Distancing when undertaking first person action inquiry: Two devices

Action Inquiry is a methodology with the desired outcome of research action producing systemic change. In the context of a doctoral study seeking to explore how art-based pedagogies may empower educational practice, Action Inquiry was an obvious choice where empowerment involves social work practitioners exploring this question together. As part of a participatory approach, a process of self-examination is integral to the author’s inquiry as a means of contextualising professional practice in terms of social, cultural and political dynamics, and as a means to appreciate the journeys of participants in the author’s inquiry. In this article the author discusses distancing, a process of estrangement, as a means of exploring and analysing personally generated data. Two devices are developed to enhance distancing in self-inquiry, particularly when the data is challenging because it is ‘too close’ to the inquirer. The first is a visual Johari Window (Luft and Ingram 1955), involving a series of self-portraits and collaged images related to the author’s educational journey in life. The second is a dramatic device inspired by the work of Dorothy Heathcote (Heathcote and Bolton 1995) that involves the development of a fictitious character who presents the work of the author and provides opportunities for transformative reflection. The character of William Loveday is developed during a number of educational events using an iterative spiral of planning, performance, evaluation and further performance. The inquiry shows how visual art and drama can provided potent possibilities to critique and reappraise both doctoral work and practice education through a process of distancing. The author highlights how these devices can be adapted to numerous practice situations involving self-inquiry and participatory inquiry and to empower educational practice

Cross-Modal Health State Estimation

Individuals create and consume more diverse data about themselves today than any time in history. Sources of this data include wearable devices, images, social media, geospatial information and more. A tremendous opportunity rests within cross-modal data analysis that leverages existing domain knowledge methods to understand and guide human health. Especially in chronic diseases, current medical practice uses a combination of sparse hospital based biological metrics (blood tests, expensive imaging, etc.) to understand the evolving health status of an individual. Future health systems must integrate data created at the individual level to better understand health status perpetually, especially in a cybernetic framework. In this work we fuse multiple user created and open source data streams along with established biomedical domain knowledge to give two types of quantitative state estimates of cardiovascular health. First, we use wearable devices to calculate cardiorespiratory fitness (CRF), a known quantitative leading predictor of heart disease which is not routinely collected in clinical settings. Second, we estimate inherent genetic traits, living environmental risks, circadian rhythm, and biological metrics from a diverse dataset. Our experimental results on 24 subjects demonstrate how multi-modal data can provide personalized health insight. Understanding the dynamic nature of health status will pave the way for better health based recommendation engines, better clinical decision making and positive lifestyle changes.Comment: Accepted to ACM Multimedia 2018 Conference - Brave New Ideas, Seoul, Korea, ACM ISBN 978-1-4503-5665-7/18/1

Health-related welfare prioritisation of canine disorders using electronic health records in primary care practice in the UK.

BACKGROUND: Evidence-based comparison of the disorder-specific welfare burdens of major canine conditions could better inform targeting of stakeholder resources, to maximise improvement of health-related welfare in UK dogs. Population-level disease related welfare impact offers a quantitative, welfare-centred framework for objective disorder prioritisation, but practical applications have been limited to date due to sparse reliable evidence on disorder-specific prevalence, severity and duration across the canine disease spectrum. The VetCompass™ Programme collects de-identified electronic health record data from dogs attending primary-care clinics UK-wide, and is well placed to fill these information gaps. RESULTS: The eight common, breed-related conditions assessed were anal sac disorder, conjunctivitis, dental disease, dermatitis, overweight/obese, lipoma, osteoarthritis and otitis externa. Annual period prevalence estimates (based on confirming 250 cases from total potential cases identified from denominator population of 455, 557 dogs) were highest for dental disorder (9.6%), overweight/obese (5.7%) and anal sac disorder (4.5%). Dental disorder (76% of study year), osteoarthritis (82%), and overweight/obese (70%) had highest annual duration scores. Osteoarthritis (scoring 13/21), otitis externa (11/21) and dermatitis demonstrated (10/21) highest overall severity scores. Dental disorder (2.47/3.00 summative score), osteoarthritis (2.24/3.00) and overweight/obese (1.67/3.00) had highest VetCompass Welfare Impact scores overall. DISCUSSION: Of the eight common, breed-related disorders assessed, dental disorder, osteoarthritis and overweight/obese demonstrated particular welfare impact, based on combinations of high prevalence, duration and severity. Future work could extend this methodology to cover a wider range of disorders. CONCLUSIONS: Dental disorders, osteoarthritis and overweight/obese have emerged as priority areas for health-related welfare improvement in the UK dog population. This study demonstrated applicability of a standardised methodology to assess the relative health-related welfare impact across a range of canine disorders using VetCompass clinical data

RNase MRP and the RNA processing cascade in the eukaryotic ancestor

BACKGROUND: Within eukaryotes there is a complex cascade of RNA-based macromolecules that process other RNA molecules, especially mRNA, tRNA and rRNA. An example is RNase MRP processing ribosomal RNA (rRNA) in ribosome biogenesis. One hypothesis is that this complexity was present early in eukaryotic evolution; an alternative is that an initial simpler network later gained complexity by gene duplication in lineages that led to animals, fungi and plants. Recently there has been a rapid increase in support for the complexity-early theory because the vast majority of these RNA-processing reactions are found throughout eukaryotes, and thus were likely to be present in the last common ancestor of living eukaryotes, herein called the Eukaryotic Ancestor. RESULTS: We present an overview of the RNA processing cascade in the Eukaryotic Ancestor and investigate in particular, RNase MRP which was previously thought to have evolved later in eukaryotes due to its apparent limited distribution in fungi and animals and plants. Recent publications, as well as our own genomic searches, find previously unknown RNase MRP RNAs, indicating that RNase MRP has a wide distribution in eukaryotes. Combining secondary structure and promoter region analysis of RNAs for RNase MRP, along with analysis of the target substrate (rRNA), allows us to discuss this distribution in the light of eukaryotic evolution. CONCLUSION: We conclude that RNase MRP can now be placed in the RNA-processing cascade of the Eukaryotic Ancestor, highlighting the complexity of RNA-processing in early eukaryotes. Promoter analyses of MRP-RNA suggest that regulation of the critical processes of rRNA cleavage can vary, showing that even these key cellular processes (for which we expect high conservation) show some species-specific variability. We present our consensus MRP-RNA secondary structure as a useful model for further searches

A matrix interpolation between classical and free max operations: I. The univariate case

Recently, Ben Arous and Voiculescu considered taking the maximum of two free random variables and brought to light a deep analogy with the operation of taking the maximum of two independent random variables. We present here a new insight on this analogy: its concrete realization based on random matrices giving an interpolation between classical and free settings.Comment: 14 page

Constant Size Molecular Descriptors For Use With Machine Learning

A set of molecular descriptors whose length is independent of molecular size is developed for machine learning models that target thermodynamic and electronic properties of molecules. These features are evaluated by monitoring performance of kernel ridge regression models on well-studied data sets of small organic molecules. The features include connectivity counts, which require only the bonding pattern of the molecule, and encoded distances, which summarize distances between both bonded and non-bonded atoms and so require the full molecular geometry. In addition to having constant size, these features summarize information regarding the local environment of atoms and bonds, such that models can take advantage of similarities resulting from the presence of similar chemical fragments across molecules. Combining these two types of features leads to models whose performance is comparable to or better than the current state of the art. The features introduced here have the advantage of leading to models that may be trained on smaller molecules and then used successfully on larger molecules.Comment: 18 pages, 5 figure

Ultra-compact optical auto-correlator based on slow-light enhanced third harmonic generation in a silicon photonic crystal waveguide

The ability to use coherent light for material science and applications is directly linked to our ability to measure short optical pulses. While free-space optical methods are well-established, achieving this on a chip would offer the greatest benefit in footprint, performance, flexibility and cost, and allow the integration with complementary signal processing devices. A key goal is to achieve operation at sub-Watt peak power levels and on sub-picosecond timescales. Previous integrated demonstrations require either a temporally synchronized reference pulse, an off-chip spectrometer, or long tunable delay lines. We report the first device capable of achieving single-shot time-domain measurements of near-infrared picosecond pulses based on an ultra-compact integrated CMOS compatible device, with the potential to be fully integrated without any external instrumentation. It relies on optical third-harmonic generation in a slow-light silicon waveguide. Our method can also serve as a powerful in-situ diagnostic tool to directly map, at visible wavelengths, the propagation dynamics of near-infrared pulses in photonic crystals.Comment: 20 pages, 6 figures, 38 reference

Acquiring Articles through Unmediated, User-Initiated Pay-Per-View Transactions: An Assessment of Current Practices

Depressed economic times often lead libraries to consider new practices, including alternatives to the traditional subscription model. This column discusses a pay-per-view (PPV) model for acquiring journal articles whereby a library creates an account with a content provider through which authenticated users can purchase articles at the library’s expense. To gain insight into the current use of this model, the paper draws on both a literature review and the results of a survey assessing the practices of academic libraries with experience acquiring articles through unmediated, user-initiated pay-per-view transactions. The future of the PPV model as well as issues and challenges that it raises are also considered

MicroRNAs Associated with Caste Determination and Differentiation in a Primitively Eusocial Insect

In eusocial Hymenoptera (ants, bees and wasps), queen and worker adult castes typically arise via environmental influences. A fundamental challenge is to understand how a single genome can thereby produce alternative phenotypes. A powerful approach is to compare the molecular basis of caste determination and differentiation along the evolutionary trajectory between primitively and advanced eusocial species, which have, respectively, relatively undifferentiated and strongly differentiated adult castes. In the advanced eusocial honeybee, Apis mellifera, studies suggest that microRNAs (miRNAs) play an important role in the molecular basis of caste determination and differentiation. To investigate how miRNAs affect caste in eusocial evolution, we used deep sequencing and Northern blots to isolate caste-associated miRNAs in the primitively eusocial bumblebee Bombus terrestris. We found that the miRNAs Bte-miR-6001-5p and -3p are more highly expressed in queen- than in worker-destined late-instar larvae. These are the first caste-associated miRNAs from outside advanced eusocial Hymenoptera, so providing evidence for caste-associated miRNAs occurring relatively early in eusocial evolution. Moreover, we found little evidence that miRNAs previously shown to be associated with caste in A. mellifera were differentially expressed across caste pathways in B. terrestris, suggesting that, in eusocial evolution, the caste-associated role of individual miRNAs is not conserved