Datalog as a parallel general purpose programming language

The increasing available parallelism of computers demands new programming languages that make parallel programming dramatically easier and less error prone. It is proposed that datalog with negation and timestamps is a suitable basis for a general purpose programming language for sequential, parallel and distributed computers. This paper develops a fully incremental bottom-up interpreter for datalog that supports a wide range of execution strategies, with trade-offs affecting efficiency, parallelism and control of resource usage. Examples show how the language can accept real-time external inputs and outputs, and mimic assignment, all without departing from its pure logical semantics

Multitask Diffusion Adaptation over Networks

Adaptive networks are suitable for decentralized inference tasks, e.g., to monitor complex natural phenomena. Recent research works have intensively studied distributed optimization problems in the case where the nodes have to estimate a single optimum parameter vector collaboratively. However, there are many important applications that are multitask-oriented in the sense that there are multiple optimum parameter vectors to be inferred simultaneously, in a collaborative manner, over the area covered by the network. In this paper, we employ diffusion strategies to develop distributed algorithms that address multitask problems by minimizing an appropriate mean-square error criterion with $\ell_2$-regularization. The stability and convergence of the algorithm in the mean and in the mean-square sense is analyzed. Simulations are conducted to verify the theoretical findings, and to illustrate how the distributed strategy can be used in several useful applications related to spectral sensing, target localization, and hyperspectral data unmixing.Comment: 29 pages, 11 figures, submitted for publicatio

Shaping Global Partnerships for a Post-2015 World

As we discuss the post-2015 development agenda, how can we empower global partnerships to achieve the transformational change we need for a better future? This article provides lessons and best practices from six diverse initiatives on applying the collective impact approach on a global scale -- how to develop a common agenda, operate effective shared measurement systems, support and coordinate activities, facilitate communication, and provide strong governance for global collaborative efforts.The report uses a collective impact lens to research and evaluate a range of global partnerships, with a particular emphasis on these six diverse initiatives: Roll Back Malaria Partnership, Global Alliance for Improved Nutrition, Global Road Safety Partnership, the World Economic Forum's New Vision for Agriculture, the Global Partnership for Education, and the World Wide Fund for Nature

A cryogenically cooled, multidetector spectrometer for infrared astronomy

A liquid helium-cooled, 24 detector grating spectrometer was developed and used for low resolution astronomical observations in the 5 to 14 micron spectral range. The instrument operated on the 91 cm Kuiper Airborne Observatory, the 3 m IRTF (Mauna Kea), the 3 m Shane telescope Observatory, the 3 m Shane telescope (Lick Observatory), and the 152 cm NASA and University of Arizona telescope. The detectors are discrete Si:Bi photoconductors with individual metal oxide semiconductor field effect transistor preamplifiers operating at 4 K. The system uses a liquid helium-cooled slit, order-sorter filter, collimator mirror, grating, and camera mirror arranged in a Czerny-Turner configuration with a cold stop added between the collimator mirror and the grating. The distances between components are chosen so that the collimator mirror images the secondary mirror of the telescope onto the cold stop, thus providing a very effective baffle. Scattered radiation is effectively reduced by using liquid helium-cooled, black baffles to divide the spectrometer into three separate compartments. The system noise-equivalent flux density, when used on the 152 cm telescope from 8 to 13 microns with a resolving power of 50, is 4.4 x 10 to the minus 17th power W/sq cm micron square root of Hz. The main applications are for measuring continuum radiation levels and solid state emission and absorption features in regions of star and planet formation

Developing interest management techniques in distributed interactive simulation using Java

Bandwidth consumption in distributed real time simulation, or networked real time simulation, is a major problem as the number of participants and the sophistication of joint simulation exercises grow in size. The paper briefly reviews distributed real time simulation and bandwidth reduction techniques and introduces the Generic Runtime Infrastructure for Distributed Simulation (GRIDS) as a research architecture for studying such problems. GRIDS uses Java abstract classes to promote distributed services called thin agents, a novel approach to implementing distributed simulation services, such as user defined bandwidth reduction mechanisms, and to distributing the executable code across the simulation. Thin agents offer the advantages of traditional agents without the overhead imposed by mobility or continuous state, which are unnecessary in this context. We present our implementation and some predicted results from message reduction studies using thin agent

Is Religion an Evolutionary Adaptation?

Religious people talk about things that cannot be seen, stories that cannot be verified, and beings and forces beyond the ordinary. Perhaps their gods are truly at work, or perhaps in human nature there is an impulse to proclaim religious knowledge. If so, it would have to have arisen by natural selection. It is hard to imagine how natural selection could have produced such an impulse. There is a debate among evolutionary scientists about whether or not there is any adaptive advantage to religion at all (Bulbulia 2004a; Atran and Norenzayan 2004). Some believe that it has no adaptive value itself and that it is just a hodge podge of of behaviors that have evolved because they are adaptive in other non-religious contexts. The agent-based simulation described in this article shows that a central unifying feature of religion, a belief in an unverifiable world, could have evolved along side of verifiable knowledge. The simulation makes use of an agent-based communication model with two types of information: verifiable information (real information) about a real world and unverifiable information (unreal information) about about an imaginary world. It examines the conditions necessary for the communication of unreal information to evolved along side the communication of real information. It offers support for the theory that religion is an adaptive complex and it disputes the theory that religion is a byproduct of unrelated adaptive processes.Religion, Myth, Deception, Empirical Reasoning, Rationality