Ngāti Tāwhaki ki Ngāpūtahi: A View on Enabling Their Social Architecture

Socially Responsible Architecture is the way in which an architect practices architecture, but more so the way in which they relate and integrate their clients. This thesis explores the nature of a socially responsible architecture through a series of social interactions with the people of Ngāti Tāwhaki ki Ngāpūtahi. Aiming to understand what are the most appropriate design decisions for their architecture and their hapū's future. This thesis is chronologically taught by real people (the clients of the project) and the lessons learnt through my social interaction with these clients are attributed to the main contention of this thesis, Social Architecture. The design decision-making process for a newly proposed marae at Ngāpūtahi, in Te Urewera, is the means to which I understand how this process differs from mainstream or conventional architectural practice. The means to which I understand what the most appropriate way of practicing this architecture is through an understanding of Kaupapa Māori theory but more so understanding my clients through the relationships that I have formed with them. Within this thesis the nature of these relationships and the way in which they originated are explored. It is an exploration into not only the nature of this architectural project but also an exploration into how my contentions about the nature of this socially responsible architecture developed. Thus a personal insight into how my learning developed throughout the process

Special issue : The Human Intestinal Microbiota

Peer reviewedPublisher PD

A multinomial logit model of college stopout and dropout behavior

Studies of college attrition typically assume that all attrition is permanent. We use data from the 1990/94 Beginning Postsecondary Survey to distinguish between long-term dropout and short-term stopout behavior in order to test that assumption. We find significant differences between those who stop out and those who drop out in the first year. Failure to recognize these differences biases the results of standard attrition models and hence may cause policy makers to pursue inappropriate policy initiatives or incorrectly target at-risk populations. Furthermore, the type of financial aid received is found to have a differential impact on stopout versus dropout probabilities

Are the factors affecting dropout behavior related to initial enrollment intensity for college undergraduates?

We use data from the 1990/94 Beginning Post-Secondary Survey to determine whether the factors associated with long-term attrition from higher education differ for students who initially enrolled part-time as compared to for students who initially enrolled full-time. Using a two-stage sequential decision model to analyze the initial enrollment intensity decision jointly with attrition, we find no evidence of correlation in the unobservables that necessitates joint estimation, but substantial evidence that the factors associated with attrition differ by initial enrollment status. The timing of initial enrollment, academic performance, parental education, household characteristics, and economic factors had a substantially greater impact on those initially enrolled full-time, while racial and ethnic characteristics had a greater impact on those initially enrolled part-time. The results of our study suggest that separate specifications are necessary to identify at-risk full-time as compared with at-risk part-time students

Effective information sharing using update logs

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1996.Includes bibliographical references (leaves 80-88).by James William O'Toole, Jr.Ph.D

Painting Doesn't Count:The Temporal Conditions of Painting

An exhibition and accompanying catalogue that examine the relations between painting and tim

Painting Doesn't Count

Painting Doesn’t Count features the work of three artists at a similar point in their careers. Having completed, or currently working towards the completion of practice based PhDs, Quin, Bracey and O’Toole’s exhibition marks the first in a series of exhibitions, publications and proposed conferences that examine the relations between Art and Time. The three artists are members of the Art and Time Research Group, founded by James Quin at LICA (Lancaster Institute for the Contemporary Arts), at Lancaster University. Andrew Bracey, James Quin and M.B. O’Toole present work that responds to, and remediate extant works of art. Bracey re-paints Fra Angelico’s 1441 Florentine fresco, The Mocking of Christ. James Quin repeats images from the library scene in Andrei Tarkovsky’s 1972 science fiction film Solaris, and M.B O’Toole offers insights into the relations between the space of poetry and painting through a timely interrogation of Stéphane Mallarmé’s seminal 1897 modernist work, Un Coup De Des N’abolira Le Hasard (A throw of the dice will never abolish chance). A work of art is what Andre Malraux described as ‘an object, but it is also an encounter with time’. What connects the objects presented by Bracey, Quin and O’Toole are the ways in which temporality is at work. For all three artists, conversations between simultaneity and succession are in play, combined with a sense that the past is being reconfigured in the present. The exhibition and catalogue were made possible through LICA research funding

TöRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesis

Neural networks can represent and accurately reconstruct radiance fields for static 3D scenes (e.g., NeRF). Several works extend these to dynamic scenes captured with monocular video, with promising performance. However, the monocular setting is known to be an under-constrained problem, and so methods rely on data-driven priors for reconstructing dynamic content. We replace these priors with measurements from a time-of-flight (ToF) camera, and introduce a neural representation based on an image formation model for continuous-wave ToF cameras. Instead of working with processed depth maps, we model the raw ToF sensor measurements to improve reconstruction quality and avoid issues with low reflectance regions, multi-path interference, and a sensor's limited unambiguous depth range. We show that this approach improves robustness of dynamic scene reconstruction to erroneous calibration and large motions, and discuss the benefits and limitations of integrating RGB+ToF sensors that are now available on modern smartphones.Comment: Accepted to NeurIPS 2021. Web page: https://imaging.cs.cmu.edu/torf/ NeurIPS camera ready updates -- added quantitative comparisons to new methods, visual side-by-side comparisons performed on larger baseline camera sequence

Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

Peer reviewedPublisher PD

Predictive modeling of housing instability and homelessness in the Veterans Health Administration

OBJECTIVE: To develop and test predictive models of housing instability and homelessness based on responses to a brief screening instrument administered throughout the Veterans Health Administration (VHA). DATA SOURCES/STUDY SETTING: Electronic medical record data from 5.8 million Veterans who responded to the VHA's Homelessness Screening Clinical Reminder (HSCR) between October 2012 and September 2015. STUDY DESIGN: We randomly selected 80% of Veterans in our sample to develop predictive models. We evaluated the performance of both logistic regression and random forests—a machine learning algorithm—using the remaining 20% of cases. DATA COLLECTION/EXTRACTION METHODS: Data were extracted from two sources: VHA's Corporate Data Warehouse and National Homeless Registry. PRINCIPAL FINDINGS: Performance for all models was acceptable or better. Random forests models were more sensitive in predicting housing instability and homelessness than logistic regression, but less specific in predicting housing instability. Rates of positive screens for both outcomes were highest among Veterans in the top strata of model‐predicted risk. CONCLUSIONS: Predictive models based on medical record data can identify Veterans likely to report housing instability and homelessness, making the HSCR screening process more efficient and informing new engagement strategies. Our findings have implications for similar instruments in other health care systems.U.S. Department of Veterans Affairs (VA) Health Services Research and Development (HSR&D), Grant/Award Number: IIR 13-334 (IIR 13-334 - U.S. Department of Veterans Affairs (VA) Health Services Research and Development (HSRD))Accepted manuscrip