750 research outputs found
An online peer-based spiritual mentoring program for field missionaries
https://place.asburyseminary.edu/ecommonsatsdissertations/1398/thumbnail.jp
A Unified Approach to Attractor Reconstruction
In the analysis of complex, nonlinear time series, scientists in a variety of
disciplines have relied on a time delayed embedding of their data, i.e.
attractor reconstruction. The process has focused primarily on heuristic and
empirical arguments for selection of the key embedding parameters, delay and
embedding dimension. This approach has left several long-standing, but common
problems unresolved in which the standard approaches produce inferior results
or give no guidance at all. We view the current reconstruction process as
unnecessarily broken into separate problems. We propose an alternative approach
that views the problem of choosing all embedding parameters as being one and
the same problem addressable using a single statistical test formulated
directly from the reconstruction theorems. This allows for varying time delays
appropriate to the data and simultaneously helps decide on embedding dimension.
A second new statistic, undersampling, acts as a check against overly long time
delays and overly large embedding dimension. Our approach is more flexible than
those currently used, but is more directly connected with the mathematical
requirements of embedding. In addition, the statistics developed guide the user
by allowing optimization and warning when embedding parameters are chosen
beyond what the data can support. We demonstrate our approach on uni- and
multivariate data, data possessing multiple time scales, and chaotic data. This
unified approach resolves all the main issues in attractor reconstruction.Comment: 22 pages, revised version as submitted to CHAOS. Manuscript is
currently under review. 4 Figures, 31 reference
Fast and powerful heritability inference for family-based neuroimaging studies.
Heritability estimation has become an important tool for imaging genetics studies. The large number of voxel- and vertex-wise measurements in imaging genetics studies presents a challenge both in terms of computational intensity and the need to account for elevated false positive risk because of the multiple testing problem. There is a gap in existing tools, as standard neuroimaging software cannot estimate heritability, and yet standard quantitative genetics tools cannot provide essential neuroimaging inferences, like family-wise error corrected voxel-wise or cluster-wise P-values. Moreover, available heritability tools rely on P-values that can be inaccurate with usual parametric inference methods. In this work we develop fast estimation and inference procedures for voxel-wise heritability, drawing on recent methodological results that simplify heritability likelihood computations (Blangero et al., 2013). We review the family of score and Wald tests and propose novel inference methods based on explained sum of squares of an auxiliary linear model. To address problems with inaccuracies with the standard results used to find P-values, we propose four different permutation schemes to allow semi-parametric inference (parametric likelihood-based estimation, non-parametric sampling distribution). In total, we evaluate 5 different significance tests for heritability, with either asymptotic parametric or permutation-based P-value computations. We identify a number of tests that are both computationally efficient and powerful, making them ideal candidates for heritability studies in the massive data setting. We illustrate our method on fractional anisotropy measures in 859 subjects from the Genetics of Brain Structure study
Ewing\u27s sarcoma: A case report of a 52-year-old woman with recurrent tumor and literature review
Activism, affect, identification: trans documentary in France and Spain and its reception
This article explores the documentation of trans activism in France and
Spain since the 2000s. The first part addresses questions surrounding the
place of affect and narrative in documentary film, particularly in relation
to trans issues. The second part o
f the article analyses an audience case
study from a screening at the International Gay and Lesbian Film Festival
in Barcelona of
Valérie Mitteaux's
Girl or Boy, My Sex is not my Gender
(2011), considering how different viewers respond to the representatio
n
of trans identities. The article builds on qualitative research whilst
extending the exploration of sexuality and gender in previous audience
studies to a consideration of documentary film, seeking to provide a more
nuanced understanding of what audience
claims for identification in
politicised contexts mean
Digital libraries unfurled: supporting the New Zealand flag debate
This article reports on the development of an interactive web environment, backed by a digital library, that supports the creation of new flag designs. Specifically, it supports the user through an iterative design process, guided by principles drawn from the field of Vexillology. The work has been motivated by a legally binding referendum on the issue in New Zealand, planned to occur in late 2015/early 2016
Integrating Behavioral Health & Primary Care in New Hampshire: A Path Forward to Sustainable Practice & Payment Transformation
New Hampshire residents face challenges with behavioral and physical health conditions and the interplay between them. National studies show the costs and the burden of illness from behavioral health conditions and co-occurring chronic health conditions that are not adequately treated in either primary care or behavioral health settings. Bringing primary health and behavioral health care together in integrated care settings can improve outcomes for both behavioral and physical health conditions. Primary care integrated behavioral health works in conjunction with specialty behavioral health providers, expanding capacity, improving access, and jointly managing the care of patients with higher levels of acuity
In its work to improve the health of NH residents and create effective and cost-effective systems of care, the NH Citizens Health Initiative (Initiative) created the NH Behavioral Health Integration Learning Collaborative (BHI Learning Collaborative) in November of 2015, as a project of its Accountable Care Learning Network (NHACLN). Bringing together more than 60 organizations, including providers of all types and sizes, all of the state’s community mental health centers, all of the major private and public insurers, and government and other stakeholders, the BHI Learning Collaborative built on earlier work of a NHACLN Workgroup focused on improving care for depression and co-occurring chronic illness. The BHI Learning Collaborative design is based on the core NHACLN philosophy of “shared data and shared learning” and the importance of transparency and open conversation across all stakeholder groups.
The first year of the BHI Learning Collaborative programming included shared learning on evidence-based practice for integrated behavioral health in primary care, shared data from the NH Comprehensive Healthcare Information System (NHCHIS), and work to develop sustainable payment models to replace inadequate Fee-for-Service (FFS) revenues. Provider members joined either a Project Implementation Track working on quality improvement projects to improve their levels of integration or a Listen and Learn Track for those just learning about Behavioral Health Integration (BHI). Providers in the Project Implementation Track completed a self-assessment of levels of BHI in their practice settings and committed to submit EHR-based clinical process and outcomes data to track performance on specified measures. All providers received access to unblinded NHACLN Primary Care and Behavioral Health attributed claims data from the NHCHIS for provider organizations in the NH BHI Learning Collaborative.
Following up on prior work focused on developing a sustainable model for integrating care for depression and co-occurring chronic illness in primary care settings, the BHI Learning Collaborative engaged consulting experts and participants in understanding challenges in Health Information Technology and Exchange (HIT/HIE), privacy and confidentiality, and workforce adequacy. The BHI Learning Collaborative identified a sustainable payment model for integrated care of depression in primary care. In the process of vetting the payment model, the BHI Learning Collaborative also identified and explored challenges in payment for Substance Use Disorder Screening, Brief Intervention and Referral to Treatment (SBIRT). New Hampshire’s residents will benefit from a health care system where primary care and behavioral health are integrated to support the care of the whole person. New Hampshire’s current opiate epidemic accentuates the need for better screening for behavioral health issues, prevention, and treatment referral integrated into primary care. New Hampshire providers and payers are poised to move towards greater integration of behavioral health and primary care and the Initiative looks forward to continuing to support progress in supporting a path to sustainable integrated behavioral and primary care
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