1,752 research outputs found
Quantum Zeno Effect Explains Magnetic-Sensitive Radical-Ion-Pair Reactions
Chemical reactions involving radical-ion pairs are ubiquitous in biology,
since not only are they at the basis of the photosynthetic reaction chain, but
are also assumed to underlie the biochemical magnetic compass used by avian
species for navigation. Recent experiments with magnetic-sensitive radical-ion
pair reactions provided strong evidence for the radical-ion-pair
magnetoreception mechanism, verifying the expected magnetic sensitivities and
chemical product yield changes. It is here shown that the theoretical
description of radical-ion-pair reactions used since the 70's cannot explain
the observed data, because it is based on phenomenological equations masking
quantum coherence effects. The fundamental density matrix equation derived here
from basic quantum measurement theory considerations naturally incorporates the
quantum Zeno effect and readily explains recent experimental observations on
low- and high-magnetic-field radical-ion-pair reactions.Comment: 10 pages, 5 figure
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"Call a Teenagerā¦ That's What I Do!" - Grandchildren Help Older Adults Use New Technologies: Qualitative Study.
BackgroundAlthough family technical support seems intuitive, there is very little research exploring this topic.ObjectiveThe objective of this study was to conduct a subanalysis of data collected from a large-scale qualitative project regarding older adults' experiences in using health information technology. Specifically, the subanalysis explored older adults' experiences with technology support from family members to inform strategies for promoting older adults' engagement with new health technologies. Although the primary analysis of the original study was theoretically driven, this paper reports results from an inductive, open-coding analysis.MethodsThis is a subanalysis of a major code identified unexpectedly from a qualitative study investigating older adults' use experience of a widespread health technology, the patient portal. A total of 24 older patients (ā„65 years) with multiple chronic conditions (Charlson Comorbidity Index >2) participated in focus groups conducted at the patients' primary clinic. While conducting the primary theoretically driven analysis, coders utilized an open-coding approach to ensure important ideas not reflected in the theoretical code book were captured. Open coding resulted in 1 code: family support. This subanalysis further categorized family support by who provided tech support, how tech support was offered, and the opinions of older participants about receiving family tech support.ResultsThe participants were not specifically asked about family support, yet themes around family assistance and encouragement for technology emerged from every focus group. Participants repeatedly mentioned that they called their grandchildren and adult children if they needed help with technology. Participants also reported that family members experienced difficulty when teaching technology use. Family members struggled to explain simple technology tasks and were frustrated by the slow teaching process.ConclusionsThe results suggest that older adults ask their family members, particularly grandchildren, to support them in the use of new technologies. However, family may experience difficulties in providing this support. Older adults will be increasingly expected to use health technologies, and family members may help with tech support. Providers and health systems should consider potential family support and engagement strategies to foster adoption and use among older patients
Auditing Predictive Models for Intersectional Biases
Predictive models that satisfy group fairness criteria in aggregate for
members of a protected class, but do not guarantee subgroup fairness, could
produce biased predictions for individuals at the intersection of two or more
protected classes. To address this risk, we propose Conditional Bias Scan
(CBS), a flexible auditing framework for detecting intersectional biases in
classification models. CBS identifies the subgroup for which there is the most
significant bias against the protected class, as compared to the equivalent
subgroup in the non-protected class, and can incorporate multiple commonly used
fairness definitions for both probabilistic and binarized predictions. We show
that this methodology can detect previously unidentified intersectional and
contextual biases in the COMPAS pre-trial risk assessment tool and has higher
bias detection power compared to similar methods that audit for subgroup
fairness.Comment: 29 pages, 7 figure
Ultra-fast excited state dynamics in green fluorescent protein: multiple states and proton transfer.
Tissue-specific regulatory elements in mammalian promoters
Transcription factor-binding sites and the cis-regulatory modules they compose are central determinants of gene expression. We previously showed that binding site motifs and modules in proximal promoters can be used to predict a significant portion of mammalian tissue-specific transcription. Here, we report on a systematic analysis of promoters controlling tissue-specific expression in heart, kidney, liver, pancreas, skeletal muscle, testis and CD4 T cells, for both human and mouse. We integrated multiple sources of expression data to compile sets of transcripts with strong evidence for tissue-specific regulation. The analysis of the promoters corresponding to these sets produced a catalog of predicted tissue-specific motifs and modules, and cis-regulatory elements. Predicted regulatory interactions are supported by statistical evidence, and provide a foundation for targeted experiments that will improve our understanding of tissue-specific regulatory networks. In a broader context, methods used to construct the catalog provide a model for the analysis of genomic regions that regulate differentially expressed genes
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