Increasing EHR Use for Quality Improvement in Community Health Centers: The Role of Networks

Describes how five community health center networks helped implement electronic health records to improve chronic and preventive care, as well as the obstacles they faced, including limited software capabilities, funding, and ability to share resources

Predictive control for energy management in all/more electric vehicles with multiple energy storage units

The paper describes the application of Model Predictive Control (MPC) methodologies for application to electric and hybrid-electric vehicle drive-train formats incorporating multiple energy/power sources. Particular emphasis is given to the co-ordinated management of energy flow from the multiple sources to address issues of extended vehicle range and battery life-time for all-electric drive-trains, and emissions reduction and drive-train torsional oscillations, for hybrid-electric counterparts, whilst accommodating operational constraints and, ultimately, generic non-standard driving cycles

Emergency braking for free piston energy converters

Free piston energy converters are a potential technology for future hybrid vehicles, as well as stationary power generation applications. A candidate 2-stroke system comprises of two opposing combustion chambers with a common piston rod, and integrated with a tubular permanent magnet electrical machine for the conversion of mechanical to electrical energy. A key issue for the ultimate adoption of such systems, however, is their robustness in the event of a fault to enable a safe shutdown, with minimal mechanical or electrical damage. The paper considers system braking issues and the importance of early fault detection. Results are presented to demonstrate the effectiveness of passive and active braking techniques for a range of dc-link supply voltage and operating output power

A Mixed-Method Investigation into Therapeutic Yoga as an Adjunctive Treatment for People Recovering from Substance Use Disorders

© 2020, The Author(s). Mind Body Connect (MBC) is a charity which uses therapeutic yoga as a vehicle of change for marginalized populations. Alongside MBC, Sheffield Hallam University’s SHU Strength researchers carried out this study aiming to: (1) Gauge the impact of therapeutic yoga classes upon the mood state of people with a Substance Use Disorder (SUD) and (2) Explore the perceived benefits of therapeutic yoga class participation. An adapted shortened Profile of Mood States (POMS) was completed before and after each yoga class. A comparison of means with paired sample T-Test and Cohen’s D was then carried out. Participants who attended 6+ classes were interviewed. Findings were then converged. Before and after measurements of anger, sadness, tiredness, worry, confusion, energy and relaxation were taken, Classes were held at SHU for service users from a Phoenix Future’s (PF) rehabilitation centre. A single yoga class significantly relaxed participants and reduced negative mood states. Interview data covered a range of perceived benefits including the use of yogic down-regulation techniques as daily coping strategies. The MBC yoga programme appears beneficial as an adjunctive therapy for PF residents. Future SHU Strength research shall focus on the mid-long-term exercise habits of the recovery community and the impact of the MBC yoga programme upon the early recovery period of detoxification

Incidence and repetition of deliberate self-harm in three remote Indigenous communities in Far North Queensland, Australia

Aim: To investigate the incidence and repetition of deliberate self-harm (DSH) using data from a clinical file audit for the period 2006-2011 in three remote Indigenous communities in Far North Queensland. Background: Deliberate self-harm (DSH) is a global public health concern. It is the single most important risk factor for suicide (Cooper, et al., 2005) with a higher frequency over time associated with a greater acquired ability for suicide (Willoughby, et al., 2015). Therefore, understanding the incidence and repetition of DSH is crucial for services and practitioners concerned with the prevention of suicidal behavior (Perry, et al., 2012). Method: The study communities are located on the Cape York Peninsula in Far North Queensland, Australia. These communities are very remote, experience a similarly low sociodemographic ranking, and the great majority of the population are Indigenous Australians. A clinical file audit was performed at the primary health clinic in each community for the six year period from 1st January 2006 to 31st December 2011. Presentations involving DSH were extracted and analysed to characterise the incidence and repetition of DSH in these communities

Towards extracting 3-D structural representations of AGR core fuel channels from 2-D in-core inspection videos

Remote Visual Inspection (RVI) of Advanced Gas-cooled Reactor (AGR) nuclear power stations allows engineers to gain an understanding of the AGR graphite core health by investigating the incorporated fuel channels. During planned, periodic outages, video footage of the pre-selected fuel channels is acquired using specialist inspection tools and is subsequently taken offline for further analysis using visualization techniques. Current methods of visualization however provide limited structural information due to the loss of depth information as a direct result of the image acquisition process. This paper introduces a new bespoke 3-D reconstruction framework to recover lost depth information to produce 3-D point cloud reconstructions of fuel channels from inspection videos. We also present here a new, lab based, experimental rig setup with which we effectively captured data under lab controlled conditions to verify our 3-D reconstruction algorithms. Our proposed method is tested on 2-D in core inspection videos in addition to the footage captured within laboratory conditions and outperforms state-of-the-art incremental reconstruction frameworks whilst producing a more representative 3-D point cloud for improved in-core visualization

3-D advanced gas-cooled nuclear reactor fuel channel reconstruction using structure-from-motion

During planned, periodic outages, a selection of fuel channels within the UK fleet of Advanced Gas-cooled Reactor (AGR) cores are inspected using specialist tools which record video footage and other sensory data for each channel which undergoes inspection. Current visualization techniques comprise of manually produced montages by inspection engineers of points of interest (i.e. structural defects) and 2-D panoramic images of the fuel channels automatically produced using bespoke image stitching software. Both techniques however provide limited structural information due to the loss of depth data as a result of the image formation process. By recovering the depth information from the footage, a 3-D model could be constructed and subsequently, allow for more accurate profiling of specific defects observed during inspection in addition to obtaining the fuel channels structure using existing footage. This work explores the preliminary application of a 3-D visualization technique known as Structure-from-Motion (SfM) which aims to obtain 3-D information by exploiting image correspondences across multiple viewpoints of the same scene in the RVI footage. This paper investigates the difficulties of applying state-of-the-art SfM to RVI footage and we present new techniques to improve feature correspondence searching in repetitive, non-descript environments