Education in India: An Overview of Challenges and Philanthropic Opportunities

India's young population and productive workforce are a remarkable asset to the country, but large gaps in the education sector hinder it from realizing the true potential of this gift. Where are the needs and how can donors help

Determinants of Weekly Yields on Government Securities in India

This paper examines the determinants of the Government yields in India using weekly data from April 2001 through March 2009. The analysis covers Treasury Bills with residual maturity of 15-91 days and Government securities of residual maturity one, five and ten years respectively. The empirical estimates show that a long-run relationship exists between each of these interest rates and the policy rate, rate of growth of money supply, inflation, interest rate spread, foreign interest rate and forward premium. At the same time, the empirical results also show that the relative importance of the determinants varies across the maturity spectrum. The normalized generalized variance decompositions suggest that the policy rate and the rate of growth of high powered money are less important in explaining the proportion of variation in longer term interest rates. The weight of the forward premium also diminishes as we move towards higher maturity interest rates. The inflation rate is also relatively less important in explaining variations in the 10-year rate. The yield spread, on the other hand, is more important in explaining the longer term rates. The results also show that a large proportion of the variation in the rates on the 5-year and 10-year government securities is attributed to the interest rate itself suggesting that the unexplained variation may be a result of cyclical factors that are relatively more important for longer term rates but are not captured by the yield spread and are omitted from the estimations due to the high frequency of data employed.interest rate determination; government yields; cointegration and generalized variance decompositions

Signals of supersymmetry with inaccessible first two families at the Large Hadron Collider

We investigate the signals of supersymmetry (SUSY) in a scenario where only the third family squarks and sleptons can be produced at the Large Hadron Collider (LHC), in addition to the gluino, charginos and neutralinos. The final states in such cases are marked by a multiplicity of top and/or bottom quarks. We study in particular, the case when the stop, sbottom and gluino masses are near the TeV scale due to which, the final state t's and b's are very energetic. We point out the difficulty in b-tagging and identifying energetic tops and suggest several event selection criteria which allow the signals to remain significantly above the standard model background. We show that such scenarios with gluino mass up to 2 TeV can be successfully probed at the LHC. Information on $\tan \beta$ can also be obtained by looking at associated Higgs production in the cascades of accompanying neutralinos. We also show that a combined analysis of event rates in the different channels and the effective mass distribution allows one to differentiate this scenario from the one where all three sfermion families are accessible.Comment: v3: 17 pages, 8 figures, 7 table

An updated analysis of radion-higgs mixing in the light of LHC data

We explore the constraints on the parameter space of a Randall-Sundrum warped geometry scenario, where a radion field arises out of the attempt to stabilise the radius of the extra compact spacelike dimension, using the most recent data from higgs searches at the Large Hadron Collider (LHC) and the Tevatron. We calculate contributions from both the scalar mass eigenstates arising from radion-higgs kinetic mixing in all important search channels. The most important channel to be affected is the decay via WW*, where no invariant mass peak can discern the two distinct physical states. Improving upon the previous studies, we perform a full analysis in the WW* channel, taking into account the effect of various cuts and interference when the two scalar are closely spaced. We examine both cases where the experimentally discovered scalar is either 'higgs-like' or 'radion-like'. The implications of a relatively massive scalar decaying into a pair of 125 GeV scalars is also included. Based on a global analysis of the current data, including not only a single 125 GeV scalar but also another one with mass over the range 110 to 600 GeV, we obtain the up-to-date exclusion contours in the parameter space. Side by side, regions agreeing with the data within 68% and 95% confidence level based on a \chi^2-minimisation procedure, are also presented

Interest Rate Modeling and Forecasting in India

The study develops univariate (ARIMA and ARCH/GARCH) and multivariate models (VAR, VECM and Bayesian VAR) to forecast short- and long-term rates, viz., call money rate, 15-91 days Treasury Bill rates and interest rates on Government securities with (residual) maturities of one year, five years and ten years. Multivariate models consider factors such as liquidity, Bank Rate, repo rate, yield spread, inflation, credit, foreign interest rates and forward premium. The study finds that multivariate models generally outperform univariate ones over longer forecast horizons. Overall, the study concludes that the forecasting performance of Bayesian VAR models is satisfactory for most interest rates and their superiority in performance is marked at longer forecast horizons.

Compressed and Split Spectra in Minimal SUSY SO(10)

The non-observation of supersymmetric signatures in searches at the Large Hadron Collider strongly constrains minimal supersymmetric models like the CMSSM. We explore the consequences on the SUSY particle spectrum in a minimal SO(10) with large D-terms and non-universal gaugino masses at the GUT scale. This changes the sparticle spectrum in a testable way and for example can sufficiently split the coloured and non-coloured sectors. The splitting provided by use of the SO(10) D-terms can be exploited to obtain light first generation sleptons or third generation squarks, the latter corresponding to a compressed spectrum scenario.Comment: 35 pages, 10 figures, published versio

Closing in on the Tip of the CMSSM Stau Coannihilation Strip

Near the tip of the stau coannihilation strip in the CMSSM with a neutralino LSP, the astrophysical cold dark matter density constraint forces the stau-neutralino mass difference to be small. If this mass difference is smaller than the tau mass, the stau may decay either in the outer part of an LHC detector - the `disappearing track' signature - or be sufficiently long-lived to leave the detector before decaying - the long-lived massive charged-particle signature. We combine searches for these signatures with conventional missing transverse energy searches during LHC Run 1, identifying the small remaining parts of the CMSSM stau coannihilation strip region that have not yet been excluded, and discussing how they may be explored during Run 2 of the LHC.Comment: 19 pages, 6 figures. Fig. 1 and the corresponding text are changed due to the updated ATLAS result (ref.[16]). More details of our simulation are provided in Section 3.1. The caption of Fig. 6 and the corresponding text are changed. Matches the published versio

Blacow Road Improvement Plan

Providing safe and accessible entrances to schools, especially elementary, middle, and high schools where children are below the age of 18, should be of utmost priority to cities. Providing wide sidewalks, painted bicycle lanes and continental crosswalks (with the lateral lines) are just basic infrastructure improvements that can be made within the vicinity of a school. However, due to lack of funding or attention from the city departments, many school entryways are being neglected and the direct impact of this is increased collisions among students, drivers, and bicyclists. My senior project studied one such school in Fremont, California where the entrance is not very efficient or safe for any mode of transport, including pedestrian traffic

DISTINGUISHING EARTHQUAKES AND NOISE USING RANDOM FOREST ALGORITHM

Earthquakes are a major cause of life and property destruction. It is known that earthquakes radiate energy in the form of surface and body seismic waves. P-wave and S-waves are types of body waves. Both waves can be detected and recorded at an earthquake station. These waves can be analyzed to detect earthquakes. Most of the earthquake prediction techniques today are a combination of geophysics and signal processing, which are relatively complex. Machine learning can be used to learn the behavior of seismic waves and help in early detection. Machine learning can also be employed to process massive amounts of raw seismic data. The goal of this project is to distinguish between earthquakes and noise. Recordings of seismic waves from earthquake stations contain significant noise, for example from mining explosions or surface vibrations caused by vehicle traffic. It is necessary to distinguish between noise and actual earthquake signals. In this project machine learning classification techniques will be used for this purpose