List rankings and on-line list rankings of graphs

A $k$-ranking of a graph $G$ is a labeling of its vertices from $\{1,\ldots,k\}$ such that any nontrivial path whose endpoints have the same label contains a larger label. The least $k$ for which $G$ has a $k$-ranking is the ranking number of $G$, also known as tree-depth. The list ranking number of $G$ is the least $k$ such that if each vertex of $G$ is assigned a set of $k$ potential labels, then $G$ can be ranked by labeling each vertex with a label from its assigned list. Rankings model a certain parallel processing problem in manufacturing, while the list ranking version adds scheduling constraints. We compute the list ranking number of paths, cycles, and trees with many more leaves than internal vertices. Some of these results follow from stronger theorems we prove about on-line versions of list ranking, where each vertex starts with an empty list having some fixed capacity, and potential labels are presented one by one, at which time they are added to the lists of certain vertices; the decision of which of these vertices are actually to be ranked with that label must be made immediately.Comment: 16 pages, 3 figure

More Tips: Communicating with Institutional Review Boards Over the Course of Your Project

This article focuses on the continuing review process required by Institutional Review Boards. It is a follow-up to a series of recent articles designed to help Extension Professionals navigate the university IRB process. The authors present general guidelines for the continuing review process and offer some issues and tips for success

More Tips: What If a Cooperative Extension Professional Must Work with Native American Institutional Review Boards?

This article focuses on working with tribal IRBs to conduct research or evaluations of projects on tribal lands. It is a follow up to a series of four recent articles designed to help Extension Professionals navigate the university IRB process. The authors use their experience with a community assessment project conducted in one small, remote community located on the Navajo Nation to illustrate some of the issues and tips for success

Domperidone for Drug-Induced Orthostatic Hypotension-A Review

Drug-induced orthostatic hypotension (OH) is a common side effect of heterocyclic and MAOI antidepressant medications. It usually does not respond to conservative treatment and drug treatments with mineralocorticoids or central dopaminergic antagonists such as metoclopramide have significant long-term side effects that limit their use. Domperidone, a peripherally acting dopaminergic antagonist with few side effects, has been used in a number of small clinical trials to treat OH of various etiologies. We reviewed 9 studies of domperidone in the treatment of OH. Although limited by small sample sizes and poor design, these studies generally showed successful treatment of OH by domperidone. Further controlled studies of domperidone for antidepressant induced OH in relevant patient samples are warranted

Dynamic communities in multichannel data: An application to the foreign exchange market during the 2007--2008 credit crisis

We study the cluster dynamics of multichannel (multivariate) time series by representing their correlations as time-dependent networks and investigating the evolution of network communities. We employ a node-centric approach that allows us to track the effects of the community evolution on the functional roles of individual nodes without having to track entire communities. As an example, we consider a foreign exchange market network in which each node represents an exchange rate and each edge represents a time-dependent correlation between the rates. We study the period 2005-2008, which includes the recent credit and liquidity crisis. Using dynamical community detection, we find that exchange rates that are strongly attached to their community are persistently grouped with the same set of rates, whereas exchange rates that are important for the transfer of information tend to be positioned on the edges of communities. Our analysis successfully uncovers major trading changes that occurred in the market during the credit crisis.Comment: 8 pages, 6 figures, accepted for publication in Chao

Neuroimaging Biomarkers and Cognitive Function in Non-CNS Cancer and Its Treatment: Current Status and Recommendations for Future Research

Cognitive changes in patients undergoing treatment for non-central nervous system (CNS) cancers have been recognized for several decades, yet the underlying mechanisms are not well understood. Structural, functional and molecular neuroimaging has the potential to help clarify the neural bases of these cognitive abnormalities. Structural magnetic resonance imaging (MRI), functional MRI (fMRI), diffusion tensor imaging (DTI), MR spectroscopy (MRS), and positron emission tomography (PET) have all been employed in the study of cognitive effects of cancer treatment, with most studies focusing on breast cancer and changes thought to be induced by chemotherapy. Articles in this special issue of Brain Imaging and Behavior are devoted to neuroimaging studies of cognitive changes in patients with non-CNS cancer and include comprehensive critical reviews and novel research findings. The broad conclusions that can be drawn from past studies and the present body of new research is that there are structural and functional changes associated with cancer and various treatments, particularly systemic cytotoxic chemotherapy, although some cognitive and fMRI studies have identified changes at pre-treatment baseline. Recommendations to accelerate progress include well-powered multicenter neuroimaging studies, a better standardized definition of the cognitive phenotype and extension to other cancers. A systems biology framework incorporating multimodality neuroimaging, genetics and other biomarkers will be highly informative regarding individual differences in risk and protective factors and disease- and treatment-related mechanisms. Studies of interventions targeting cognitive changes are also needed. These next steps are expected to identify novel protective strategies and facilitate a more personalized medicine for cancer patients