Differential reproductive success in Cassia fistula in different habitants-A case of pollinator limitations?

Differences in flower success patterns in two habitat types that differed drastically with respect to rainfall, tree density and species composition were studied at Mudumalai wildlife sanctuary, India. Observations on phenological patterns of two species, Cassia fistula and Gmelina arborea, were made from April 1988 through June 1990. Quantitative data on flower-fruit ratio, insect visitation rates, pollen grain per stigma and the number of fruits per tree were recorded. Data were also collected on the number of pollen deposited on the stigma after different types of bees visited the flower. The data suggested that only carpenter bees (Xylocopa spp) effect pollination in C. fistula. The differences in fruit-flower ratios were attributed to the differences in insect visitation rates to inflorescences between sites. The low pollen number per stigma and the resultant reduction in reproductive success in C. fistula are attributed to the competing species G. arborea receiving more visitations from pollinators in the wetter site. These results suggest that pollinator limitation is another constraint in reproductive success of plants.

Interest in university studies : Its role and relation to other motivational variables

This dissertation empirically explored interest as a motivational force in university studies, including the role it currently plays and possible ways of enhancing this role as a student motivator. The general research questions were as follows: 1) What role does interest play in university studies? 2) What explains academic success if studying is not based on interest? 3) How do different learning environments support or impede interest-based studying? Four empirical studies addressed these questions. Study 1 (n=536) compared first-year students explanations of their disciplinary choices in three fields: veterinary medicine, humanities and law. Study 2 (n=28) focused on the role of individual interest in the humanities and veterinary medicine, fields which are very different from each other as regards their nature of studying. Study 3 (n=52) explored veterinary students motivation and study practices in relation to their study success. Study 4 (n=16) explored veterinary students interest experience in individual lectures on a daily basis. By comparing different fields and focusing on one study field in more detail, it was possible to obtain a many-sided picture of the role of interest in different learning environments. Questionnaires and quantitative methods have often been used to measure interest in academic learning. The present work is based mostly on qualitative data, and qualitative methods were applied to add to the previous research. Study 1 explored students open-ended answers, and these provided a basis for the interviews in Study 2. Study 3 explored veterinary students portfolios in a longitudinal setting. For Study 4, a diary including both qualitative and quantitative measures was designed to capture veterinary students interest experience. Qualitative content analysis was applied in all four studies, but quantitative analyses were also added. The thesis showed that university students often explain their disciplinary choices in terms of interest. Because interest is related to high-quality learning, the students seemed to have a good foundation for successful studies. However, the learning environments did not always support interest-based studying; Time-management and coping skills were found to be more important than interest in terms of study success. The results also indicated that interest is not the only motivational variable behind university studies. For example, future goals are needed in order to complete a degree. Even so, the results clearly indicated that it would be worth supporting interest-based studying both in professionally and generally oriented study fields. This support is important not only to promote high-quality learning but also meaningful studying, student well-being, and life-long learning.

A Study on the Success Potential of Multiple Mobile Payment Technologies

Payment systems all over the world have grown into a complicated web of solutions. This is more challenging in the case of mobile based payment systems. Mobile based payment systems are many and consist of different technologies providing different services. The diffusion of these various technologies in a market is uncertain. Diffusion theorists, for example Rogers, and Davis suggest how innovation is accepted in markets. In the case of electronic payment systems, the tale of Mondex vs Octopus throws interesting insights on diffusion. Our paper attempts to understand the success potential of various mobile payment technologies. We illustrate what we describe as technology breadth in mobile payment systems using data from payment systems all over the world (n=62). Our data shows an unexpected superiority of SMS technology, over other technologies like NFC, WAP and others. We also used a Delphi based survey (n=5) with experts to address the possibility that SMS will gain superiority in market diffusion. The economic conditions of a country, particularly in developing countries, the services availed and characteristics of the user (for example number of un-banked users in large populated countries) may put SMS in the forefront. This may be true more for micro payments using the mobile.

A game theoretical multiple resource interaction approach to resource allocation in an air campaign

In this paper we propose a multiple resource interaction model in a game-theoretical framework to solve resource allocation problems in theater level military campaigns. An air raid campaign using SEAD aircraft and bombers against an enemy target defended by air defense units is considered as the basic platform. Conditions for the existence of saddle point in pure strategies is proved and explicit feedback strategies are obtained for a simplified model with linear attrition function limited by resource availability. An illustrative example demonstrates the key features.

Middleware for Long-running Applications on Batch Grids. Student Research Symposium poster

Computational grids with multiple batch systems (batch grids) can be powerful infrastructures for executing long-running multicomponent parallel applications. In this paper, we have constructed a middleware framework for executing such long-running applications spanning multiple submissions to the queues on multiple batch systems. We have used our framework for execution of a foremost long-running multi-component application for climate modeling, the Community Climate System Model (CCSM). Our framework coordinates the distribution, execution, migration and restart of the components of CCSM on the multiple queues where the component jobs of the different queues can have different queue waiting and startup times.

A mixture model approach for formant tracking and the robustness of student's-t distribution

We address the problem of robust formant tracking in continuous speech in the presence of additive noise. We propose a new approach based on mixture modeling of the formant contours. Our approach consists of two main steps: (i) Computation of a pyknogram based on multiband amplitude-modulation/frequency-modulation (AM/FM) decomposition of the input speech; and (ii) Statistical modeling of the pyknogram using mixture models. We experiment with both Gaussian mixture model (GMM) and Student's-t mixture model (tMM) and show that the latter is robust with respect to handling outliers in the pyknogram data, parameter selection, accuracy, and smoothness of the estimated formant contours. Experimental results on simulated data as well as noisy speech data show that the proposed tMM-based approach is also robust to additive noise. We present performance comparisons with a recently developed adaptive filterbank technique proposed in the literature and the classical Burg's spectral estimator technique, which show that the proposed technique is more robust to noise.

Influence limitation in multi-campaign social networks: A Shapley value based approach

We investigate the problem of influence limitation in the presence of competing campaigns in a social network. Given a negative campaign which starts propagating from a specified source and a positive/counter campaign that is initiated, after a certain time delay, to limit the the influence or spread of misinformation by the negative campaign, we are interested in finding the top k influential nodes at which the positive campaign may be triggered. This problem has numerous applications in situations such as limiting the propagation of rumor, arresting the spread of virus through inoculation, initiating a counter-campaign against malicious propaganda, etc. The influence function for the generic influence limitation problem is non-submodular. Restricted versions of the influence limitation problem, reported in the literature, assume submodularity of the influence function and do not capture the problem in a realistic setting. In this paper, we propose a novel computational approach for the influence limitation problem based on Shapley value, a solution concept in cooperative game theory. Our approach works equally effectively for both submodular and non-submodular influence functions. Experiments on standard real world social network datasets reveal that the proposed approach outperforms existing heuristics in the literature. As a non-trivial extension, we also address the problem of influence limitation in the presence of multiple competing campaigns.

STUDENT'S-t MIXTURE MODEL BASED MULTI-INSTRUMENT RECOGNITION IN POLYPHONIC MUSIC

We address the problem of multi-instrument recognition in polyphonic music signals. Individual instruments are modeled within a stochastic framework using Student's-t Mixture Models (tMMs). We impose a mixture of these instrument models on the polyphonic signal model. No a priori knowledge is assumed about the number of instruments in the polyphony. The mixture weights are estimated in a latent variable framework from the polyphonic data using an Expectation Maximization (EM) algorithm, derived for the proposed approach. The weights are shown to indicate instrument activity. The output of the algorithm is an Instrument Activity Graph (IAG), using which, it is possible to find out the instruments that are active at a given time. An average F-ratio of 0 : 7 5 is obtained for polyphonies containing 2-5 instruments, on a experimental test set of 8 instruments: clarinet, flute, guitar, harp, mandolin, piano, trombone and violin.

How to run a campaign: Optimal control of SIS and SIR information epidemics

Information spreading in a population can be modeled as an epidemic. Campaigners (e.g., election campaign managers, companies marketing products or movies) are interested in spreading a message by a given deadline, using limited resources. In this paper, we formulate the above situation as an optimal control problem and the solution (using Pontryagin's Maximum Principle) prescribes an optimal resource allocation over the time of the campaign. We consider two different scenarios-in the first, the campaigner can adjust a direct control (over time) which allows her to recruit individuals from the population (at some cost) to act as spreaders for the Susceptible-Infected-Susceptible (SIS) epidemic model. In the second case, we allow the campaigner to adjust the effective spreading rate by incentivizing the infected in the Susceptible-Infected-Recovered (SIR) model, in addition to the direct recruitment. We consider time varying information spreading rate in our formulation to model the changing interest level of individuals in the campaign, as the deadline is reached. In both the cases, we show the existence of a solution and its uniqueness for sufficiently small campaign deadlines. For the fixed spreading rate, we show the effectiveness of the optimal control strategy against the constant control strategy, a heuristic control strategy and no control. We show the sensitivity of the optimal control to the spreading rate profile when it is time varying. (C) 2014 Elsevier Inc. All rights reserved.

Emergent properties of the interferon-signalling network may underlie the success of hepatitis C treatment

Current interferon alpha-based treatment of hepatitis C virus (HCV) infection fails to cure a sizeable fraction of patients treated. The cause of this treatment failure remains unknown. Here using mathematical modelling, we predict treatment failure to be a consequence of the emergent properties of the interferon-signalling network. HCV induces bistability in the network, creating a new steady state where it can persist. Cells that admit the new steady state alone are refractory to interferon. Using a model of viral kinetics, we show that when the fraction of cells refractory to interferon in a patient exceeds a critical value, treatment fails. Direct-acting antivirals that suppress HCV replication can eliminate the new steady state, restoring interferon sensitivity and improving treatment response. Our study thus presents a new conceptual basis of HCV persistence and treatment response, elucidates the origin of the synergy between interferon and direct-acting antivirals, and facilitates rational treatment optimization.

Sources of black carbon aerosols in South Asia and surrounding regions during the Integrated Campaign for Aerosols, Gases and Radiation Budget (ICARB)

This study examines differences in the surface black carbon (BC) aerosol loading between the Bay of Bengal (BoB) and the Arabian Sea (AS) and identifies dominant sources of BC in South Asia and surrounding regions during March-May 2006 (Integrated Campaign for Aerosols, Gases and Radiation Budget, ICARB) period. A total of 13 BC tracers are introduced in the Weather Research and Forecasting Model coupled with Chemistry to address these objectives. The model reproduced the temporal and spatial variability of BC distribution observed over the AS and the BoB during the ICARB ship cruise and captured spatial variability at the inland sites. In general, the model underestimates the observed BC mass concentrations. However, the model-observation discrepancy in this study is smaller compared to previous studies. Model results show that ICARB measurements were fairly well representative of the AS and the BoB during the pre-monsoon season. Elevated BC mass concentrations in the BoB are due to 5 times stronger influence of anthropogenic emissions on the BoB compared to the AS. Biomass burning in Burma also affects the BoB much more strongly than the AS. Results show that anthropogenic and biomass burning emissions, respectively, accounted for 60 and 37% of the average +/- standard deviation (representing spatial and temporal variability) BC mass concentration (1341 +/- 2353 ng m(-3)) in South Asia. BC emissions from residential (61 %) and industrial (23 %) sectors are the major anthropogenic sources, except in the Himalayas where vehicular emissions dominate. We find that regional-scale transport of anthropogenic emissions contributes up to 25% of BC mass concentrations in western and eastern India, suggesting that surface BC mass concentrations cannot be linked directly to the local emissions in different regions of South Asia.

Innovation processes within the healthcare industry: Determining critical success factors aligned to product strategies

The impact of differing product strategies on product innovation processes pursued by healthcare firms is discussed. The critical success factors aligned to product strategies are presented. A definite split between pioneering product strategies and late entrant product strategies is also recognised.