Relational Parametricity for Computational Effects

According to Strachey, a polymorphic program is parametric if it applies a uniform algorithm independently of the type instantiations at which it is applied. The notion of relational parametricity, introduced by Reynolds, is one possible mathematical formulation of this idea. Relational parametricity provides a powerful tool for establishing data abstraction properties, proving equivalences of datatypes, and establishing equalities of programs. Such properties have been well studied in a pure functional setting. Many programs, however, exhibit computational effects, and are not accounted for by the standard theory of relational parametricity. In this paper, we develop a foundational framework for extending the notion of relational parametricity to programming languages with effects.Comment: 31 pages, appears in Logical Methods in Computer Scienc

Institutional Involvement and the Mental Health Effects of Perceived Neighborhood Disorder in Old Age: The Role of Personal and Divine Control

Previous research has shown that perceptions of neighborhood disorder are related to increased levels of psychological distress. Neighborhood disorder may be especially salient for older adults because the transitions associated with aging heighten the salience of the neighborhood as an arena for social interaction. A stress-process perspective suggests that the effects of neighborhood disorder on mental health may be indirect, and mediated through harm in elders' self-concepts, but also that the structural arrangements in which individuals are embedded may protect elder's mental health by protecting the self. I add to this perspective by focusing on engagement in family and religious institutions as primary indications of enmeshment in the structural arrangements of society. Using a longitudinal study of older adults, I examine whether marriage prevents the mental health effects of perceived neighborhood disorder by protecting mastery, and whether attendance at religious services and prayer protect elders' mental health by preventing loss of a second type of perceived control, sense of divine control. Results show that marriage prevents the effects of neighborhood disorder on depression and anger by preventing a loss of mastery. Further, losses in mastery strengthen the effects of neighborhood disorder on mental health, but only for women and the less educated. Neighborhood disorder is also related to loss of sense of divine control, but only for elders with greater levels of education, and religious involvement helps prevent these effects. However, this moderation provides no mental health benefits, and change in sense of divine control does not alter the relationship between neighborhood disorder and mental health. A primary contribution of this dissertation is that it places the effects of perceived neighborhood disorder in a larger structural context by demonstrating that they are contingent on engagement in the social structures which pattern human behavior and sustain the structure of society

What Makes Retirees Happier: A Gradual or 'Cold Turkey' Retirement?

This study explores the factors that affect an individual’s happiness while transitioning into retirement. Recent studies highlight gradual retirement as an attractive option to older workers as they approach full retirement. However, it is not clear whether phasing or cold turkey makes for a happier retirement. Using longitudinal data from the Health and Retirement Study, this study explores what shapes the change in happiness between the last wave of full employment and the first wave of full retirement. Results suggest that what really matters is not the type of transition (gradual retirement or cold turkey), but whether people perceive the transition as chosen or forced

Statistical algorithms improve accuracy of gene fusion detection.

Gene fusions are known to play critical roles in tumor pathogenesis. Yet, sensitive and specific algorithms to detect gene fusions in cancer do not currently exist. In this paper, we present a new statistical algorithm, MACHETE (Mismatched Alignment CHimEra Tracking Engine), which achieves highly sensitive and specific detection of gene fusions from RNA-Seq data, including the highest Positive Predictive Value (PPV) compared to the current state-of-the-art, as assessed in simulated data. We show that the best performing published algorithms either find large numbers of fusions in negative control data or suffer from low sensitivity detecting known driving fusions in gold standard settings, such as EWSR1-FLI1. As proof of principle that MACHETE discovers novel gene fusions with high accuracy in vivo, we mined public data to discover and subsequently PCR validate novel gene fusions missed by other algorithms in the ovarian cancer cell line OVCAR3. These results highlight the gains in accuracy achieved by introducing statistical models into fusion detection, and pave the way for unbiased discovery of potentially driving and druggable gene fusions in primary tumors

Assessing Progress Toward the Vision of a Comprehensive, Shared Electronic Care Plan: Scoping Review

BACKGROUND: Care plans are central to effective care delivery for people with multiple chronic conditions. But existing care plans-which typically are difficult to share across care settings and care team members-poorly serve people with multiple chronic conditions, who often receive care from numerous clinicians in multiple care settings. Comprehensive, shared electronic care (e-care) plans are dynamic electronic tools that facilitate care coordination and address the totality of health and social needs across care contexts. They have emerged as a potential way to improve care for individuals with multiple chronic conditions. OBJECTIVE: To review the landscape of e-care plans and care plan-related initiatives that could allow the creation of a comprehensive, shared e-care plan and inform a joint initiative by the National Institutes of Health and the Agency for Healthcare Research and Quality to develop e-care planning tools for people with multiple chronic conditions. METHODS: We conducted a scoping review, searching literature from 2015 to June 2020 using Scopus, Clinical Key, and PubMed; we also searched the gray literature. To identify initiatives potentially missing from this search, we interviewed expert informants. Relevant data were then identified and extracted in a structured format for data synthesis and analysis using an expanded typology of care plans adapted to our study context. The extracted data included (1) the perspective of the initiatives; (2) their scope, (3) network, and (4) context; (5) their use of open syntax standards; and (6) their use of open semantic standards. RESULTS: We identified 7 projects for e-care plans and 3 projects for health care data standards. Each project provided critical infrastructure that could be leveraged to promote the vision of a comprehensive, shared e-care plan. All the e-care plan projects supported both broad goals and specific behaviors; 1 project supported a network of professionals across clinical, community, and home-based networks; 4 projects included social determinants of health. Most projects specified an open syntax standard, but only 3 specified open semantic standards. CONCLUSIONS: A comprehensive, shared, interoperable e-care plan has the potential to greatly improve the coordination of care for individuals with multiple chronic conditions across multiple care settings. The need for such a plan is heightened in the wake of the ongoing COVID-19 pandemic. While none of the existing care plan projects meet all the criteria for an optimal e-care plan, they all provide critical infrastructure that can be leveraged as we advance toward the vision of a comprehensive, shared e-care plan. However, critical gaps must be addressed in order to achieve this vision