity of a given patient via a linear regression. Our generative-discriminative framework is able to exploit the structure of rs-fMRI correlation matrices to capture group level effects, while simultaneously accounting for patient variability. We employ ten fold cross validation to demonstrate the predictive power of our model on a cohort of fifty eight patients diagnosed with Autism Spectrum Disorder. Our method outperforms classical semi-supervised frameworks, which perform dimensionality reduction on the correlation features followed by non-linear regression to predict the clinical scores