Effect of limited statistics on higher order cumulants measurement in heavy-ion collision experiments

We have studied the effect of limited statistics of data on measurement of the different order of cumulants of net-proton distribution assuming that the proton and antiproton distributions follow Possionian and Binomial distributions with initial parameters determined from experimental results for two top center of mass energies ($\sqrt{s_{\mathrm{NN}}}=200$ and $62.4$ GeV) in most central ($0-5$%) Au$+$Au collisions at Relativistic Heavy Ion Collider (RHIC). In this simulation, we observe that the central values for higher order cumulants have a strong dependence on event sample size and due to statistical randomness the central values of higher order cumulants could become negative. We also present a study on the determination of the statistical error on cumulants using delta theorem, bootstrap and sub-group methods and verified their suitability by employing a Monte Carlo procedure. Based on our study we find that the bootstrap method provides a robust way for statistical error estimation on high order cumulants. We also present the exclusion limits on the minimum event statistics needed for determination of cumulants if the signal strength (phase transition or critical point) is at a level of $5$% and $10$% above the statistical level. This study will help the experiments to arrive at the minimum required event statistics and choice of proper method for statistical error estimation for high order cumulant measurements.Comment: 14 pages, 16 figure

Identifying realistic recovery targets and conservation actions for tigers in a human dominated landscape using spatially-explicit densities of wild prey and their determinants

Aim Setting realistic population targets and identifying actions for site and landscape-level recovery plans are critical for achieving the global target of doubling wild tiger numbers by 2022. Here, we estimate the spatially explicit densities of wild ungulate prey across a gradient of disturbances in two disjunct tiger habitat blocks (THBs) covering 5212 km2, to evaluate landscape-wide conditions for tigers and identify opportunities and specific actions for recovery. Location Western Terai Arc Landscape, India. Methods Data generated from 96 line transects in 15 systematically selected geographical cells (166.5 km2) were used to estimate spatially explicit densities of six wild ungulate prey species at a fine scale (1 km2). Employing distance-based density surface models, we derived species-specific estimates within three major forest land management categories (inviolate protected areas (PA), PAs with settlements and multiple-use forests). By scaling estimated prey densities using an established relationship, we predicted the carrying capacity for tigers within each THB. Results Species-specific responses of the six wild ungulates to natural-habitat and anthropogenic covariates indicated the need for targeted prey recovery strategies. Inviolate PAs supported the highest prey densities compared with PAs with settlements and multiple-use forests, and specifically benefited the principal tiger prey species (chital Axis axis and sambar Rusa unicolor). The estimated mean prey density of 35.16 (±5.67) individuals per km2 can potentially support 82 (62–106) and 299 (225–377) tigers across THB I and THB II, which currently support 2 (2–7) and 225 (199–256) tigers, respectively. This suggests a potential c. 68% increase in population size given existing prey abundances. Finally, while THB I represents a potential tiger recovery site given adequate prey, PAs where resettlement of pastoralists is underway represent potential prey recovery sites in THB II. Main conclusions This systematic approach of setting realistic population targets and prioritizing spatially explicit recovery strategies should aid in developing effective landscape conservation plans towards achieving global tiger conservation targets

Rotco twins making progress

Modified WHO Job Aid Algorithms. (PDF 126 kb

Picture Detection in RSVP: Features or Identity?

A pictured object can be readily detected in a rapid serial visual presentation sequence when the target is specified by a superordinate category name such as animal or vehicle. Are category features the initial basis for detection, with identification of the specific object occurring in a second stage (Evans & Treisman, 2005), or is identification of the object the basis for detection? When 2 targets in the same superordinate category are presented successively (lag 1), only the identification-first hypothesis predicts lag 1 sparing of the second target. The results of 2 experiments with novel pictures and a wide range of categories supported the identification-first hypothesis and a transient-attention model of lag 1 sparing and the attentional blink (Wyble, Bowman, & Potter, 2009)National Institute of Mental Health (U.S.) (grant MH47432

A novel double quad-inverter configuration for multilevel twelve-phase open-winding converter

This paper work articulates the novel proposal of double quad-inverter configuration for multilevel twelve-phase open-winding ac converter. Modular power units are developed from reconfigured eight classical three-phase voltage source inverters (VSIs). Each VSI has one additional bi-directional switching device (MOSFET/IGBT) per each phase and linked neutral with two capacitors. An original modified single carrier five-level modulation (MSCFM) algorithm is developed and modulates each 2-level VSIs as equivalent to ones 5-level multilevel inverter. Observed set of results are presented with model based numerical simulation software’s (Matlab/PLECS) developments. Further, the results confirm the good agreement to the developed theoretical background. Proposed converter suits the need of low-voltage/high-current applications such as ac tractions and ‘More-Electric Aircraft’ propulsion system

From Research to Policy to Programme: Success Story of Seven State Iodine Deficiency Disorders (IDD) Survey in India

Iodine Deficiency Disorders (IDD) constitute the single largest cause of preventable brain damage worldwide. In India the entire population is prone to IDD due to deficiency of iodine in the soil of the subcontinent and consequently the food derived from it. Of these, an estimated 350 million people are at higher risk of IDDs as they consume salt with inadequate iodine. Every year nine million pregnant women and eight million newborns are at risk of IDD in India.On September 13, 2000, the Government of India lifted the ban at the national level on the sale of non-iodized salt (India Gazette 2000). Scientists, civil society, international agencies and other stakeholders joined ranks to fight against this retrograde step by the government of India. The four pronged approach to fight the removal of ban on non- iodized salt comprised of writing advocacy documents, meeting with stakeholders, media campaign and tracking of Universal Salt Iodization (USI) in states by state iodine status surveys.But effective advocacy and media campaign were hampered by lack of scientific data substantiating the magnitude of Iodine Deficiency disorders (IDD) in India. To address this lacuna, state level Iodine status surveys were planned in seven states of India and were executed over next five years in collaboration with various national and international stakeholders.State level IDD surveys were carried out in seven states (Kerala, Tamil Nadu, Orissa, Rajasthan, Bihar, Goa and Jharkhand) from 2000 to 2006 by International Council for Control of Iodine Deficiency Disorders (ICCIDD) in collaboration with state medical colleges, Micronutrient Initiative (MI) and UNICEF. The surveys were carried as per the recommended guidelines of WHO/UNICEF/ICCIDD and used 30 cluster into 40 children sampling methodology. Children in the age group of 6-12 years, women in the household, retail shop keepers and other community stakeholders constituted the study population. All three indicators viz. Total Goiter Rate (TGR), Urinary Iodine (UI) concentration and iodine content of salt (household and retail shop) were studied. TGR ranged from 0.9% in Jharkhand to 14.7% in Goa. The median urinary iodine excretion ranged from 76 µg/L in Goa to 173.2 µg/L in Jharkhand. The household level consumption of adequately iodized salt ( ≥ 15 ppm) ranged from 18.2% in Tamil Nadu to 91.9% in Goa. These state level IDD surveys are the only sub-national (state) level IDD surveys in India where all three indicators viz. iodized salt coverage, urinary iodine and TGR were assessed concurrently.These surveys provided valuable reliable scientific data to back up the need of urgency to re-instate the ban and aided in convincing wider scientific community and policy makers regarding the need for the same. These surveys also aided in capacity building at state level which will provide necessary impetus to sustain USI. The ban on sale of non-iodized salt was finally re-instated in May, 2005.Purpose of the study : To understand the complex policy environment in which National Health Programmes in India are operating.Basic Procedures : A case study approach applying the criteria of policy formulation and policy implementation to National Iodine Deficiency Disorders Control Programme (NIDDCP).Main Findings : The major limiting factor in the implementation of NIDDCP was that the community perceptions about IDD and iodized salt and their interests and beliefs (Values) were not explicitly considered as part of the implementation process. Addressing the values through sustained advocacy, development of partnerships among stakeholders, supply and demand side interventions and more research based on the programme needs helped in achieving sustainability in elimination of IDD.Conclusion : In formulating National Health Programmes in a policy environment, scientific inputs, political will and institutional structure for decision making are necessary but not sufficient. Pro-active recognition values of key stakeholders, continuous and dynamic generation of scientific information and development of partnerships are critical for sustainability of the National Health Programmes

Ensemble transcript interaction networks: A case study on Alzheimer's disease

Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of A