Post-cataract eye drops can be avoided by depot steroid injections.

There are over 400 000 cataract operations now being performed annually in the UK. With the majority of those patients being older people, comorbidities such as dementia or arthritis can prevent patients putting in their own post-operative eye drops. Where there is a lack of family or other support, district nursing services are often called upon to administer these eye drops, which are typically prescribed four times a day for 4 weeks, thus potentially totalling 112 visits for drop instillation per patient. To reduce the burden of these post-operative eye drops on district nursing services, administration of an intra-operative sub-Tenon's depot steroid injection is possible for cataract patients who then do not require any post-operative drop instillation. As a trial of this practice, 16 such patients were injected in one year, thus providing a reduction of 1792 in the number of visits requested. Taking an estimated cost of each district nurse visit of £38, this shift in practice potentially saved more than £68 000; the additional cost of the injection over the cost of eye drops was just £8.80 for the year. This practice presents an opportunity to protect valuable community nursing resources, but advocacy for change in practice would be needed with secondary care, or via commissioners

IV. Discours

Abstract Background The Enhanced Recovery After Surgery (ERAS) programme is an approach to the perioperative care of patients which aims to improve outcomes and speed up recovery after surgery. Although the evidence base appears strong for this programme, the implementation of ERAS has been slow. This study aimed to gain an understanding of the facilitating factors and challenges of implementing the programme with a view to providing additional contextual information to aid implementation. The study had a particular focus on the nutritional elements as these have been highlighted as important. Methods The study employed qualitative research methods, guided by the Normalisation Process Theory (NPT) to explore the experiences and opinions of 26 healthcare professionals from a range of disciplines implementing the programme. Results This study identified facilitating factors to the implementation of ERAS: alignment with evidence based practice, standardising practice, drawing on the evidence base of other specialties, leadership, teamwork, ERAS meetings, patient involvement and education, a pre-operative assessment unit, staff education, resources attached to obtaining The Commissioning for Quality and Innovation (CQUIN) money, the ward layout, data collection and feedback, and adapting the care pathway. A number of implementation challenges were also identified: resistance to change, standardisation affecting personalised patient care, the buy-in of relevant stakeholders, keeping ERAS visible, information provision to patients, resources, palatability of nutritional drinks, aligning different ward cultures, patients going to non-ERAS departments, spreading the programme within the hospital, differences in health issue, and utilising a segmental approach.  Conclusions The findings presented here provide useful contextual information from diverse surgical specialties to inform healthcare providers when implementing ERAS in practice. Addressing the challenges and utilising the facilitating factors identified in this study, could speed up the rate at which ERAS is adopted, implemented and embedded

Challenges and Opportunities in Wireless Fronthaul

To date the evolution from traditional distributed radio access networks (D-RAN) towards fronthaul oriented centralized (C-RAN) architectures has imposed significant challenges for the underlying transport network. The processing and coordination benefits anticipated in C-RAN are generally underpinned with the assumption of a full fiber transport network capable of meeting the demanding performance criteria of fronthaul transport. Recent advances in Ethernet based fronthaul interfaces together with exploration of new mmWave and sub-THz spectrum bands present an opportunity for wireless solutions to also realize these fronthaul transport requirements. In this work, the requirements for promising new Ethernet based fronthaul interfaces are explored. These requirements are assessed against the measured capabilities of a state-of-the-art E-band (71-86 GHz) wireless transport solution. The experimental results are then used to forecast the performance expectations of future higher bandwidth systems operating above 100 GHz. A dimensioning and link budget analysis is performed for the various candidate spectrum bands and fronthaul interfaces to highlight the viability of fronthaul delivered over wireless transport. Finding show that transport solutions operating at mmWave and sub-THz frequencies are able to support the performance requirements of newly standardized fronthaul interface splits and as such present an opportunity to utilize wireless fronthaul transport in C-RAN architectures where fiber cannot otherwise be supported. Furthermore, analysis demonstrates that the hop lengths possible for 5G small cell configurations are well aligned with the expected inter-site distances of future dense urban cell deployments making wireless fronthaul a promising concept for realizing future C-RAN based cell densification

A Unified Line-of-Sight Probability Model for Commercial 5G Mobile Network Deployments

In this paper we present a novel analytical approach used to derive a new multi-scenario line-of-sight (LOS) probability model for cellular network deployments in the UK. The approach considers the use of lamp post databases as statistically representative geo-spatial data points for evaluation of LOS likelihood from macro cellular base stations. Crucially, the proposed model is built on a high resolution (0.25-1 m) 3D digital surface model underpinned by real network and environmental datasets and validated with supporting field measurements. This work unifies all common cell site classification types; urban, suburban and rural into a single 3D LOS statistical probability model whilst also addressing the influence of endpoint height properties up to 10 m. The contributions outlined in this paper have applications in statistical path loss modelling and coverage/outage probability. They also have direct application in deployment modelling of mmWave (millimeter wave) mobile access networks (24.25-52.6 GHz) and wireless x-haul transport networks (71-174.8 GHz)

From MinX to MinC: Semantics-Driven Decompilation of Recursive Datatypes

Reconstructing the meaning of a program from its binary executable is known as reverse engineering; it has a wide range of applications in software security, exposing piracy, legacy systems, etc. Since reversing is ultimately a search for meaning, there is much interest in inferring a type (a meaning) for the elements of a binary in a consistent way. Unfortunately existing approaches do not guarantee any semantic relevance for their reconstructed types. This paper presents a new and semantically-founded approach that provides strong guarantees for the reconstructed types. Key to our approach is the derivation of a witness program in a high-level language alongside the reconstructed types. This witness has the same semantics as the binary, is type correct by construction, and it induces a (justifiable) type assignment on the binary. Moreover, the approach effectively yields a type-directed decompiler. We formalise and implement the approach for reversing Minx, an abstraction of x86, to MinC, a type-safe dialect of C with recursive datatypes. Our evaluation compiles a range of textbook C algorithms to MinX and then recovers the original structures

Projective simulation for artificial intelligence

We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.Comment: 22 pages, 18 figures. Close to published version, with footnotes retaine

Patients' use of a home-based virtual reality system to provide rehabilitation of the upper limb following stroke

Background: A low cost, virtual reality system that translates movements of the hand, fingers and thumb into game play was designed to provide a flexible and motivating approach to increasing adherence to home based rehabilitation. Objective: Effectiveness depends on adherence, so did patients use the intervention to the recommended level. If not, what reasons did they give? Design: Prospective cohort study plus qualitative analysis of interviews. Methods: 17 patients recovering from stroke recruited to the intervention arm of a feasibility trial had the equipment left in their homes for eight weeks and were advised to use it three times a day for periods of no more than 20 minutes. Frequency and duration of use were automatically recorded. At the end of the intervention, participants were interviewed to determine barriers to using it in the recommended way. Results: Duration of use and how many days they used the equipment are presented for the 13 participants who successfully started the intervention. These figures were highly variable and could fall far short of our recommendations. There was a weak (p=0.053) positive correlation between duration and baseline reported activities of daily living. Participants reported familiarity with technology and competing commitments as barriers to use although appreciated the flexibility of the intervention and found it motivating

Correction:Using the Normalization Process Theory to qualitatively explore sense-making in implementation of the Enhanced Recovery After Surgery programme: "It's not rocket science"

[This corrects the article DOI: 10.1371/journal.pone.0195890.]

A Context-Sensing Mobile Phone App (Q Sense) for Smoking Cessation: A Mixed-Methods Study.

BACKGROUND: A major cause of lapse and relapse to smoking during a quit attempt is craving triggered by cues from a smoker's immediate environment. To help smokers address these cue-induced cravings when attempting to quit, we have developed a context-aware smoking cessation app, Q Sense, which uses a smoking episode-reporting system combined with location sensing and geofencing to tailor support content and trigger support delivery in real time. OBJECTIVE: We sought to (1) assess smokers' compliance with reporting their smoking in real time and identify reasons for noncompliance, (2) assess the app's accuracy in identifying user-specific high-risk locations for smoking, (3) explore the feasibility and user perspective of geofence-triggered support, and (4) identify any technological issues or privacy concerns. METHODS: An explanatory sequential mixed-methods design was used, where data collected by the app informed semistructured interviews. Participants were smokers who owned an Android mobile phone and were willing to set a quit date within one month (N=15). App data included smoking reports with context information and geolocation, end-of-day (EoD) surveys of smoking beliefs and behavior, support message ratings, and app interaction data. Interviews were undertaken and analyzed thematically (N=13). Quantitative and qualitative data were analyzed separately and findings presented sequentially. RESULTS: Out of 15 participants, 3 (20%) discontinued use of the app prematurely. Pre-quit date, the mean number of smoking reports received was 37.8 (SD 21.2) per participant, or 2.0 (SD 2.2) per day per participant. EoD surveys indicated that participants underreported smoking on at least 56.2% of days. Geolocation was collected in 97.0% of smoking reports with a mean accuracy of 31.6 (SD 16.8) meters. A total of 5 out of 9 (56%) eligible participants received geofence-triggered support. Interaction data indicated that 50.0% (137/274) of geofence-triggered message notifications were tapped within 30 minutes of being generated, resulting in delivery of a support message, and 78.2% (158/202) of delivered messages were rated by participants. Qualitative findings identified multiple reasons for noncompliance in reporting smoking, most notably due to environmental constraints and forgetting. Participants verified the app's identification of their smoking locations, were largely positive about the value of geofence-triggered support, and had no privacy concerns about the data collected by the app. CONCLUSIONS: User-initiated self-report is feasible for training a cessation app about an individual's smoking behavior, although underreporting is likely. Geofencing was a reliable and accurate method of identifying smoking locations, and geofence-triggered support was regarded positively by participants