Mean Flow and Turbulence in a Laboratory Channel with Simulated Vegatation (HES 51)

U.S. Army Corps of Engineers, Waterways Experiment Station (Contract DACW39-94-K-0010)unpublishednot peer reviewe

Enzyme activity and dynamics in near-anhydrous conditions

Water is widely assumed to be essential for life 1, although the exact molecular basis of this requirement is unclear 2-4. Water facilitates protein motions 5-9 and although enzyme activity has been demonstrated at low hydrations in organic solvents 10-13, such non-aqueous solvents may allow the necessary motions for catalysis. To examine enzyme function in the absence of solvation and bypass diffusional constraints we have tested the ability of an esterase to catalyse alcoholysis as an anhydrous powder, using a closed reaction system in which the substrates and products of the enzyme reaction are gaseous 14-15, and where the water content can be well defined 16. At hydrations equivalent to 3 (±2) molecules of water per molecule of enzyme, activity is observed that is several orders of magnitude greater than non-enzymatic catalysis. Neutron spectroscopy indicates that the fast (≤nanosecond) global anharmonic dynamics of the anhydrous functional enzyme are heavily suppressed. The results indicate that neither hydration water nor the solvent-activated fast anharmonic dynamics are required for enzyme function. An implication of these results is that one of the essential requirements of water for life may lie with its role as a diffusion medium rather than any of its more specific properties

Association between health behaviours and religion in Austrian high school pupils:A cross-sectional survey

The prevalence of risk factors for chronic diseases such as smoking, alcohol abuse, low fruit and vegetable consumption, and lack of physical activity is high among young adults. Health behaviours are influenced by many factors and also by religious orientation, as American studies show. The aim of the present study was to explore whether a similar association with religion exists in Austria (Europe). A cross-sectional survey was carried out in seven randomly selected high schools, whereby a total of 225 11th-grade pupils (64% girls, 36% boys; average age 16.4 years) were surveyed by means of an online questionnaire. The study reveals a positive association between religion and healthy food choices as well as meal patterns. Smoking (number of cigarettes smoked daily) and alcohol consumption (getting drunk) was negatively associated with religion. These negative associations remained after adjusting for confounding factors using logistic regression analysis. Thus, the study showed that religion is associated with a reduction in these risky health behaviours in Austrian high school pupils. However, due to the limitations of the study design, causality cannot be inferred

Incorporating Personalization Features in a Hospital-Stay Summary Generation System

Most of the currently available health resources contain vast amount of information that are created by keeping the “general” population in mind, which in reality, might not be useful for anyone. One approach to providing comprehensible health information to patients is to generate summaries that are personalized to each individual. This paper details the design of a personalized hospital-stay summary generation system that tailors its content to the patient’s understanding of medical terminologies and their level of engagement in improving their own health. Our summaries were found to cover around 80% of the health concepts that were considered as important by a doctor or a nurse. An online survey conducted on 150 participants verified that our algorithm’s interpretation of the personalization parameters is representative of that of a larger population

Using Artificial Intelligence to Improve Pain Assessment and Pain Management: A Scoping Review

CONTEXT: Over 20% of US adults report they experience pain on most days or every day. Uncontrolled pain has led to increased healthcare utilization, hospitalization, emergency visits, and financial burden. Recognizing, assessing, understanding, and treating pain using artificial intelligence (AI) approaches may improve patient outcomes and healthcare resource utilization. A comprehensive synthesis of the current use and outcomes of AI-based interventions focused on pain assessment and management will guide the development of future research. OBJECTIVES: This review aims to investigate the state of the research on AI-based interventions designed to improve pain assessment and management for adult patients. We also ascertain the actual outcomes of Al-based interventions for adult patients. METHODS: The electronic databases searched include Web of Science, CINAHL, PsycINFO, Cochrane CENTRAL, Scopus, IEEE Xplore, and ACM Digital Library. The search initially identified 6946 studies. After screening, 30 studies met the inclusion criteria. The Critical Appraisals Skills Programme was used to assess study quality. RESULTS: This review provides evidence that machine learning, data mining, and natural language processing were used to improve efficient pain recognition and pain assessment, analyze self-reported pain data, predict pain, and help clinicians and patients to manage chronic pain more effectively. CONCLUSIONS: Findings from this review suggest that using AI-based interventions has a positive effect on pain recognition, pain prediction, and pain self-management; however, most reports are only pilot studies. More pilot studies with physiological pain measures are required before these approaches are ready for large clinical trial

Do NO, N2O, N2 and N2 fluxes differ in soils sourced from cropland and varying riparian buffer vegetation? An incubation study

Riparian buffers are expedient interventions for water quality functions in agricultural landscapes. However, the choice of vegetation and management affects soil microbial communities, which in turn affect nutrient cycling and the production and emission of gases such as nitric oxide (NO), nitrous oxide (N2O), nitrogen gas (N2) and carbon dioxide (CO2). To investigate the potential fluxes of the above-mentioned gases, soil samples were collected from a cropland and downslope grass, willow and woodland riparian buffers from a replicated plot scale experimental facility. The soils were re-packed into cores and to investigate their potential to produce the aforementioned gases via potential denitrification, a potassium nitrate (KNO3−) and glucose (labile carbon)-containing amendment, was added prior to incubation in a specialized laboratory DENItrification System (DENIS). The resulting NO, N2O, N2 and CO2 emissions were measured simultaneously, with the most NO (2.9 ± 0.31 mg NO m−2) and N2O (1413.4 ± 448.3 mg N2O m−2) generated by the grass riparian buffer and the most N2 (698.1 ± 270.3 mg N2 m−2) and CO2 (27,558.3 ± 128.9 mg CO2 m−2) produced by the willow riparian buffer. Thus, the results show that grass riparian buffer soils have a greater NO3− removal capacity, evidenced by their large potential denitrification rates, while the willow riparian buffers may be an effective riparian buffer as its soils potentially promote complete denitrification to N2, especially in areas with similar conditions to the current study

ABA Criminal Justice Section Task Force on College Due Process Rights and Victim Protections: Recommendations for Colleges and Universities in Resolving Allegations of Campus Sexual Misconduct

The Executive Committee of the ABA Criminal Justice Section commissioned the Task Force on College Due Process Rights and Victim Protections in November 2016. Immediately after, extensive efforts were made to find members that represented all interested parties: victims, the accused, universities, other stakeholders, and national experts. The Task Force was fully constituted in the winter of 2017, and it ended up including two voting members who were originally liaisons from the ABA Commission on Domestic and Sexual Violence and the ABA Section of Civil Rights and Social Justice. This elevation was made in recognition of their significant contributions

Chaste: an open source C++ library for computational physiology and biology

Chaste - Cancer, Heart And Soft Tissue Environment - is an open source C++ library for the computational simulation of mathematical models developed for physiology and biology. Code development has been driven by two initial applications: cardiac electrophysiology and cancer development. A large number of cardiac electrophysiology studies have been enabled and performed, including high performance computational investigations of defibrillation on realistic human cardiac geometries. New models for the initiation and growth of tumours have been developed. In particular, cell-based simulations have provided novel insight into the role of stem cells in the colorectal crypt. Chaste is constantly evolving and is now being applied to a far wider range of problems. The code provides modules for handling common scientific computing components, such as meshes and solvers for ordinary and partial differential equations (ODEs/PDEs). Re-use of these components avoids the need for researchers to "re-invent the wheel" with each new project, accelerating the rate of progress in new applications. Chaste is developed using industrially-derived techniques, in particular test-driven development, to ensure code quality, re-use and reliability. In this article we provide examples that illustrate the types of problems Chaste can be used to solve, which can be run on a desktop computer. We highlight some scientific studies that have used or are using Chaste, and the insights they have provided. The source code, both for specific releases and the development version, is available to download under an open source Berkeley Software Distribution (BSD) licence at http://www.cs.ox.ac.uk/chaste, together with details of a mailing list and links to documentation and tutorials

How inclusive, user-centered design research can improve psychological therapies for psychosis: Development of SlowMo

Real-world implementation of psychological interventions for psychosis is poor. Barriers include therapy being insufficiently usable and useful for a diverse range of people. User-centered, inclusive design approaches could improve the usability of therapy, which may increase uptake, adherence, and effectiveness. This study aimed to optimize the usability of an existing psychological intervention, Thinking Well, which targets reasoning processes in paranoia using a basic digital interface. We conducted inclusive, user-centered design research characterized by purposive sampling of extreme users from the margins of groups, ethnographic investigation of the problem context, and iterative prototyping of solutions. The UK Design Council's double diamond method was used. This consisted of 4 phases: discover, including a case series of Thinking Well, stakeholder interviews, desk research, user profiling, system mapping, and a mood board; define, consisting of workshops to synthesize findings and generate the design brief; develop, involving concept workshops and prototype testing; and deliver, in which the final minimal viable product was storyboarded and iteratively coded. Consistent with our previous work, the Thinking Well case series showed medium to large effects on paranoia and well-being and small effects on reasoning. These were maintained at follow-up despite some participants reporting difficulties with the therapy interface. Insights from the discover phase confirmed that usability was challenged by information complexity and poor accessibility. Participants were generally positive about the potential of technology to be enjoyable, help manage paranoia, and provide tailored interpersonal support from therapists and peers, although they reported privacy and security concerns. The define phase highlighted that the therapy redesign should support monitoring, simplify information processing, enhance enjoyment and trust, promote personalization and normalization, and offer flexible interpersonal support. During the develop phase over 60 concepts were created, with 2 key concepts of thoughts visualized as bubbles and therapy as a journey selected for storyboarding. The output of the deliver phase was a minimal viable product of an innovative digital therapy, SlowMo. SlowMo works by helping people to notice their worries and fast thinking habits, and encourages them to slow down for a moment to find ways of feeling safer. A Web app supports the delivery of 8 face-to-face sessions, which are synchronized to a native mobile app. SlowMo makes use of personalization, ambient information, and visual metaphors to tailor the appeal, engagement, and memorability of therapy to a diversity of needs. Feasibility testing has been promising, and the efficacy of SlowMo therapy is now being tested in a multicentered randomized controlled trial. The study demonstrates that developments in psychological theory and techniques can be enhanced by improving the usability of the therapy interface to optimize its impact in daily life. [Abstract copyright: ©Amy Hardy, Anna Wojdecka, Jonathan West, Ed Matthews, Christopher Golby, Thomas Ward, Natalie D Lopez, Daniel Freeman, Helen Waller, Elizabeth Kuipers, Paul Bebbington, David Fowler, Richard Emsley, Graham Dunn, Philippa Garety. Originally published in JMIR Mental Health (http://mental.jmir.org), 05.12.2018.