Heavy X-ray obscuration in the most-luminous galaxies discovered by WISE

Hot Dust-Obscured Galaxies (Hot DOGs) are hyperluminous ($L_{\mathrm{8-1000\,\mu m}}>10^{13}\,\mathrm{L_\odot}$) infrared galaxies with extremely high (up to hundreds of K) dust temperatures. The sources powering both their extremely high luminosities and dust temperatures are thought to be deeply buried and rapidly accreting supermassive black holes (SMBHs). Hot DOGs could therefore represent a key evolutionary phase in which the SMBH growth peaks. X-ray observations can be used to study their obscuration levels and luminosities. In this work, we present the X-ray properties of the 20 most-luminous ($L_{\mathrm{bol}}\gtrsim10^{14}\, L_\odot$) known Hot DOGs at $z=2-4.6$. Five of them are covered by long-exposure ($10-70$ ks) Chandra and XMM-Newton observations, with three being X-ray detected, and we study their individual properties. One of these sources (W0116$-$0505) is a Compton-thick candidate, with column density $N_H=(1.0-1.5)\times10^{24}\,\mathrm{cm^{-2}}$ derived from X-ray spectral fitting. The remaining 15 Hot DOGs have been targeted by a Chandra snapshot (3.1 ks) survey. None of these 15 is individually detected; therefore we applied a stacking analysis to investigate their average emission. From hardness-ratio analysis, we constrained the average obscuring column density and intrinsic luminosity to be log$N_H\,\mathrm{[cm^{-2}]}>23.5$ and $L_X\gtrsim10^{44}\,\mathrm{erg\,cm^{-2}\,s^{-1}}$, which are consistent with results for individually detected sources. We also investigated the $L_X-L_{6\mu\mathrm{m}}$ and $L_X-L_{bol}$ relations, finding hints that Hot DOGs are typically X-ray weaker than expected, although larger samples of luminous obscured QSOs are needed to derive solid conclusions.Comment: MNRAS, accepted 2017 November 29 . Received 2017 November 29 ; in original form 2017 October 11. 15 pages, 6 figure

Multifractal properties of power-law time sequences; application to ricepiles

We study the properties of time sequences extracted from a self-organized critical system, within the framework of the mathematical multifractal analysis. To this end, we propose a fixed-mass algorithm, well suited to deal with highly inhomogeneous one dimensional multifractal measures. We find that the fixed mass (dual) spectrum of generalized dimensions depends on both the system size L and the length N of the sequence considered, being however stable when these two parameters are kept fixed. A finite-size scaling relation is proposed, allowing us to define a renormalized spectrum, independent of size effects.We interpret our results as an evidence of extremely long-range correlations induced in the sequence by the criticality of the systemComment: 12 pages, RevTex, includes 9 PS figures, Phys. Rev. E (in press

Analysis Of Multi-Platform Mobile Application Development

The variety of mobile devices and their operating platforms has rapidly increased. With this increase come separate standards, programming languages, and distribution markets. Typically developers want to deliver their products to a variety of users encompassing various platforms; however choosing to develop using a native program for a platform can delay the development and release on another platform. Multi-platform development applications were created in order to deploy applications to various platforms in a more timely and cost efficient manner by using a single code base. The purpose of this study was to investigate the multi-platform development applications MoSync, Appcelerator, and PhoneGap, create a test application using each multi-platform development application to run on the Android emulator and iOS simulator to determine performance, and also determine which multi-platform application was best suited for allowing a developer to create a mobile application that could be utilized on a variety of platforms

Selecting Attributes for Sport Forecasting using Formal Concept Analysis

In order to address complex systems, apply pattern recongnition on their evolution could play an key role to understand their dynamics. Global patterns are required to detect emergent concepts and trends, some of them with qualitative nature. Formal Concept Analysis (FCA) is a theory whose goal is to discover and to extract Knowledge from qualitative data. It provides tools for reasoning with implication basis (and association rules). Implications and association rules are usefull to reasoning on previously selected attributes, providing a formal foundation for logical reasoning. In this paper we analyse how to apply FCA reasoning to increase confidence in sports betting, by means of detecting temporal regularities from data. It is applied to build a Knowledge-Based system for confidence reasoning.Comment: Paper 3 for the Complex Systems in Sports Workshop 2011 (CS-Sports 2011

The Potential of Cacao Agribusiness for Poverty Alleviation in West Sumatra

The cacao industry has played an important role in terms of export earnings and employment opportunities in Indonesia since 1980s. It is the main source of income for more than one million smallholder farmers in Indonesia, who are considered poor. Most planted areas of cacao are in Eastern Indonesia; however, cacao production has developed in Western Indonesia recently, with West Sumatra designated as the area of central production. Due to the importance of cacao industry in the Indonesian economy, there is a big opportunity to explore the potential of the industry in poverty alleviation. The study uses the participatory impact pathway analysis (PIPA) method. It is a new approach to formulate a development strategy and policies proposed by the Institutional Learning and Change. This approach is used because it: (1) covers impact analysis in order to investigate the potential contribution of cacao agribusiness development to poverty alleviation, which is not covered by other participatory approaches; and (2) can be used to identify stakeholders‟ relationships for cacao agribusiness development. The use of PIPA in this study involves various tools: a participatory workshop, surveys and semi-structured interviews. Problems facing the cacao industry were identified through the workshop, including low yields and price and price instability. Lack of knowledge by farmers of agronomic practices and low quality of seedlings were considered to be the main causes of low yields by the participants. Low price of cacao beans was thought to be mainly caused by low quality of cacao beans while lack of cooperation between farmers and the village cooperative and lack of a farmers‟ association were considered to be the main factors affecting price instability. Farmer survey data results show slightly different priorities from the workshop. Most cacao farmers disagreed on the problem of low yields and low price of cacao beans but a high proportion agreed on the problem of price instability and confirmed that cacao farmers face a problem of low quality of cacao beans. Most farmers do not know the cause of price instability, while improper fermentation was agreed as the main factor causing the low quality of cacao beans.agribusiness economics and management, international development, farm management., Agribusiness, Farm Management, International Development,

Modelling Spatial Regimes in Farms Technologies

We exploit the information derived from geographical coordinates to endogenously identify spatial regimes in technologies that are the result of a variety of complex, dynamic interactions among site-specific environmental variables and farmer decision making about technology, which are often not observed at the farm level. Controlling for unobserved heterogeneity is a fundamental challenge in empirical research, as failing to do so can produce model misspecification and preclude causal inference. In this article, we adopt a two-step procedure to deal with unobserved spatial heterogeneity, while accounting for spatial dependence in a cross-sectional setting. The first step of the procedure takes explicitly unobserved spatial heterogeneity into account to endogenously identify subsets of farms that follow a similar local production econometric model, i.e. spatial production regimes. The second step consists in the specification of a spatial autoregressive model with autoregressive disturbances and spatial regimes. The method is applied to two regional samples of olive growing farms in Italy. The main finding is that the identification of spatial regimes can help drawing a more detailed picture of the production environment and provide more accurate information to guide extension services and policy makers

XMMPZCAT: A catalogue of photometric redshifts for X-ray sources

The third version of the XMM-Newton serendipitous catalogue (3XMM), containing almost half million sources, is now the largest X-ray catalogue. However, its full scientific potential remains untapped due to the lack of distance information (i.e. redshifts) for the majority of its sources. Here we present XMMPZCAT, a catalogue of photometric redshifts (photo-z) for 3XMM sources. We searched for optical counterparts of 3XMM-DR6 sources outside the Galactic plane in the SDSS and Pan-STARRS surveys, with the addition of near- (NIR) and mid-infrared (MIR) data whenever possible (2MASS, UKIDSS, VISTA-VHS, and AllWISE). We used this photometry data set in combination with a training sample of 5157 X-ray selected sources and the MLZ-TPZ package, a supervised machine learning algorithm based on decision trees and random forests for the calculation of photo-z. We have estimated photo-z for 100,178 X-ray sources, about 50% of the total number of 3XMM sources (205,380) in the XMM-Newton fields selected to build this catalogue (4208 out of 9159). The accuracy of our results highly depends on the available photometric data, with a rate of outliers ranging from 4% for sources with data in the optical+NIR+MIR, up to $\sim$40% for sources with only optical data. We also addressed the reliability level of our results by studying the shape of the photo-z probability density distributions.Comment: 16 pages, 14 figures, A&A accepte