A Framework for Analyzing Nonprofit Governance and Accountability Policies and Strategies

This paper presents a framework for analyzing the sprawling topic of nonprofit governance and accountability. It distinguishes various accountability-generating mechanisms and actors, including the unit-level governing board; government policies aimed at shaping the behavior of governing boards; and a broader, natural demand for accountability, generated by an organizations many stakeholders. The aims of these accountability mechanisms and actors also vary, and include the prevention of theft and fraud; the efficient use of resources; the choice of socially valuable goals; and the effective performance of an organization in service of those goals.This publication is Hauser Center Working Paper No. 33.3. Hauser Working Paper Series Nos. 33.1-33.9 were prepared as background papers for the Nonprofit Governance and Accountability Symposium October 3-4, 2006

Post-processing partitions to identify domains of modularity optimization

We introduce the Convex Hull of Admissible Modularity Partitions (CHAMP) algorithm to prune and prioritize different network community structures identified across multiple runs of possibly various computational heuristics. Given a set of partitions, CHAMP identifies the domain of modularity optimization for each partition ---i.e., the parameter-space domain where it has the largest modularity relative to the input set---discarding partitions with empty domains to obtain the subset of partitions that are "admissible" candidate community structures that remain potentially optimal over indicated parameter domains. Importantly, CHAMP can be used for multi-dimensional parameter spaces, such as those for multilayer networks where one includes a resolution parameter and interlayer coupling. Using the results from CHAMP, a user can more appropriately select robust community structures by observing the sizes of domains of optimization and the pairwise comparisons between partitions in the admissible subset. We demonstrate the utility of CHAMP with several example networks. In these examples, CHAMP focuses attention onto pruned subsets of admissible partitions that are 20-to-1785 times smaller than the sets of unique partitions obtained by community detection heuristics that were input into CHAMP.Comment: http://www.mdpi.com/1999-4893/10/3/9

PMLB: A Large Benchmark Suite for Machine Learning Evaluation and Comparison

The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world and simulated benchmark datasets have emerged from different sources, but their organization and adoption as standards have been inconsistent. As such, selecting and curating specific benchmarks remains an unnecessary burden on machine learning practitioners and data scientists. The present study introduces an accessible, curated, and developing public benchmark resource to facilitate identification of the strengths and weaknesses of different machine learning methodologies. We compare meta-features among the current set of benchmark datasets in this resource to characterize the diversity of available data. Finally, we apply a number of established machine learning methods to the entire benchmark suite and analyze how datasets and algorithms cluster in terms of performance. This work is an important first step towards understanding the limitations of popular benchmarking suites and developing a resource that connects existing benchmarking standards to more diverse and efficient standards in the future.Comment: 14 pages, 5 figures, submitted for review to JML

Performance of Major Flare Watches from the Max Millennium Program (2001-2010)

The physical processes that trigger solar flares are not well understood and significant debate remains around processes governing particle acceleration, energy partition, and particle and energy transport. Observations at high resolution in energy, time, and space are required in multiple energy ranges over the whole course of many flares in order to build an understanding of these processes. Obtaining high-quality, co-temporal data from ground- and space- based instruments is crucial to achieving this goal and was the primary motivation for starting the Max Millennium program and Major Flare Watch (MFW) alerts, aimed at coordinating observations of all flares >X1 GOES X-ray classification (including those partially occulted by the limb). We present a review of the performance of MFWs from 1 February 2001 to 31 May 2010, inclusive, that finds: (1) 220 MFWs were issued in 3,407 days considered (6.5% duty cycle), with these occurring in 32 uninterrupted periods that typically last 2-8 days; (2) 56% of flares >X1 were caught, occurring in 19% of MFW days; (3) MFW periods ended at suitable times, but substantial gain could have been achieved in percentage of flares caught if periods had started 24 h earlier; (4) MFWs successfully forecast X-class flares with a true skill statistic (TSS) verification metric score of 0.500, that is comparable to a categorical flare/no-flare interpretation of the NOAA Space Weather Prediction Centre probabilistic forecasts (TSS = 0.488).Comment: 19 pages, 2 figures, accepted for publication in Solar Physic

Ketogenic Diet Alters Dopaminergic Activity in the Mouse Cortex [post-print]

The present study was conducted to determine if the ketogenic diet altered basal levels of monoamineneurotransmitters in mice. The catecholamines dopamine (DA) and norephinephrine (NE) and the indolamine serotonin (5HT) were quantified postmortem in six different brain regions of adult mice fed a ketogenic diet for 3 weeks. The dopamine metabolites 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA) and the serotonin metabolite 5-hydroxyindole acetic acid (5HIAA) were also measured. Tissue punches were collected bilaterally from the motor cortex, somatosensory cortex,nucleus accumbens, anterior caudate–putamen, posterior caudate–putamen and the midbrain. Dopaminergic activity, as measured by the dopamine metabolites to dopamine content ratio – ([DOPAC] + [HVA])/[DA] – was significantly increased in the motor and somatosensory cortex regions of mice fed the ketogenic diet when compared to those same areas in brains of mice fed a normal diet. These results indicate that the ketogenic diet alters the activity of the meso-cortical dopaminergic system, which may contribute to the diet\u27s therapeutic effect in reducing epileptic seizure activity