Strong clustering of underdense regions and the environmental dependence of clustering from Gaussian initial conditions

We discuss two slightly counter-intuitive findings about the environmental dependence of clustering in the Sloan Digital Sky Survey. First, we find that the relation between clustering strength and density is not monotonic: galaxies in the densest regions are more strongly clustered than are galaxies in regions of moderate overdensity; galaxies in moderate overdensities are more strongly clustered than are those in moderate underdensities; but galaxies in moderate underdensities are less clustered than galaxies in the least dense regions. We argue that this is natural if clustering evolved gravitationally from a Gaussian field, since the highest peaks and lowest troughs in Gaussian fields are similarly clustered. The precise non-monotonic dependence of galaxy clustering on density is very well reproduced in a mock catalog which is based on a halo-model decomposition of galaxy clustering. Second, the distribution of galaxy counts in our sample is rather well described by a Poisson cluster model. We show that, despite their Poisson nature, correlations with environment are expected in such models. More remarkably, the expected trends are very like those in standard models of halo bias, despite the fact that correlations with environment in these models arise purely from the fact that dense regions are dense because they happen to host more massive halos. This is in contrast to the usual analysis which assumes that it is the large scale environment which determines the halo mass function. [Abridged]Comment: 10 pages, 5 figures, accepted for publication in MNRA

A Multi Hidden Recurrent Neural Network with a Modified Grey Wolf Optimizer

Identifying university students' weaknesses results in better learning and can function as an early warning system to enable students to improve. However, the satisfaction level of existing systems is not promising. New and dynamic hybrid systems are needed to imitate this mechanism. A hybrid system (a modified Recurrent Neural Network with an adapted Grey Wolf Optimizer) is used to forecast students' outcomes. This proposed system would improve instruction by the faculty and enhance the students' learning experiences. The results show that a modified recurrent neural network with an adapted Grey Wolf Optimizer has the best accuracy when compared with other models.Comment: 34 pages, published in PLoS ON

Effects of Length and Diameter of Open-Ended Coaxial Sensor on its Reflection Coefficient

This paper presents a calibration technique for a coaxial sensor using a transmission signal approach. The sensor was fabricated from commercially available RG402/U and RG405/U semi-rigid coaxial cable. The length of the coaxial sensor was correlated with the attenuation and standing wave inside the coaxial line. The functions of multiple reflection amplitude and tolerance length with respect to the actual length of coaxial line were empirically formulated using regression analysis. The tolerances and the undesired standing wave which occurs along the coaxial line were analyzed in detai

Research options for controlling Zoonotic disease in India, 2010-2015

BACKGROUND: Zoonotic infections pose a significant public health challenge for low- and middle-income countries and have traditionally been a neglected area of research. The Roadmap to Combat Zoonoses in India (RCZI) initiative conducted an exercise to systematically identify and prioritize research options needed to control zoonoses in India. METHODS AND FINDINGS: Priority setting methods developed by the Child Health and Nutrition Research Initiative were adapted for the diversity of sectors, disciplines, diseases and populations relevant for zoonoses in India. A multidisciplinary group of experts identified priority zoonotic diseases and knowledge gaps and proposed research options to address key knowledge gaps within the next five years. Each option was scored using predefined criteria by another group of experts. The scores were weighted using relative ranks among the criteria based upon the feedback of a larger reference group. We categorized each research option by type of research, disease targeted, factorials, and level of collaboration required. We analysed the research options by tabulating them along these categories. Seventeen experts generated four universal research themes and 103 specific research options, the majority of which required a high to medium level of collaboration across sectors. Research options designated as pertaining to 'social, political and economic' factorials predominated and scored higher than options focussing on ecological, genetic and biological, or environmental factors. Research options related to 'health policy and systems' scored highest while those related to 'research for development of new interventions' scored the lowest. CONCLUSIONS: We methodically identified research themes and specific research options incorporating perspectives of a diverse group of stakeholders. These outputs reflect the diverse nature of challenges posed by zoonoses and should be acceptable across diseases, disciplines, and sectors. The identified research options capture the need for 'actionable research' for advancing the prevention and control of zoonoses in India

Infrared upconversion for astronomical applications

The performance of an upconversion system is examined for observation of astronomical sources in the low to middle infrared spectral range. Theoretical values for the performance parameters of an upconversion system for astronomical observations are evaluated in view of the conversion efficiencies, spectral resolution, field of view, minimum detectable source brightness and source flux. Experimental results of blackbody measurements and molecular absorption spectrum measurements using a lithium niobate upconverter with an argon-ion laser as the pump are presented. Estimates of the expected optimum sensitivity of an upconversion device which may be built with the presently available components are given

A Physical Theory of the Competition that Allows HIV to Escape from the Immune System

Competition within the immune system may degrade immune control of viral infections. We formalize the evolution that occurs in both HIV-1 and the immune system quasispecies. Inclusion of competition in the immune system leads to a novel balance between the immune response and HIV-1, in which the eventual outcome is HIV-1 escape rather than control. The analytical model reproduces the three stages of HIV-1 infection. We propose a vaccine regimen that may be able to reduce competition between T cells, potentially eliminating the third stage of HIV-1.Comment: 5 pages, 2 figures, to appear in Phys. Rev. Let