Roles and Responsibilities of Nonprofit Boards: the Peace Case

This exploratory study identifies the levels of importance and fulfillment of board roles and responsibilities by nonprofit peacemaking organization board members and executive directors. It suggests a three-component framework for understanding board governance. By employing purposive non-probability sampling, this study used board governance instruments, developed by Inglis, Alexander, and Weaver\u27s (1999, 163-165), to identify a three-component framework: strategic activities, resource planning, and evaluations for nonprofit organizations whose mission is peacemaking. It examines the relevance of the framework suggested by Inglis, Alexander, and Weavers (1999, 161-165) for nonprofit peacemaking organizations. The results of this study can be used by nonprofit peacemaking organizations to improve their governance capacity and prompt future research about the governance of nonprofit peacemaking organizational boards

Electrical networks and Lie theory

We introduce a new class of "electrical" Lie groups. These Lie groups, or more precisely their nonnegative parts, act on the space of planar electrical networks via combinatorial operations previously studied by Curtis-Ingerman-Morrow. The corresponding electrical Lie algebras are obtained by deforming the Serre relations of a semisimple Lie algebra in a way suggested by the star-triangle transformation of electrical networks. Rather surprisingly, we show that the type A electrical Lie group is isomorphic to the symplectic group. The nonnegative part (EL_{2n})_{\geq 0} of the electrical Lie group is a rather precise analogue of the totally nonnegative subsemigroup (U_{n})_{\geq 0} of the unipotent subgroup of SL_{n}. We establish decomposition and parametrization results for (EL_{2n})_{\geq 0}, paralleling Lusztig's work in total nonnegativity, and work of Curtis-Ingerman-Morrow and de Verdi\`{e}re-Gitler-Vertigan for networks. Finally, we suggest a generalization of electrical Lie algebras to all Dynkin types.Comment: 14 pages, 5 figure

Selected experiments in laminar flow: An annotated bibliography

Since the 1930s, there have been attempts to reduce drag on airplanes by delaying laminar to turbulent boundary layer transition. Experiments conducted during the 1940's, while successful in delaying transition, were discouraging because of the careful surface preparation necessary to meet roughness and waviness requirements. The resulting lull in research lasted nearly 30 years. By the late 1970s, airframe construction techniques had advanced sufficiently that the high surface quality required for natural laminar flow (NLF) and laminar flow control (LFC) appeared possible on production aircraft. As a result, NLF and LFC research became widespread. This report is an overview of that research. The experiments summarized herein were selected for their applicability to small transonic aircraft. Both flight and wind tunnel tests are included. The description of each experiment is followed by corresponding references. Part One summarizes NLF experiments; Part Two deals with LFC and hybrid laminar flow control (HLFC) experiments

Constitutional rights law and its limitations: topical examples

One consequence of the post-World War II ‘rights revolution’ is the ever growing use of constitutional law to protect fundamental rights. The goal of this is not only to protect such rights by judicial enforcement, at which it can be relatively successful, but to ultimately place them beyond political contestation.[1] However, it is regularly argued that placing rights beyond political contestation is very difficult to achieve where deep and sustained disagreement over rights exists.[2

Where Will Technology Lead Us?

Artificial intelligence is a misnomer in my opinion. You get out what you put in. AI seeks to simulate intelligent human behaviour in software and computers. If you consider AI software like a big database and learns along the way. It is programmed by clever humans who create algorithms which use all of the data available and process it to give a calculated result. For example, my IPhone will tell me that it’s going to take me ten minutes to drive home when I walk onto the street from my office in Killorglin. It doesn’t know I’m going home, but it’s making a good guess that I am based on the way it’s been tracking me and my driving over the past while. It hasn’t yet figured out that on an odd Friday, I turn left instead of right and cross the road to Declan Falveys Bar for a few pints and take a taxi home. Google might make a good guess, but they clearly don’t know what’s going on inside my head! Of course, Amazon use AI to predict what they think we need to buy next, Netflix on what we want to watch, and Siri finds the answers to those questions when we’re too lazy to Google

Out of the Box: Homegrown in Greater Lafayette: The Sound of Greater Lafayette [full paper]

Students from the Honors 299 course, “Homegrown,” researched local Hispanic culture, sound, green spaces, and coffee shops, among other areas of study, as well as the role of each in establishing a sense of place