Lessons Learned From Community-Based Participatory Research in Indian Country

The purpose of this article is to share lessons learned from implementing community-based participatory research (CBPR) in Indian Country that may be generalizable to other medically underserved communities. CBPR is currently included in multiple grant announcements by the National Institute of Health and Centers for Disease Control and Prevention, but information about this methodology vs traditional research methodology is often misleading. This article addresses some common mistakes made by academic research institutes by sharing what we have learned about how CBPR can be implemented in a respectful manner. The majority of tribal Nations prefer, if not mandate, that CBPR be used in most proposed studies involving their communities today

Large–Scale Laboratory Observations of Wave Forces on a Highway Bridge Superstructure

A. Objectives The objectives of this study are to: (1) conduct the first, large-scale physical model study of wave loads on a highway bridge superstructure under realistic wave conditions and bridge geometries, and (2) evaluate the application of existing design formulas developed for deep water, wave-in-deck loading of offshore structures to shallow water, highway bridge geometries. This will aid in our understanding of the dynamic loads by hurricane waves on highway bridge superstructures and assess the accuracy of present methods for safer design of new bridges or retrofit of existing bridges. B. Scope In their 2006 report titled Wave Forces on Bridge Decks prepared for the US Department of Transportation, Office of Bridge Technology, Douglass et al. provide a synthesis of existing knowledge related to hurricane wave forces on highway bridge superstructures. Their extensive literature search found that the existing methods to evaluate wave loads on highway bridge geometries were not adequate. One of the uncertainties is due to a lack of physical model test data with highway bridge geometries using modern wave generating capabilities to simulate realistic sea states. One of their conclusions is that more research with hydraulic models is necessary to develop new analytical tools to advance bridge design. This one-year project will conduct the first-of-its-kind, large-scale, hydraulic model test of wave forces on a highway bridge superstructure cross-section, similar to those bridges that failed during Hurricanes Katrina in 2005 and Ivan in 2004. One graduate student will be trained in the area of wave-structure interaction, and two undergraduate students will be involved in this research. Project results will be disseminated through peer-reviewed publications. C. Methodology The hydraulic model study will be conducted in the Large Wave Flume at the O.H. Hinsdale Wave Research Laboratory at Oregon State University, the largest facility of its kind in North America, and in conjunction with the Kiewit Center for Infrastructure and Transportation at OSU. The model will be scaled 1:4 for length and 1:2 for time using Froude similitude. The model will be constructed of concrete and steel using a realistic cross-section and will be instrumented with sensors to provide wave conditions, impact pressures, dynamic horizontal and vertical loads, and moments. The wave climate will be derived from available buoy data and existing wave modeling studies. Existing methods developed for wave-indeck loading of offshore platforms as outlined by McConnel, Allsop and Cruickshank (2004) will be compared with the data to evaluate the accuracy of these methods. D. Relevant OTREC theme This project advances technologies leading to safer design and repair of bridges subjected to wave loadings. It will develop new knowledge in this area, will train one graduate student and two undergraduate students, and will develop national leadership in this area at Oregon State University. E. USDOT priorities Safety Assurance of Highway Structures for Extreme Events to improve the performance of bridges and other highway structures under the impacts of extreme events. Safety, Structures Research to provide highway managers and engineers with information and tools to design, build, and maintain safer and better performing infrastructure assets

Hygrothermal Performance of Insulated, Sloped, Wood-Framed Roof Assemblies

Roofs are the single enclosure element common to artificial shelters constructed by all cultures in all climate regions. The hygrothermal performance of insulated, sloped, wood-framed roof assemblies has long been of interest to building scientists and building codes alike. Requirements for the ventilation of roof assemblies have been included in building codes for more than 50 years, however moisture problems still occur. Unvented roof assemblies have been suggested as an alternate and potentially superior solution. While unvented roofs have become relatively common in the warmer southern climates of North America, some technical issues remain unclear and the need exists for further study and demonstration of the hygrothermal performance of both ventilated and unvented roof assemblies in cold northern climates. This thesis seeks to address these issues through a review of existing literature, experience and industry practice, field investigation and measurement, analytical calculation and computer simulations

The effects of cultural differences on consumers' willingness to share personal information

Consumer information is an increasingly valuable resource in the digitally interconnected modern world. Globally, the number of firms collecting and exploiting consumer information to optimize their marketing efforts is increasing rapidly. The authors determine how four cultural dimensions—power distance, masculinity, uncertainty avoidance, and long-term orientation—affect consumers’ willingness to share their personal information with firms (WTS). The authors empirically test the direct effect of national culture on WTS, as well as its moderating effect on the link between WTS and two of its key drivers, privacy concerns and perceived benefits. Drawing on regulatory focus theory, the authors develop a conceptual framework and test it using multilevel modeling on data from 15,045 consumers across 24 countries. The empirical findings demonstrate that national culture directly affects WTS and moderates the effects of both privacy concerns and perceived benefits on WTS. These results highlight the need for managers and marketers to consider international cultural differences when collecting consumer information

Additivity for a class of unital qubit channels

Additivity of the Holevo capacity is proved for product channels, under the condition that one of the channels is in a certain class of unital qubit channels, with the other completely arbitrary. This qubit class includes the depolarizing channel. As a byproduct this proves that the Holevo bound is the ultimate information capacity of such qubit channels (assuming no prior entanglement between sender and receiver). Additivity of minimal entropy and multiplicativity of p-norms are also proved under the same assumptions

Qubit Channels Can Require More Than Two Inputs to Achieve Capacity

We give examples of qubit channels that require three input states in order to achieve the Holevo capacity.Comment: RevTex, 5 page, 4 figures

Maximization of capacity and p-norms for some product channels

It is conjectured that the Holevo capacity of a product channel \Omega \otimes \Phi is achieved when product states are used as input. Amosov, Holevo and Werner have also conjectured that the maximal p-norm of a product channel is achieved with product input states. In this paper we establish both of these conjectures in the case that \Omega is arbitrary and \Phi is a CQ or QC channel (as defined by Holevo). We also establish the Amosov, Holevo and Werner conjecture when \Omega is arbitrary and either \Phi is a qubit channel and p=2, or \Phi is a unital qubit channel and p is integer. Our proofs involve a new conjecture for the norm of an output state of the half-noisy channel I \otimes \Phi, when \Phi is a qubit channel. We show that this conjecture in some cases also implies additivity of the Holevo capacity

Sample size justifications in Gait & Posture

BACKGROUND: Context regarding how researchers determine the sample size of their experiments is important for interpreting the results and determining their value and meaning. Between 2018 and 2019, the journal Gait & Posture introduced a requirement for sample size justification in their author guidelines. RESEARCH QUESTION: How frequently and in what ways are sample sizes justified in Gait & Posture research articles and was the inclusion of a guideline requiring sample size justification associated with a change in practice? METHODS: The guideline was not in place prior to May 2018 and was in place from 25th July 2019. All articles in the three most recent volumes of the journal (84-86) and the three most recent, pre-guideline volumes (60-62) at time of preregistration were included in this analysis. This provided an initial sample of 324 articles (176 pre-guideline and 148 post-guideline). Articles were screened by two authors to extract author data, article metadata and sample size justification data. Specifically, screeners identified if (yes or no) and how sample sizes were justified. Six potential justification types (Measure Entire Population, Resource Constraints, Accuracy, A priori Power Analysis, Heuristics, No Justification) and an additional option of Other/Unsure/Unclear were used. RESULTS: In most cases, authors of Gait & Posture articles did not provide a justification for their study's sample size. The inclusion of the guideline was associated with a modest increase in the percentage of articles providing a justification (16.6-28.1%). A priori power calculations were the dominant type of justification, but many were not reported in enough detail to allow replication. SIGNIFICANCE: Gait & Posture researchers should be more transparent in how they determine their sample sizes and carefully consider if they are suitable. Editors and journals may consider adding a similar guideline as a low-resource way to improve sample size justification reporting